subject:(predictive model)

Delft University of Technology

1. Lindo, H.M.A. Predicting the Individual Pathway of the Kidney Donor and Acceptor Patient based on Preoperative Patient Data:.

Degree: 2014, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:c41946a4-011d-4c66-89a4-6db15b054145

► Background – With the growing costs in healthcare and the growing need for care, prediction models offer great opportunities for improving efficiency and patient outcome.… (more)

▼ Background – With the growing costs in healthcare and the growing need for care, prediction models offer great opportunities for improving efficiency and patient outcome. With these models, one can manage the different outcomes as efficient as possible and next to that, understand which variables influence the patient’s pathway. The Erasmus Medical Centre in Rotterdam provided the data of the kidney transplantation patients (donors and acceptors) to examine the effects of different preoperative variables, such as age, body mass index and gender, on the operating time, the surgical complexity, the occurrence of peri- and postoperative complications and the length of stay. Prediction models using this data can give insight into the patients and the processes, it can improve the efficiency, and make it possible to steer the process when necessary. Goal – The goal of this retrospective thesis study is to gain insight into the patient groups and processes and to create a model able to predict the patients pathway through analyzing preoperative patient data. This model should lead to higher efficiency and better patient outcomes and give insight into the variables influencing the patients pathway for both the kidney donors and acceptors. Additionally, this study should provide a practical guideline for prediction model use to achieve the best results in efficiency and patient outcome. Materials and methods - Two sets of clinical histories were used for both the kidney donors and the acceptors: one for deriving the predictive equations and another for validation. For deriving the predictive equations, preoperative patient data was collected from 282 donors and 269 acceptors admitted to the Erasmus Medical Center (EMC) in the period of 2011-2012. For the validation of the equations, patient data was collected from 141 donor patients and 135 acceptor patients admitted in the year 2013. The data includes variables such as gender, age, patient’s body mass index (BMI) and medical history. The variables were selected with the consultation of previous research and experts in the kidney transplantation field. Regression analysis was used to identify the risk factors for each outcome and to estimate the predictive equations used for predicting the patients pathway. Results – For the 80% best predictions, the validation shows that the operating time can be predicted with an average deviation of 11,9% (21,4 minutes) from the actual operating time for the donors and 12,8% (17,0 minutes) for the acceptors. Relevant features for predicting the operating time include gender, BMI, number of veins and arteries, surgeon and surgical technique for the donors and gender, ethnicity and previous transplantations for the acceptors. The length of stay can be predicted with an average deviation of 17,9% (0,6 days) from the actual length of stay for the donors and 16,6% (2,3 days) for the acceptors. The relevant features for predicting the length of stay include gender and pulmonary history for the donors and age of the donor, BMI of the donor… Advisors/Committee Members: Dankelman, J., Guedon, A.C.P..

Subjects/Keywords: Predictive model

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APA (6^th Edition):

Lindo, H. M. A. (2014). Predicting the Individual Pathway of the Kidney Donor and Acceptor Patient based on Preoperative Patient Data:. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:c41946a4-011d-4c66-89a4-6db15b054145

Chicago Manual of Style (16^th Edition):

Lindo, H M A. “Predicting the Individual Pathway of the Kidney Donor and Acceptor Patient based on Preoperative Patient Data:.” 2014. Masters Thesis, Delft University of Technology. Accessed December 06, 2019. http://resolver.tudelft.nl/uuid:c41946a4-011d-4c66-89a4-6db15b054145.

MLA Handbook (7^th Edition):

Lindo, H M A. “Predicting the Individual Pathway of the Kidney Donor and Acceptor Patient based on Preoperative Patient Data:.” 2014. Web. 06 Dec 2019.

Vancouver:

Lindo HMA. Predicting the Individual Pathway of the Kidney Donor and Acceptor Patient based on Preoperative Patient Data:. [Internet] [Masters thesis]. Delft University of Technology; 2014. [cited 2019 Dec 06]. Available from: http://resolver.tudelft.nl/uuid:c41946a4-011d-4c66-89a4-6db15b054145.

Council of Science Editors:

Lindo HMA. Predicting the Individual Pathway of the Kidney Donor and Acceptor Patient based on Preoperative Patient Data:. [Masters Thesis]. Delft University of Technology; 2014. Available from: http://resolver.tudelft.nl/uuid:c41946a4-011d-4c66-89a4-6db15b054145

University of Waterloo

2. Tejeda-Iglesias, Manuel. A Framework for Explicit Model Predictive Control using Adjustable Robust Optimization and Economic Optimization of an Industrial-Scale Sulfuric Acid Plant.

Degree: 2018, University of Waterloo

URL: http://hdl.handle.net/10012/14276

► Optimization plays an important role in the operation of chemical engineering systems. Due to their typical size, different optimization tools and techniques are required to… (more)

▼ Optimization plays an important role in the operation of chemical engineering systems. Due to their typical size, different optimization tools and techniques are required to improve the efficiency in process operations. In this thesis, a mathematical tool is developed to address the issue of optimal control for linear systems under uncertainty. Also, a comprehensive plant model describing the behaviour of an industrial-scale Sulphuric Acid plant is developed to assist in identification of the optimal operating conditions under uncertainty Model predictive control (MPC) is considered an attractive strategy for the optimal control of complex chemical engineering systems. Conventional MPC involves solving an optimization problem online to determine the control actions that minimize a performance criterion function. The high computational expense associated with conventional MPC may make its application challenging for large-scale systems. Explicit MPC has been developed to solve the optimization problem offline. In this work, adjustable robust optimization (ARO) is used to obtain the explicit solution to the MPC optimization problem offline for discrete-time linear time invariant systems with constraints on inputs and states. In the robust model formulation an uncertain additive time-varying error is introduced to account for model uncertainty resulting from plant-model mismatch caused by un-measurable disturbances or process nonlinearities. The explicit solution is an optimal time-varying sequence of feedback control laws for the control inputs parameterized by the system’s states. The control laws are evaluated in a time-varying manner when the process is online using state measurements. This study shows that the resulting control laws ensure the implemented control actions maintain the system states within their feasible region for any realizations of the uncertain parameter within the uncertainty set. Three case studies are presented to demonstrate the proposed approach and to highlight the benefits and limitations of this method. The optimal operating condition to which an optimal controller will drive a large industrial-scale plant is identified using a different set of tools. In this thesis, an industrial-scale sulfuric acid plant is considered. The production of sulfuric acid is an important process due to its many applications and its use as a mitigation strategy for Sulphur dioxide (SO2). The reactor of the sulfuric acid plant has been the focus of many studies, and thus there has been very limited works in the literature that have analyzed the complete sulfuric acid plant. In this work, the flowsheet for an industrial-scale sulfuric acid plant with scrubbing tower is presented. The model is developed in Aspen Plus V8.8 and it is validated using historical data from an actual industrial plant. A sensitivity analysis was carried out, followed by optimization using two alternative objective functions: maximization of plant profitability or productivity. The optimization was extended to consider uncertainty…

Subjects/Keywords: Model Predictive Control

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APA (6^th Edition):

Tejeda-Iglesias, M. (2018). A Framework for Explicit Model Predictive Control using Adjustable Robust Optimization and Economic Optimization of an Industrial-Scale Sulfuric Acid Plant. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/14276

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Tejeda-Iglesias, Manuel. “A Framework for Explicit Model Predictive Control using Adjustable Robust Optimization and Economic Optimization of an Industrial-Scale Sulfuric Acid Plant.” 2018. Thesis, University of Waterloo. Accessed December 06, 2019. http://hdl.handle.net/10012/14276.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Tejeda-Iglesias, Manuel. “A Framework for Explicit Model Predictive Control using Adjustable Robust Optimization and Economic Optimization of an Industrial-Scale Sulfuric Acid Plant.” 2018. Web. 06 Dec 2019.

Vancouver:

Tejeda-Iglesias M. A Framework for Explicit Model Predictive Control using Adjustable Robust Optimization and Economic Optimization of an Industrial-Scale Sulfuric Acid Plant. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/10012/14276.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tejeda-Iglesias M. A Framework for Explicit Model Predictive Control using Adjustable Robust Optimization and Economic Optimization of an Industrial-Scale Sulfuric Acid Plant. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/14276

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Ontario Institute of Technology

3. Gillett, Jonathan. Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers.

Degree: 2016, University of Ontario Institute of Technology

URL: http://hdl.handle.net/10155/884

► The ability to predict financial markets has tremendous potential to limit exposure to risk and provide better assurances of annualized gains. In this thesis, a… (more)

▼ The ability to predict financial markets has tremendous potential to limit exposure to risk and provide better assurances of annualized gains. In this thesis, a model for predicting the future daily price of Bitcoin is proposed and evaluated in comparison to that of a purely random model. Bitcoin is a novel digital currency that relies on cryptography instead of a central authority to verify transactions. Without a central authority, Bitcoin requires a complete list of all transactions to be made public so that they can be verified by all users. This unique feature of Bitcoin, where all transactions are public, is exploited by the model to predict the future price directions based on the actions of Bitcoin users. The daily activity of the markets, aggregate network features, and the actions of major network influencers are all used as features for the predictive model. Where major network influencers are defined as users that accumulate a disproportionate amount of wealth within the Bitcoin network compared to others. The information about the actions of all Bitcoin users are extracted from the blockchain and stored in a relational database for ease of use. Two metrics were created to identify the major network influencers based on the history of their actions recorded on the blockchain. The first metric, based on the concept of an h-index, often used in academia to rank authors by their citations, is used to rank users by the amount of wealth they accumulate monthly. The second metric is based on the optimization of multiple objectives, the maximum increase in wealth with the least amount of activity using Pareto optimization. All of the major network influencers identified were then used as features, in combination with aggregate network features, and market data, to test and evaluate several predictive models. The models created were based on non-linear equations, support vector machines, decision trees, and XGBoost; all evaluated and compared using the same data. The XGBoost model consistently proved to be much more accurate than all other models and was used for the final set of experiments. The XGBoost model was compared to that of a purely random Monte Carlo model using the entire history of data for the period of 2013???2016. The first set of experiments were conducted using various sizes of training and testing data, in each case the XGBoost model had an accuracy 20% greater than that of the Monte Carlo model. For the final experiments, the model was tested in a realistic scenario, predicting the price direction for each future day, while also being re-trained using the results of each new day. The XGBoost model achieved a much better performance in comparison to the Monte Carlo model, which had approximately 50% accuracy, whereas the XGBoost model had 70%???79% accuracy. Advisors/Committee Members: Rahnamayan, Shahryar, Makrehchi, Masoud.

Subjects/Keywords: Bitcoin; Predictive model; Machine learning

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APA (6^th Edition):

Gillett, J. (2016). Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/884

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Gillett, Jonathan. “Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers.” 2016. Thesis, University of Ontario Institute of Technology. Accessed December 06, 2019. http://hdl.handle.net/10155/884.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Gillett, Jonathan. “Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers.” 2016. Web. 06 Dec 2019.

Vancouver:

Gillett J. Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers. [Internet] [Thesis]. University of Ontario Institute of Technology; 2016. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/10155/884.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Gillett J. Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers. [Thesis]. University of Ontario Institute of Technology; 2016. Available from: http://hdl.handle.net/10155/884

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

4. Kreuzen, C. Cooperative adaptive cruise control: using information from multiple predecessors in combination with MPC:.

Degree: 2012, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:dd0c766a-5f16-4799-8c84-39abbddbce9e

► Cooperative adaptive cruise control (CACC) makes the vehicle follow its predecessor at a close but safe distance, and uses information received from other vehicles to… (more)

▼ Cooperative adaptive cruise control (CACC) makes the vehicle follow its predecessor at a close but safe distance, and uses information received from other vehicles to accomplish this task. In literature and in practice, the control method mostly applied for CACC is proportional integral derivative (PID) control, possibly with some refinement for gear shifting or comfort. The control method called model predictive control (MPC) can also be used for CACC, and from literature it appears to be more promising than PID, because of its ability to anticipate future situations and to implement constraints directly into the control algorithm. MPC applies the first input of a control input sequence that optimises a performance index calculated from predicted system behaviour, based on a prediction model, subject to operational constraints, in a receding horizon approach. Furthermore, literature has shown that with PID the use of state information from the second predecessor or the platoon leader, in addition to the direct predecessor’s states, can improve the CACC performance. Therefore, in this thesis the approach of using such additional communicated information from either the second predecessor or the platoon leader is combined with the use of MPC as control method. The goal is to investigate whether any of these two configurations give an increase in performance compared with similar configurations with PID as control method, and compared with a more basic configuration that uses just the direct predecessor’s state information with either MPC or PID. Also, the possibly added value of using communicated predicted states, in addition to current states, with MPC is investigated. The CACC controllers are designed to control the throttle, the brakes, and the gears, subject to operational constraints on acceleration, velocity, and vehicle-to-vehicle distance. The PID-based CACC controller contains a proportional feedback of the errors in velocity, position, and acceleration, combined with an automatic transmission scheme, and the control input is restricted at time instants at which a constraint is (almost) violated. The MPC-based CACC controller at each time step minimises the expected errors in position and velocity and the corresponding input variation. The MPC prediction model is obtained by approximating a nonlinear vehicle model by a piecewise affine (PWA) model, and converting the MPC optimisation problem into a mixed integer linear programming (MILP) problem. In this project, tuning is done by applying simulated annealing for a scenario involving four CACC-controlled vehicles following a platoon leader. Then, the tuned controllers are implemented in a validation scenario comprising a larger platoon undergoing a longer simulation. The results from simulating this validation scenario show that the PID-based CACC controller has a low responsiveness, compared with MPC, and lets the first two vehicles crash. With MPC several peaks and oscillations in throttle/brake input and acceleration occur, and it is expected that with… Advisors/Committee Members: De Schutter, B..

Subjects/Keywords: system & control; model predictive control

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Kreuzen, C. (2012). Cooperative adaptive cruise control: using information from multiple predecessors in combination with MPC:. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:dd0c766a-5f16-4799-8c84-39abbddbce9e

Chicago Manual of Style (16^th Edition):

Kreuzen, C. “Cooperative adaptive cruise control: using information from multiple predecessors in combination with MPC:.” 2012. Masters Thesis, Delft University of Technology. Accessed December 06, 2019. http://resolver.tudelft.nl/uuid:dd0c766a-5f16-4799-8c84-39abbddbce9e.

MLA Handbook (7^th Edition):

Kreuzen, C. “Cooperative adaptive cruise control: using information from multiple predecessors in combination with MPC:.” 2012. Web. 06 Dec 2019.

Vancouver:

Kreuzen C. Cooperative adaptive cruise control: using information from multiple predecessors in combination with MPC:. [Internet] [Masters thesis]. Delft University of Technology; 2012. [cited 2019 Dec 06]. Available from: http://resolver.tudelft.nl/uuid:dd0c766a-5f16-4799-8c84-39abbddbce9e.

Council of Science Editors:

Kreuzen C. Cooperative adaptive cruise control: using information from multiple predecessors in combination with MPC:. [Masters Thesis]. Delft University of Technology; 2012. Available from: http://resolver.tudelft.nl/uuid:dd0c766a-5f16-4799-8c84-39abbddbce9e

University of Waterloo

5. Masoudi, Yasaman. Real-time Optimal Battery Thermal Management System Controller for Electric and Plug-in Hybrid Electric Vehicles.

Degree: 2017, University of Waterloo

URL: http://hdl.handle.net/10012/11269

► The objective of this thesis is to propose a real-time model predictive control (MPC) scheme for the battery thermal management system (BTMS) of given plug-in… (more)

Subjects/Keywords: Nonlinear Model Predictive Control

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APA (6^th Edition):

Masoudi, Y. (2017). Real-time Optimal Battery Thermal Management System Controller for Electric and Plug-in Hybrid Electric Vehicles. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/11269

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Masoudi, Yasaman. “Real-time Optimal Battery Thermal Management System Controller for Electric and Plug-in Hybrid Electric Vehicles.” 2017. Thesis, University of Waterloo. Accessed December 06, 2019. http://hdl.handle.net/10012/11269.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Masoudi, Yasaman. “Real-time Optimal Battery Thermal Management System Controller for Electric and Plug-in Hybrid Electric Vehicles.” 2017. Web. 06 Dec 2019.

Vancouver:

Masoudi Y. Real-time Optimal Battery Thermal Management System Controller for Electric and Plug-in Hybrid Electric Vehicles. [Internet] [Thesis]. University of Waterloo; 2017. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/10012/11269.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Masoudi Y. Real-time Optimal Battery Thermal Management System Controller for Electric and Plug-in Hybrid Electric Vehicles. [Thesis]. University of Waterloo; 2017. Available from: http://hdl.handle.net/10012/11269

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Waterloo

6. Santander, Omar. Economic Model Predictive Control of Chemical Processes.

Degree: 2015, University of Waterloo

URL: http://hdl.handle.net/10012/9982

► The objective of any chemical process is to transform raw materials into more valuable products subject to not only physical and environmental but also economic… (more)

▼ The objective of any chemical process is to transform raw materials into more valuable products subject to not only physical and environmental but also economic and safety constraints. To meet all these constraints in the presence of disturbances the processes must be controlled. Although nowadays there are many available control techniques available Model Predictive Control (MPC) is widely used in industry due to its many advantages such as optimal handling of interactions in multivariable systems and process constraints. Generally, the MPC strategy is implemented within a hierarchical structure, where it receives set points or targets from the Real Time Optimization (RTO) layer and then maintains the process at these targets by calculating optimal control moves. However, often the set point from the RTO may not be the best optimal operation or it may not be reachable thus motivating the integration of the RTO and MPC calculations into one single computation layer. This work focuses on this idea of integrating RTO and MPC into one single optimization problem thus resulting in an approach referred in literature as Economic Model Predictive Control (EMPC). The term “Economic” is used to reflect that the objective function used for optimization includes an economic objective generally used in RTO calculations. In this thesis, we propose an EMPC algorithm which calculates manipulated variables values to optimize an objective consisting of a combination of a steady state and a dynamic economic cost. A weight factor is used to balance the contributions of each of these two terms. Also, the cost is defined such as when the best economic steady state is reached the objective is only influenced by the dynamic economic cost. An additional feature of the proposed algorithm is that the asymptotic stability is satisfied online by enforcing four especial constraints within the optimization problem: 1-positive definiteness of the matrix P defining the Lyapunov function, 2- contraction of the Lyapunov function with respect to set point changes, 3- contraction of the matrix P with respect to time and 4- Lyapunov stability condition. The last constraint both ensures decreasing of the Lyapunov function and also accounts for the robustness of the algorithm with respect to model error (uncertainty). A particular novelty of this algorithm is that it constantly calculates a best set point with respect to which stability is ensured by the aforementioned constraints. In contrast to other algorithms reported in the literature, the proposed algorithm does not require terminal constraints or terms in the cost that penalize deviations from fixed set points that often lead to conservative closed loop performance. To account for unmeasured disturbances entering the process, changes in parameters are also explored and the algorithm is devised to compensate for these changes through parameter updating. Accordingly, the parameters are included as additional decision variables within the optimization problem without the need…

Subjects/Keywords: Economic Model Predictive Control

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APA (6^th Edition):

Santander, O. (2015). Economic Model Predictive Control of Chemical Processes. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/9982

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Santander, Omar. “Economic Model Predictive Control of Chemical Processes.” 2015. Thesis, University of Waterloo. Accessed December 06, 2019. http://hdl.handle.net/10012/9982.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Santander, Omar. “Economic Model Predictive Control of Chemical Processes.” 2015. Web. 06 Dec 2019.

Vancouver:

Santander O. Economic Model Predictive Control of Chemical Processes. [Internet] [Thesis]. University of Waterloo; 2015. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/10012/9982.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Santander O. Economic Model Predictive Control of Chemical Processes. [Thesis]. University of Waterloo; 2015. Available from: http://hdl.handle.net/10012/9982

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Université de Grenoble

7. Lamoudi, Mohamed Yacine. Commande prédictive distribuée pour la gestion de l'énergie dans le bâtiment Distributed model predictive control for energy management in building : Distributed Predictive Control for energy management in buildings.

Degree: Docteur es, Sciences et technologie industrielles, 2012, Université de Grenoble

URL: http://www.theses.fr/2012GRENT097

►

À l’heure actuelle, les stratégies de gestion de l’énergie pour les bâtiments sontprincipalement basées sur une concaténation de règles logiques. Bien que cette approcheoffre des… (more)

▼

À l’heure actuelle, les stratégies de gestion de l’énergie pour les bâtiments sontprincipalement basées sur une concaténation de règles logiques. Bien que cette approcheoffre des avantages certains, particulièrement lors de sa mise en oeuvre sur des automatesprogrammables, elle peine à traiter la diversité de situations complexes quipeuvent être rencontrées (prix de l’énergie variable, limitations de puissance, capacitéde stockage d’énergie, bâtiments de grandes dimension).Cette thèse porte sur le développement et l’évaluation d’une commande prédictivepour la gestion de l’énergie dans le bâtiment ainsi que l’étude de l’embarcabilité del’algorithme de contrôle sur une cible temps-réel (Roombox - Schneider-Electric).La commande prédictive est basée sur l’utilisation d’un modèle du bâtiment ainsique des prévisions météorologiques et d’occupation afin de déterminer la séquencede commande optimale à mettre en oeuvre sur un horizon de prédiction glissant.Seul le premier élément de cette séquence est en réalité appliqué au bâtiment. Cetteséquence de commande optimale est obtenue par la résolution en ligne d’un problèmed’optimisation. La capacité de la commande prédictive à gérer des systèmes multivariablescontraints ainsi que des objectifs économiques, la rend particulièrementadaptée à la problématique de la gestion de l’énergie dans le bâtiment.Cette thèse propose l’élaboration d’un schéma de commande distribué pour contrôlerles conditions climatiques dans chaque zone du bâtiment. L’objectif est de contrôlersimultanément: la température intérieure, le taux de CO2 ainsi que le niveaud’éclairement dans chaque zone en agissant sur les équipements présents (CVC, éclairage,volets roulants). Par ailleurs, le cas des bâtiments multi-sources (par exemple:réseau électrique + production locale solaire), dans lequel chaque source d’énergie estcaractérisée par son propre prix et une limitation de puissance, est pris en compte.Dans ce contexte, les décisions relatives à chaque zone ne peuvent plus être effectuéesde façon indépendante. Pour résoudre ce problème, un mécanisme de coordinationbasé sur une décomposition du problème d’optimisation centralisé est proposé. Cettethèse CIFRE 1 a été préparée au sein du laboratoire Gipsa-lab en partenariat avecSchneider-Electric dans le cadre du programme HOMES (www.homesprogramme.com).

Currently, energy management strategies for buildings are mostly based on a concatenationof logical rules. Despite the fact that such rule based strategy can be easilyimplemented, it suffers from some limitations particularly when dealing with complexsituations. This thesis is concerned with the development and assessment ofModel Predictive Control (MPC) algorithms for energy management in buildings. Inthis work, a study of implementability of the control algorithm on a real-time hardwaretarget is conducted beside yearly simulations showing a substantial energy savingpotential. The thesis explores also the ability of MPC to deal with the diversity ofcomplex situations that could be encountered (varying energy…

Advisors/Committee Members: Alamir, Mazen (thesis director).

Subjects/Keywords: Commande predictive; Commande predictive distribué; Énergie; Bâtiment; Predictive control; Distributed model predictive control; Energy; Building

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APA (6^th Edition):

Lamoudi, M. Y. (2012). Commande prédictive distribuée pour la gestion de l'énergie dans le bâtiment Distributed model predictive control for energy management in building : Distributed Predictive Control for energy management in buildings. (Doctoral Dissertation). Université de Grenoble. Retrieved from http://www.theses.fr/2012GRENT097

Chicago Manual of Style (16^th Edition):

Lamoudi, Mohamed Yacine. “Commande prédictive distribuée pour la gestion de l'énergie dans le bâtiment Distributed model predictive control for energy management in building : Distributed Predictive Control for energy management in buildings.” 2012. Doctoral Dissertation, Université de Grenoble. Accessed December 06, 2019. http://www.theses.fr/2012GRENT097.

MLA Handbook (7^th Edition):

Lamoudi, Mohamed Yacine. “Commande prédictive distribuée pour la gestion de l'énergie dans le bâtiment Distributed model predictive control for energy management in building : Distributed Predictive Control for energy management in buildings.” 2012. Web. 06 Dec 2019.

Vancouver:

Lamoudi MY. Commande prédictive distribuée pour la gestion de l'énergie dans le bâtiment Distributed model predictive control for energy management in building : Distributed Predictive Control for energy management in buildings. [Internet] [Doctoral dissertation]. Université de Grenoble; 2012. [cited 2019 Dec 06]. Available from: http://www.theses.fr/2012GRENT097.

Council of Science Editors:

Lamoudi MY. Commande prédictive distribuée pour la gestion de l'énergie dans le bâtiment Distributed model predictive control for energy management in building : Distributed Predictive Control for energy management in buildings. [Doctoral Dissertation]. Université de Grenoble; 2012. Available from: http://www.theses.fr/2012GRENT097

California State University – Sacramento

8. Bhatt, Pratik R. Audio coder using perceptual linear predictive coding.

Degree: MS, Electrical and Electronic Engineering, 2011, California State University – Sacramento

URL: http://hdl.handle.net/10211.9/1045

► Audio coder using perceptual linear predictive coding is a new technique for compressing and decompressing audio signal. This technique codes only the information of an… (more)

Subjects/Keywords: Audio coder; Perceptual model; Linear predictive coding

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APA (6^th Edition):

Bhatt, P. R. (2011). Audio coder using perceptual linear predictive coding. (Masters Thesis). California State University – Sacramento. Retrieved from http://hdl.handle.net/10211.9/1045

Chicago Manual of Style (16^th Edition):

Bhatt, Pratik R. “Audio coder using perceptual linear predictive coding.” 2011. Masters Thesis, California State University – Sacramento. Accessed December 06, 2019. http://hdl.handle.net/10211.9/1045.

MLA Handbook (7^th Edition):

Bhatt, Pratik R. “Audio coder using perceptual linear predictive coding.” 2011. Web. 06 Dec 2019.

Vancouver:

Bhatt PR. Audio coder using perceptual linear predictive coding. [Internet] [Masters thesis]. California State University – Sacramento; 2011. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/10211.9/1045.

Council of Science Editors:

Bhatt PR. Audio coder using perceptual linear predictive coding. [Masters Thesis]. California State University – Sacramento; 2011. Available from: http://hdl.handle.net/10211.9/1045

Oregon State University

9. Fernández, Daniel C. Model Predictive Control for Underwater Robots in Ocean Waves.

Degree: MS, Robotics, 2015, Oregon State University

URL: http://hdl.handle.net/1957/57267

► Underwater robots beneath ocean waves can benefit from feedforward control to reduce position error. This thesis proposes a method using Model Predictive Control (MPC) to… (more)

Subjects/Keywords: model predictive control; Remote submersibles – Automatic control

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APA (6^th Edition):

Fernández, D. C. (2015). Model Predictive Control for Underwater Robots in Ocean Waves. (Masters Thesis). Oregon State University. Retrieved from http://hdl.handle.net/1957/57267

Chicago Manual of Style (16^th Edition):

Fernández, Daniel C. “Model Predictive Control for Underwater Robots in Ocean Waves.” 2015. Masters Thesis, Oregon State University. Accessed December 06, 2019. http://hdl.handle.net/1957/57267.

MLA Handbook (7^th Edition):

Fernández, Daniel C. “Model Predictive Control for Underwater Robots in Ocean Waves.” 2015. Web. 06 Dec 2019.

Vancouver:

Fernández DC. Model Predictive Control for Underwater Robots in Ocean Waves. [Internet] [Masters thesis]. Oregon State University; 2015. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/1957/57267.

Council of Science Editors:

Fernández DC. Model Predictive Control for Underwater Robots in Ocean Waves. [Masters Thesis]. Oregon State University; 2015. Available from: http://hdl.handle.net/1957/57267

University of California – Berkeley

10. Danielson, Claus. Symmetric Constrained Optimal Control: Theory, Algorithms, and Applications.

Degree: Mechanical Engineering, 2014, University of California – Berkeley

URL: http://www.escholarship.org/uc/item/7dq9176d

► This dissertation develops the theory of symmetry for constrained linear systems. We use symmetry to design model predictive controllers for constrained linear systems with reduced… (more)

▼ This dissertation develops the theory of symmetry for constrained linear systems. We use symmetry to design model predictive controllers for constrained linear systems with reduced complexity.The dissertation is divided into three parts. In the first part we review the relevant results from model predictive control and group theory. In particular we present algorithms and data structures from computational group theory used to efficiently search groups.In the second part we develop the theory of symmetry for constrained linear systems and model predictive control problems. Symmetries of constrained linear systems are linear transformations that preserve the dynamics and constraints. A symmetry of a model predictive control problem is a symmetry of the underlying constrained system that also preserves the cost. We use a group theoretic formalism to derive properties of symmetric constrained linear systems and symmetric model predictive control problems. We prove conditions under which the model predictive controller is symmetric and present a procedure for efficiently computing the symmetries of constrained linear systems and model predictive control problems. Our method transforms the problem of finding generators for the symmetry group into a graph automorphism problem. These symmetries are used to design model predictive control algorithms with reduced complexity.We also present two novel explicit model predictive control designs. Both reduce memory requirements by discarding symmetrically redundant pieces of the control-law. The control-law in the eliminated pieces can be reconstructed online using symmetry. We show that storing the symmetries of the problem requires less memory than storing the controller pieces.In the third part of this dissertation we apply our symmetry theory to the battery balancing problem. We use symmetry to reduce the memory requirements for explicit model predictive controllers for seven battery-balancing hardware designs proposed in the literature. This application demonstrates that our symmetric controller designs can significantly reduce the memory requirements of explicit model predictive control. In particular for four out of seven of the designs in our numerical study, the number of pieces in the symmetric controller did not increase as the battery pack-size was increased.

Subjects/Keywords: Mechanical engineering; Control; Model Predictive Control; Symmetry

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APA (6^th Edition):

Danielson, C. (2014). Symmetric Constrained Optimal Control: Theory, Algorithms, and Applications. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/7dq9176d

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Danielson, Claus. “Symmetric Constrained Optimal Control: Theory, Algorithms, and Applications.” 2014. Thesis, University of California – Berkeley. Accessed December 06, 2019. http://www.escholarship.org/uc/item/7dq9176d.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Danielson, Claus. “Symmetric Constrained Optimal Control: Theory, Algorithms, and Applications.” 2014. Web. 06 Dec 2019.

Vancouver:

Danielson C. Symmetric Constrained Optimal Control: Theory, Algorithms, and Applications. [Internet] [Thesis]. University of California – Berkeley; 2014. [cited 2019 Dec 06]. Available from: http://www.escholarship.org/uc/item/7dq9176d.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Danielson C. Symmetric Constrained Optimal Control: Theory, Algorithms, and Applications. [Thesis]. University of California – Berkeley; 2014. Available from: http://www.escholarship.org/uc/item/7dq9176d

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Clemson University

11. Koli, Rohit Vishvanath. Model Predictive Control of Modern High-Degree-of-Freedom Turbocharged Spark Ignited Engines with External Cooled EGR.

Degree: PhD, Automotive Engineering, 2018, Clemson University

URL: https://tigerprints.clemson.edu/all_dissertations/2211

► The efficiency of modern downsized SI engines has been significantly improved using cooled Low-Pressure Exhaust Gas Recirculation, Turbocharging and Variable Valve Timing actuation. Control of… (more)

Subjects/Keywords: EGR; Internal Combustion Engine; Model Predictive Control

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APA (6^th Edition):

Koli, R. V. (2018). Model Predictive Control of Modern High-Degree-of-Freedom Turbocharged Spark Ignited Engines with External Cooled EGR. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/2211

Chicago Manual of Style (16^th Edition):

Koli, Rohit Vishvanath. “Model Predictive Control of Modern High-Degree-of-Freedom Turbocharged Spark Ignited Engines with External Cooled EGR.” 2018. Doctoral Dissertation, Clemson University. Accessed December 06, 2019. https://tigerprints.clemson.edu/all_dissertations/2211.

MLA Handbook (7^th Edition):

Koli, Rohit Vishvanath. “Model Predictive Control of Modern High-Degree-of-Freedom Turbocharged Spark Ignited Engines with External Cooled EGR.” 2018. Web. 06 Dec 2019.

Vancouver:

Koli RV. Model Predictive Control of Modern High-Degree-of-Freedom Turbocharged Spark Ignited Engines with External Cooled EGR. [Internet] [Doctoral dissertation]. Clemson University; 2018. [cited 2019 Dec 06]. Available from: https://tigerprints.clemson.edu/all_dissertations/2211.

Council of Science Editors:

Koli RV. Model Predictive Control of Modern High-Degree-of-Freedom Turbocharged Spark Ignited Engines with External Cooled EGR. [Doctoral Dissertation]. Clemson University; 2018. Available from: https://tigerprints.clemson.edu/all_dissertations/2211

McMaster University

12. Kheradmandi, Masoud. ADVANCES IN MODEL PREDICTIVE CONTROL.

Degree: PhD, 2018, McMaster University

URL: http://hdl.handle.net/11375/23432

► In this thesis I propose methods and strategies for the design of advanced model predictive control designs. The contributions are in the areas of data-driven… (more)

Subjects/Keywords: System identification; Subspace identification; Closed-loop identification; Model predictive control; Re-identification; Lyapunov-based model predictive control; Economic model predictive control; Nonlinear model predictive control

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APA (6^th Edition):

Kheradmandi, M. (2018). ADVANCES IN MODEL PREDICTIVE CONTROL. (Doctoral Dissertation). McMaster University. Retrieved from http://hdl.handle.net/11375/23432

Chicago Manual of Style (16^th Edition):

Kheradmandi, Masoud. “ADVANCES IN MODEL PREDICTIVE CONTROL.” 2018. Doctoral Dissertation, McMaster University. Accessed December 06, 2019. http://hdl.handle.net/11375/23432.

MLA Handbook (7^th Edition):

Kheradmandi, Masoud. “ADVANCES IN MODEL PREDICTIVE CONTROL.” 2018. Web. 06 Dec 2019.

Vancouver:

Kheradmandi M. ADVANCES IN MODEL PREDICTIVE CONTROL. [Internet] [Doctoral dissertation]. McMaster University; 2018. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/11375/23432.

Council of Science Editors:

Kheradmandi M. ADVANCES IN MODEL PREDICTIVE CONTROL. [Doctoral Dissertation]. McMaster University; 2018. Available from: http://hdl.handle.net/11375/23432

Texas A&M University

13. Vedam, Narayani. Terrain-Adaptive Cruise Control: A Human-Like Approach.

Degree: 2015, Texas A&M University

URL: http://hdl.handle.net/1969.1/156224

► With rapid advancements in the ?eld of autonomous vehicles, intelligent control systems and automated highway systems, the need for GPS based vehicle data has grown… (more)

Subjects/Keywords: Terrain-Adaptive; Cruise Control; Model Predictive Control

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APA (6^th Edition):

Vedam, N. (2015). Terrain-Adaptive Cruise Control: A Human-Like Approach. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/156224

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Vedam, Narayani. “Terrain-Adaptive Cruise Control: A Human-Like Approach.” 2015. Thesis, Texas A&M University. Accessed December 06, 2019. http://hdl.handle.net/1969.1/156224.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Vedam, Narayani. “Terrain-Adaptive Cruise Control: A Human-Like Approach.” 2015. Web. 06 Dec 2019.

Vancouver:

Vedam N. Terrain-Adaptive Cruise Control: A Human-Like Approach. [Internet] [Thesis]. Texas A&M University; 2015. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/1969.1/156224.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Vedam N. Terrain-Adaptive Cruise Control: A Human-Like Approach. [Thesis]. Texas A&M University; 2015. Available from: http://hdl.handle.net/1969.1/156224

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Cornell University

14. Radecki, Peter. Applied Probabilistic Inference: Model Estimation For Hvac Predictive Controls And All-Weather Perception For Autonomous Vehicles .

Degree: 2016, Cornell University

URL: http://hdl.handle.net/1813/44364

► Probabilistic inference and reasoning is applied to two major application areas: HVAC controls in buildings and autonomous vehicle perception. Although the physical domains differ vastly,… (more)

▼ Probabilistic inference and reasoning is applied to two major application areas: HVAC controls in buildings and autonomous vehicle perception. Although the physical domains differ vastly, across both applications the presented novel contributions share real-time inference of stochastic systems for improved control capability and performance. Besides performing simple state estimation, Kalman Filters in both applications are extended for model inference-estimating thermal model parameters and disturbances in buildings and dynamic object classification for perception in autonomous vehicles. Part one of this study proposes a general, scalable method to learn controloriented thermal models of buildings that could enable wide-scale deployment of cost-effective predictive controls. An Unscented Kalman Filter augmented for parameter and disturbance estimation is shown to accurately learn and predict a building's thermal response. By leveraging building topology and measurement data, the filter quickly learns parameters of a thermal network during periods of known or constrained loads and then characterizes unknown loads in order to provide accurate 24+ hour energy predictions. Performance was validated with EnergyPlus simulation data across a year-long study of a passive building. The method is extended to multi-zone actively controlled buildings by using the controller to excite unknown portions of the building's dynamics. A simulation study demonstrates self-excitation improves model estimation. Formalization of parameterization, disturbance estimation, and self-excitation routines is shown with an observability analysis. Comparing against a baseline thermostat controller, a Model Predictive Control (MPC) framework, which anticipates weather uncertainty and time-varying temperature set-points, is shown to improve energy savings and occupant comfort. Part two of this study presents a novel probabilistic perception algorithm as a real-time joint solution to data association, object tracking, and object classification for an autonomous ground vehicle (AGV) in all-weather conditions. The presented algorithm extends a Rao-Blackwellized Particle Filter originally built for Cornell's AGV for the DARPA Urban Challenge (DUC) to include multiple model tracking for classification. Additionally a state-of-the-art vision detection algorithm that includes heading information for AGV applications was implemented. Cornell's AGV from the DUC was upgraded and used to experimentally examine if and how state-of-the-art vision algorithms can complement or replace lidar and radar sensors. Sensor and algorithm performance in adverse weather and lighting conditions is tested. Experimental evaluation demonstrates that sensor diversity with a joint probabilistic perception algorithm provides robust all-weather data association, tracking, and classification. Advisors/Committee Members: Snavely,Keith Noah (committeeMember), Hencey,Brandon M. (committeeMember).

Subjects/Keywords: Kalman Filter; Probabilistic Inference; Model Predictive Control

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APA (6^th Edition):

Radecki, P. (2016). Applied Probabilistic Inference: Model Estimation For Hvac Predictive Controls And All-Weather Perception For Autonomous Vehicles . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/44364

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Radecki, Peter. “Applied Probabilistic Inference: Model Estimation For Hvac Predictive Controls And All-Weather Perception For Autonomous Vehicles .” 2016. Thesis, Cornell University. Accessed December 06, 2019. http://hdl.handle.net/1813/44364.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Radecki, Peter. “Applied Probabilistic Inference: Model Estimation For Hvac Predictive Controls And All-Weather Perception For Autonomous Vehicles .” 2016. Web. 06 Dec 2019.

Vancouver:

Radecki P. Applied Probabilistic Inference: Model Estimation For Hvac Predictive Controls And All-Weather Perception For Autonomous Vehicles . [Internet] [Thesis]. Cornell University; 2016. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/1813/44364.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Radecki P. Applied Probabilistic Inference: Model Estimation For Hvac Predictive Controls And All-Weather Perception For Autonomous Vehicles . [Thesis]. Cornell University; 2016. Available from: http://hdl.handle.net/1813/44364

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

California State University – Sacramento

15. Guo, Zhicheng. Model predictive control for two-stage photovoltaic system.

Degree: MS, Electrical and Electronic Engineering, 2017, California State University – Sacramento

URL: http://hdl.handle.net/10211.3/198833

► Energy is a vital component for human economic development and growth. The extensive use of fossil fuels has damaged our living environment. Consequently, the world… (more)

Subjects/Keywords: Model predictive control; Photovoltaic; Two-stage system

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APA (6^th Edition):

Guo, Z. (2017). Model predictive control for two-stage photovoltaic system. (Masters Thesis). California State University – Sacramento. Retrieved from http://hdl.handle.net/10211.3/198833

Chicago Manual of Style (16^th Edition):

Guo, Zhicheng. “Model predictive control for two-stage photovoltaic system.” 2017. Masters Thesis, California State University – Sacramento. Accessed December 06, 2019. http://hdl.handle.net/10211.3/198833.

MLA Handbook (7^th Edition):

Guo, Zhicheng. “Model predictive control for two-stage photovoltaic system.” 2017. Web. 06 Dec 2019.

Vancouver:

Guo Z. Model predictive control for two-stage photovoltaic system. [Internet] [Masters thesis]. California State University – Sacramento; 2017. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/10211.3/198833.

Council of Science Editors:

Guo Z. Model predictive control for two-stage photovoltaic system. [Masters Thesis]. California State University – Sacramento; 2017. Available from: http://hdl.handle.net/10211.3/198833

Delft University of Technology

16. Jain, R.P.K. Transportation of Cable Suspended Load using Unmanned Aerial Vehicles: A Real-time Model Predictive Control approach:.

Degree: 2015, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:4c6b4a94-4f15-4e67-8c30-eb8156aab406

► Unmanned Aerial Vehicles (UAV) have received an increasing amount of attention recently with many applications being actively investigated across the globe, and several related open… (more)

▼ Unmanned Aerial Vehicles (UAV) have received an increasing amount of attention recently with many applications being actively investigated across the globe, and several related open research questions being actively pursued. Possible applications include search and rescue, disaster relief, environmental monitoring and surveillance, transportation, and construction. Transportation of cable suspended payloads using Unmanned Aerial Vehicles is one such application which is the topic of this research. Autonomous transportation of objects using UAV can contribute to the safe and reliable supply of food and medicine in remote or disaster-affected areas and even in commercial delivery of goods. The state-of-the-art approaches towards the slung load transportation either develop non-linear feedback control laws to stabilize the system to a predefined trajectory or employ open loop off-line trajectory planning schemes to generate optimal control inputs to the system. Most of these techniques often rely on availability of an accurate model of the system backed up with simulation results. Very few results exist which target experimental validation of the proposed method. Based on the findings of the previously conducted literature survey, it appears that the application of closed loop on-line trajectory generation and control schemes to transport a slung payload in swing free manner remains unanswered. The work in this thesis sets off to answer the research questions in this direction and address the issues that come along with experimental validation. Model Predictive Control (MPC) is a promising framework, which provides the means to tackle both the trajectory generation problem and the feedback control problem in an unified manner. As a result, it forms the most important component of this thesis. Specific research problem that is addressed in this thesis is to transport a cable suspended load using quadrotor from one point to another, while minimizing the swing through the use of Linear Time Invariant MPC techniques. A non-linear dynamic model for the quadrotor-slung load system is obtained and the structure within the system dynamics is exploited to decide the control strategy. Two different MPC formulations viz. MPC with integral action and MPC with delta-u formulation are simulated and compared to Linear Quadratic control with integral action which acts as a benchmark controller. Backed with simulation results, it is shown through experimental validation that it is possible to control the swing of cable suspended load using linear control techniques. MPC being an computationally expensive task, state-of-the-art fast optimization solvers such as FORCES PRO is used to achieve on-line implementation of MPC for the quadrotor-slung load system. To this end, a new software framework for implementation of MPC is developed which establishes a wireless link with the quadrotor resulting in a real-time networked control loop. Advisors/Committee Members: Keviczky, T..

Subjects/Keywords: quadrotor; model predictive control; paparazzi; MAV; robotics

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APA (6^th Edition):

Jain, R. P. K. (2015). Transportation of Cable Suspended Load using Unmanned Aerial Vehicles: A Real-time Model Predictive Control approach:. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:4c6b4a94-4f15-4e67-8c30-eb8156aab406

Chicago Manual of Style (16^th Edition):

Jain, R P K. “Transportation of Cable Suspended Load using Unmanned Aerial Vehicles: A Real-time Model Predictive Control approach:.” 2015. Masters Thesis, Delft University of Technology. Accessed December 06, 2019. http://resolver.tudelft.nl/uuid:4c6b4a94-4f15-4e67-8c30-eb8156aab406.

MLA Handbook (7^th Edition):

Jain, R P K. “Transportation of Cable Suspended Load using Unmanned Aerial Vehicles: A Real-time Model Predictive Control approach:.” 2015. Web. 06 Dec 2019.

Vancouver:

Jain RPK. Transportation of Cable Suspended Load using Unmanned Aerial Vehicles: A Real-time Model Predictive Control approach:. [Internet] [Masters thesis]. Delft University of Technology; 2015. [cited 2019 Dec 06]. Available from: http://resolver.tudelft.nl/uuid:4c6b4a94-4f15-4e67-8c30-eb8156aab406.

Council of Science Editors:

Jain RPK. Transportation of Cable Suspended Load using Unmanned Aerial Vehicles: A Real-time Model Predictive Control approach:. [Masters Thesis]. Delft University of Technology; 2015. Available from: http://resolver.tudelft.nl/uuid:4c6b4a94-4f15-4e67-8c30-eb8156aab406

Delft University of Technology

17. Siddaramappa, A. Rigid Formation Control using Hovercrafts: A Spatial Model Predictive Control Approach:.

Degree: 2015, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:3b025de3-52ff-45d3-ab80-05cf2e450ec9

► The steady increase in volume of goods to be transported over land and water has necessitated the development of efficient and alternative methods of transportation.… (more)

▼ The steady increase in volume of goods to be transported over land and water has necessitated the development of efficient and alternative methods of transportation. In current practices considerable amount of transportation delay is caused due to switching between different modes of transportation resulting in economic losses. Another difficulty in the transportation sector arises when handling extremely large objects, such as wind turbines and cargo containers. In order to overcome these difficulties, an alternative method of transportation has been proposed recently. The proposed alternative method consists of the development of a formation control framework using hovercrafts. Formation control is a widely researched topic due its potential benefits in reducing the system cost, structure flexibility and improving the efficiency of the overall system. State-of-the-art methods for formation control are focused towards developing a controller to track a predefined trajectory, and the trajectory generation is an additional problem which is addressed off-line. A path tracking formation control framework is an area which has received less attention in the literature and can have possible improvements. Hence, this thesis work answers the research question of generating a feasible path for a set of initial and final conditions, and tracking the generated path. Model Predictive Controller (MPC) is a promising framework, because of its constraint handling capabilities. Hence, it accounts for the major component of this thesis. A new framework for formation control is proposed which uses spatial-domain parametrization instead of the conventional time-domain parametrization. MPC being a computationally expensive task, the proposed framework reduces the number of decision variables and constraint evaluations which can help to achieve the desired Real Time performance. The specific research question addressed in this thesis work is to develop a path tracking formation control framework while minimising the absolute and relative position error for each vehicle in the formation. A nonlinear dynamic model for the hovercraft is obtained using first principles and its structure is used to design an optimization based controller. An Optimal Control Problem (OCP) is formulated which is solved using direct collocation method. In this method a continuous problem is discretized into a number of collocation points, and the resulting problem is solved using state-of-the-art Nonlinear Program solvers such as, SNOPT and NPSOL. The performance of the proposed framework is illustrated using numerical simulations. Advisors/Committee Members: Keviczky, T..

Subjects/Keywords: Model Predictive Controller; Formation Control; Hovercraft

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Siddaramappa, A. (2015). Rigid Formation Control using Hovercrafts: A Spatial Model Predictive Control Approach:. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:3b025de3-52ff-45d3-ab80-05cf2e450ec9

Chicago Manual of Style (16^th Edition):

Siddaramappa, A. “Rigid Formation Control using Hovercrafts: A Spatial Model Predictive Control Approach:.” 2015. Masters Thesis, Delft University of Technology. Accessed December 06, 2019. http://resolver.tudelft.nl/uuid:3b025de3-52ff-45d3-ab80-05cf2e450ec9.

MLA Handbook (7^th Edition):

Siddaramappa, A. “Rigid Formation Control using Hovercrafts: A Spatial Model Predictive Control Approach:.” 2015. Web. 06 Dec 2019.

Vancouver:

Siddaramappa A. Rigid Formation Control using Hovercrafts: A Spatial Model Predictive Control Approach:. [Internet] [Masters thesis]. Delft University of Technology; 2015. [cited 2019 Dec 06]. Available from: http://resolver.tudelft.nl/uuid:3b025de3-52ff-45d3-ab80-05cf2e450ec9.

Council of Science Editors:

Siddaramappa A. Rigid Formation Control using Hovercrafts: A Spatial Model Predictive Control Approach:. [Masters Thesis]. Delft University of Technology; 2015. Available from: http://resolver.tudelft.nl/uuid:3b025de3-52ff-45d3-ab80-05cf2e450ec9

Delft University of Technology

18. Stive, P.M. Performance assessment of tree-based model predictive control:.

Degree: 2011, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:79a718a3-cd99-4f44-8391-3de5e93c3dcd

► This research focuses on polder-belt canal systems. More is demanded from these systems every day. Man induced changes, like increasing population density and increasing land… (more)

▼ This research focuses on polder-belt canal systems. More is demanded from these systems every day. Man induced changes, like increasing population density and increasing land value on one hand and climate change in the form of longer dry spells and more extreme precipitation events on the other hand are the main sources. The operation of the structures in these systems plays a critical role in successfully dealing with these challenges. To get the most out of the current system and its structures, operation by humans alone is not enough, they need to be aided by computers. A promising technique is Model Predictive Control (MPC). A control algorithm that uses a model of the system and forecasts of the future disturbances to determine the control actions for the structures, whilst adhering to the constraints of the system. Forecasts are uncertain and are therefore provided in the form of ensemble forecasts that consist of multiple scenarios. MPC uses only one scenario and is thus vulnerable to these uncertainties. Treebased Model Predictive Control (TBMPC) considers the complete ensemble to determine control actions. TBMPC has, however, only been tested in theory. Only open loop simulations have been carried out, no continuous closed loop simulations have been done. TBMPC uses the complete ensemble, but to save calculation time reduces it to a tree-shaped representative ensemble with fewer nodes. This means aggregating nodes and scenarios on various points in the ensemble. There are multiple rules that determine which nodes and scenarios are aggregated, however, their optimal setting is not known. Also if TBMPC has more added benefit over MPC on certain system configurations (e.g. configurations with higher discharge or storage capacity) is not known either. A model is developed to simulate the performance of MPC and TBMPC. It can deal with different precipitation series, forecasts, system configurations and control algorithm parameters. All simulations have a duration of one year and a one hour time step. The rules that determine which nodes and scenarios are aggregated are investigated first. Transforming the inflow forecast scenarios to cumulative inflow scenarios before determining which nodes and scenarios to aggregate yields better results. The threshold value is also important as it determines whether or not two scenarios are close enough to each other to be aggregated. Nothing was known about the right value for this parameter. One of the objectives was to be able to fine tune this value to the system con guration. Setting this value as a percentage of the maximum pump capacity of the system works well across di erent system configurations. The optimal value is 100% of the maximum pump capacity. The scenario reduction algorithm (i.e. the algorithm that creates the tree from the original ensemble) has two parts. First it reduces the number of scenarios in the ensemble to a predefined number and secondly it creates a tree out of the reduced ensemble. No information was available about the right amount of… Advisors/Committee Members: Van de Giesen, N.C..

Subjects/Keywords: tree-based model predictive control; performance assessment

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APA (6^th Edition):

Stive, P. M. (2011). Performance assessment of tree-based model predictive control:. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:79a718a3-cd99-4f44-8391-3de5e93c3dcd

Chicago Manual of Style (16^th Edition):

Stive, P M. “Performance assessment of tree-based model predictive control:.” 2011. Masters Thesis, Delft University of Technology. Accessed December 06, 2019. http://resolver.tudelft.nl/uuid:79a718a3-cd99-4f44-8391-3de5e93c3dcd.

MLA Handbook (7^th Edition):

Stive, P M. “Performance assessment of tree-based model predictive control:.” 2011. Web. 06 Dec 2019.

Vancouver:

Stive PM. Performance assessment of tree-based model predictive control:. [Internet] [Masters thesis]. Delft University of Technology; 2011. [cited 2019 Dec 06]. Available from: http://resolver.tudelft.nl/uuid:79a718a3-cd99-4f44-8391-3de5e93c3dcd.

Council of Science Editors:

Stive PM. Performance assessment of tree-based model predictive control:. [Masters Thesis]. Delft University of Technology; 2011. Available from: http://resolver.tudelft.nl/uuid:79a718a3-cd99-4f44-8391-3de5e93c3dcd

University of Waikato

19. Forsythe, Claire Elizabeth. Predictive Risk Modelling for Hospital Readmissions .

Degree: 2014, University of Waikato

URL: http://hdl.handle.net/10289/8699

► This thesis is concerned with developing a predictive risk model to identify patients that are at high risk of readmission to hospital. Such a model… (more)

▼ This thesis is concerned with developing a predictive risk model to identify patients that are at high risk of readmission to hospital. Such a model should have a desirable level of predictive accuracy but also, should be financially beneficial to the DHB. Logistic regression and Naive Bayes probabilistic classification methods were both considered to build the predictive model. Performance measures such as the positive predictive value (PPV) and cost savings analysis were used to find the optimal days between initial admission and readmission and the optimal threshold for prediction of high risk patients. This study is concerned with Waikato District Health Board (DHB) domiciled patients discharged between 1 July 2009 and 31 October 2013. The dataset includes information about the patients initial admission and the response variable is whether a readmission occurred or not. Using logistic regression, this study found the model that fits the data best includes 21 variables that contain information about the patients initial admission. The two classification methods used produce a risk probability between 0 and 1 for each patient in the study. The logistic regression model performance was better than Naive Bayes as shown by the PPV (the proportion of patients correctly identified as at risk over the total at risk). The 56 day readmission data PPV at a risk threshold of 0.5 for the logistic regression was 48.4% and 30.8% for Naive Bayes. Analysis of the PPV identifies the risk threshold level of 0.5 and readmission period of 56 days as optimal predictive criteria in this study. Cost savings analysis also supports the 56 day model with an intervention cost of $500. The 0.5 cut off point in the 56 day model identifies a reasonable number of patients at risk for intervention, approximately 3,000, which equates to about 2 patients at risk per day over the period of this analysis. This analysis found the optimal model for predicting patients at risk of readmission is a logistic regression model using 56 day readmission data and a risk threshold of 0.5. A key recommendation of this study is that the DHB needs to introduce a method that correctly flags patient admissions. The model should be used on a trial basis at the DHB to see how accurate it performs. Advisors/Committee Members: Joshi, Chaitanya (advisor).

Subjects/Keywords: Logistic regression; Readmissions; Predictive model; Hospital

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Forsythe, C. E. (2014). Predictive Risk Modelling for Hospital Readmissions . (Masters Thesis). University of Waikato. Retrieved from http://hdl.handle.net/10289/8699

Chicago Manual of Style (16^th Edition):

Forsythe, Claire Elizabeth. “Predictive Risk Modelling for Hospital Readmissions .” 2014. Masters Thesis, University of Waikato. Accessed December 06, 2019. http://hdl.handle.net/10289/8699.

MLA Handbook (7^th Edition):

Forsythe, Claire Elizabeth. “Predictive Risk Modelling for Hospital Readmissions .” 2014. Web. 06 Dec 2019.

Vancouver:

Forsythe CE. Predictive Risk Modelling for Hospital Readmissions . [Internet] [Masters thesis]. University of Waikato; 2014. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/10289/8699.

Council of Science Editors:

Forsythe CE. Predictive Risk Modelling for Hospital Readmissions . [Masters Thesis]. University of Waikato; 2014. Available from: http://hdl.handle.net/10289/8699

University of Melbourne

20. LAM, DENISE. A model predictive approach to optimal path-following and contouring control.

Degree: 2012, University of Melbourne

URL: http://hdl.handle.net/11343/37555

► In the multi-billion dollar motion control industry, systems are often required to traverse along a geometric path, where the speed at which the path is… (more)

▼ In the multi-billion dollar motion control industry, systems are often required to traverse along a geometric path, where the speed at which the path is traversed is not pre-determined. Such path-following tasks involve competing control objectives of maximising accuracy while minimising traversal time.Existing trajectory planning routines optimise the path speed with respect to some of these objectives. However, trajectory planning is conducted in an open loop fashion, relying on trajectory tracking controllers to achieve the desired motion. Meanwhile, closed-loop path-following control schemes do not explicitly consider the control objectives. This thesis investigates the development of closed-loop path-following control schemes based on minimisation of a cost function within a receding horizon structure. The cost function is selected to reflect the desired objectives such as minimising traversal time, and is minimised subject to the system constraints. The receding horizon formulation allows for feedback to be taken into account at each sample, in contrast to open loop trajectory planning. A receding horizon path-following control scheme is first developed with the intention of achieving time-optimal path-following. The controller is designed to advance along the path as far as possible within a finite horizon while staying exactly on the path and honouring the constraints. The conditions under which the receding horizon approach replicates the time-optimal path-following solution are identified for second order differentially flat systems. In particular, it is shown that minimum-time path-following is achieved when the horizon is sufficiently long. Subsequently, a contouring control scheme for biaxial systems based on a similar framework is developed where the exact path-following constraint is relaxed in favour of penalising contouring error in the finite horizon cost function, which reflects the trade-off between competing control objectives of contouring accuracy, productivity and minimisation of control deviations. The penalty weights may be tuned to favour some objectives over others. A computationally efficient algorithm is proposed, allowing the scheme to be implemented in real time on an X-Y table. Experimental results demonstrate how the behaviour of the controller can be adjusted in a systematic manner by tuning the penalty weights. Results also show that the proposed scheme achieves superior contouring performance compared with tracking controllers implemented with constant path speed. The proposed contouring control approach is then extended to more complicated multi-axis systems involving position and orientation control. A multi-rate control architecture is proposed to facilitate the implementation of the contouring control scheme on industrial hardware. Simulations are conducted with an industrial profile cutting…

Subjects/Keywords: path-following; contouring; model predictive control

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APA (6^th Edition):

LAM, D. (2012). A model predictive approach to optimal path-following and contouring control. (Doctoral Dissertation). University of Melbourne. Retrieved from http://hdl.handle.net/11343/37555

Chicago Manual of Style (16^th Edition):

LAM, DENISE. “A model predictive approach to optimal path-following and contouring control.” 2012. Doctoral Dissertation, University of Melbourne. Accessed December 06, 2019. http://hdl.handle.net/11343/37555.

MLA Handbook (7^th Edition):

LAM, DENISE. “A model predictive approach to optimal path-following and contouring control.” 2012. Web. 06 Dec 2019.

Vancouver:

LAM D. A model predictive approach to optimal path-following and contouring control. [Internet] [Doctoral dissertation]. University of Melbourne; 2012. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/11343/37555.

Council of Science Editors:

LAM D. A model predictive approach to optimal path-following and contouring control. [Doctoral Dissertation]. University of Melbourne; 2012. Available from: http://hdl.handle.net/11343/37555

University of Waterloo

21. Diaz Mendoza, Juan Rosendo. Robust Empirical Model-Based Algorithms for Nonlinear Processes.

Degree: 2010, University of Waterloo

URL: http://hdl.handle.net/10012/5314

► This research work proposes two robust empirical model-based predictive control algorithms for nonlinear processes. Chemical process are generally highly nonlinear thus predictive control algorithms that… (more)

▼ This research work proposes two robust empirical model-based predictive control algorithms for nonlinear processes. Chemical process are generally highly nonlinear thus predictive control algorithms that explicitly account for the nonlinearity of the process are expected to provide better closed-loop performance as compared to algorithms based on linear models. Two types of models can be considered for control: first-principles and empirical. Empirical models were chosen for the proposed algorithms for the following reasons: (i) they are less complex for on-line optimization, (ii) they are easy to identify from input-output data and (iii) their structure is suitable for the formulation of robustness tests. One of the key problems of every model that is used for prediction within a control strategy is that some model parameters cannot be known accurately due to measurement noise and/or error in the structure of the assumed model. In the robust control approach it is assumed that processes can be represented by models with parameters' values that are assumed to lie between a lower and upper bound or equivalently, that these parameters can be represented by a nominal value plus uncertainty. When this uncertainty in control parameters is not considered by the controller the control actions might be insufficient to effectively control the process and in some extreme cases the closed-loop may become unstable. Accordingly, the two robust control algorithms proposed in the current work explicitly account for the effect of uncertainty on stability and closed-loop performance. The first proposed controller is a robust gain-scheduling model predictive controller (MPC). In this case the process is represented within each operating region by a state-affine model obtained from input-output data. The state-affine model matrices are used to obtain a state-space based MPC for every operating region. By combining the state-affine, disturbance and controller equations a closed-loop representation was obtained. Then, the resulting mathematical representation was tested for robustness with linear matrix inequalities (LMI's) based on a test where the vertices of the parameter box were obtained by an iterative procedure. The result of the LMI's test gives a measure of performance referred to as γ that relates the effect of the disturbances on the process outputs. Finally, for the gain-scheduling part of the algorithm a set of rules was proposed to switch between the available controllers according to the current process conditions. Since every combination of the controller tuning parameters results in a different value of γ, an optimization problem was proposed to minimize γ with respect to the tuning parameters. Accordingly, for the proposed controller it was ensured that the effect of the disturbances on the output variables was kept to its minimum. A bioreactor case study was presented to show the benefits of the proposed algorithm. For comparison purposes a non-robust linear MPC was also designed. The results show that the…

Subjects/Keywords: Robust Control; Nonlinear Model Predictive Control

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APA (6^th Edition):

Diaz Mendoza, J. R. (2010). Robust Empirical Model-Based Algorithms for Nonlinear Processes. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/5314

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Diaz Mendoza, Juan Rosendo. “Robust Empirical Model-Based Algorithms for Nonlinear Processes.” 2010. Thesis, University of Waterloo. Accessed December 06, 2019. http://hdl.handle.net/10012/5314.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Diaz Mendoza, Juan Rosendo. “Robust Empirical Model-Based Algorithms for Nonlinear Processes.” 2010. Web. 06 Dec 2019.

Vancouver:

Diaz Mendoza JR. Robust Empirical Model-Based Algorithms for Nonlinear Processes. [Internet] [Thesis]. University of Waterloo; 2010. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/10012/5314.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Diaz Mendoza JR. Robust Empirical Model-Based Algorithms for Nonlinear Processes. [Thesis]. University of Waterloo; 2010. Available from: http://hdl.handle.net/10012/5314

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of New South Wales

22. Rana, Md. Sohel. High Performance Control of an Atomic Force Microscope for Faster Image Scanning.

Degree: Engineering & Information Technology, 2014, University of New South Wales

URL: http://handle.unsw.edu.au/1959.4/54007 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12715/SOURCE02?view=true

► The performance of the atomic force microscope (AFM), a nanoscale imaging tool, is significantly influenced by the dynamics of the piezoelectric tube scanner (PTS). The… (more)

▼ The performance of the atomic force microscope (AFM), a nanoscale imaging tool, is significantly influenced by the dynamics of the piezoelectric tube scanner (PTS). The limitations of the PTS are its nonlinear behavior in the form of hysteresis and creep effects, low mechanical resonance frequency, and cross-coupling between its two axes of motion. The key focus of this dissertation is to mitigate the limitations of the PTS using controllers to increase the scanning speed. Broadly speaking, this thesis reports four significant contributions for improved scanning using AFMs with piezo tube scanners.The first and unique contribution of this thesis is the design and experimental implementation of a model predictive control (MPC) scheme to achieve accurate tracking for improved image quality at high scanning speeds. Close tracking of the reference signal ensures compensation of the creep and hysteresis effects in the PTS. The MPC control scheme is commonly used when tracking a reference trajectory is the primary goal. This capability of MPC controllers has motivated our research to indirectly compensate the creep and hysteresis effects of the PTS to improve the imaging performance of AFMs. The design of this controller is based on an identified single-input single-output (SISO) model of the PTS, and the AFM's improved imaging quality and scanning speed is illustrated for the design using the proposed control scheme. To evaluate the overall performance improvement achieved by the proposed scheme, an experimental comparison of scanned images from the proposed controller and the existing AFM proportional-integral (PI) controller is undertaken, the results of which verify the efficacy of the proposed design.Tube resonance is one of the major limitations for fast image scanning using AFMs. To overcome this, a damping compensator or notch filter introduced with the proposed MPC controller achieves a high closed-loop bandwidth and significant damping, and enables a reference triangular signal to be tracked. This is the second contribution of this dissertation. By using the proposed controller, the vibration effects in scanned images at high scanning speeds are compensated. Comparisons of the performance of the MPC controller and the modified MPC scheme with a damping compensator are presented.Another reason for the poor performance of the PTS for nanopositioning is that any movement in its x- or y-axis direction produces an undesirable motion in the z-direction called the cross-coupling effect. A multi-input multi-output (MIMO) MPC controller is proposed to compensate for the cross-coupling effect and this is the third contribution of this research. The design is based on an identified MIMO model of the PTS that includes the cross-coupling dynamics. Using the proposed controller a significant reduction in the cross-coupling is achieved and the imaging speed is enhanced up to 125 Hz.Also, a barrier in achieving high scanning speeds is the use of the zig-zag raster pattern scanning technique. In this thesis, a high-speed… Advisors/Committee Members: Petersen, Ian, Engineering & Information Technology, UNSW Canberra, UNSW, Pota, Hemanshu, Engineering & Information Technology, UNSW Canberra, UNSW.

Subjects/Keywords: Nanopositioning; Model Predictive Control; Atomic Force Micorscope

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APA (6^th Edition):

Rana, M. S. (2014). High Performance Control of an Atomic Force Microscope for Faster Image Scanning. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/54007 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12715/SOURCE02?view=true

Chicago Manual of Style (16^th Edition):

Rana, Md Sohel. “High Performance Control of an Atomic Force Microscope for Faster Image Scanning.” 2014. Doctoral Dissertation, University of New South Wales. Accessed December 06, 2019. http://handle.unsw.edu.au/1959.4/54007 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12715/SOURCE02?view=true.

MLA Handbook (7^th Edition):

Rana, Md Sohel. “High Performance Control of an Atomic Force Microscope for Faster Image Scanning.” 2014. Web. 06 Dec 2019.

Vancouver:

Rana MS. High Performance Control of an Atomic Force Microscope for Faster Image Scanning. [Internet] [Doctoral dissertation]. University of New South Wales; 2014. [cited 2019 Dec 06]. Available from: http://handle.unsw.edu.au/1959.4/54007 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12715/SOURCE02?view=true.

Council of Science Editors:

Rana MS. High Performance Control of an Atomic Force Microscope for Faster Image Scanning. [Doctoral Dissertation]. University of New South Wales; 2014. Available from: http://handle.unsw.edu.au/1959.4/54007 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12715/SOURCE02?view=true

University of Waterloo

23. Maitland, Anson. Nonlinear Model Predictive Control Reduction Strategies for Real-time Optimal Control.

Degree: 2019, University of Waterloo

URL: http://hdl.handle.net/10012/14524

► This thesis presents a variety of strategies to accelerate the turnaround times (TATs) of nonlinear and hybrid model predictive controllers (MPCs). These strategies are unified… (more)

▼ This thesis presents a variety of strategies to accelerate the turnaround times (TATs) of nonlinear and hybrid model predictive controllers (MPCs). These strategies are unified by the themes of symbolic computing, nonlinear model reduction and automotive control. The first contribution of this thesis is a new MPC problem formulation, called symbolic single shooting (symSS), that leverages the power of symbolic computing to generate an optimization problem of minimal dimension. This formulation is counter to the recent trend of introducing and exploiting sparsity of the MPC optimization problem for tailored solvers to exploit. We make use of this formulation widely in this thesis. The second contribution of this thesis is a novel application of proper orthogonal decomposition (POD) to MPC. In this strategy we construct a dimensionally-reduced optimization problem by restricting the problem Lagrangian to a subspace. This subspace is found by running simulations offline from which we extract the important solution features. Using this restricted Lagrangian we are able to reduce the problem dimension dramatically, thus simplifying the linear solve. This leads to TAT accelerations of more than two times with minimal controller degradation. The third contribution of this thesis is an informed move blocking strategy. This strategy exploits the features extracted in the restricted Lagrangian subspace to derive a sequence of increasingly blocked move blocking strategies. These move blocking strategies can then be used to reduce the dimension of the optimization problem in a sparse manner, leading to even greater acceleration of the controller TAT . The fourth contribution of this thesis is a new quasi-Newton method for MPC. This method utilizes ideas similar to singular perturbation-based model reduction to truncate the expression for the problem Hessian at the symbolic level. For nonlinear systems with a modest Lipschitz constant, we can identify the timestep as a `small' parameter about which we can do a perturbative expansion of the Lagrangian and its derivatives. Truncating to first order in the timestep, we are able to find a good approximation of the Hessian leading to TAT acceleration. The fifth contribution of this thesis is controller integration strategy based on nested MPCs. Using the symSS formulation we can construct an explicit model of a controlled plant that includes the full model as well as the MPC's action. This form of the controlled plant model allows us to generate exact derivatives so that fast solvers can be used for real time application. We focus here on the problem of planning and motion control integration for autonomous vehicles but this strategy can be extended for other problems that require accurate models of a controlled plant. The sixth contribution of this thesis is a strategy to handle integer controls in MPC based on a few reasonable assumptions: our predictions over the horizon are almost perfect and the future is inevitable. These assumptions enforce a…

Subjects/Keywords: model predictive control; nonlinear control; hybrid control

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Maitland, A. (2019). Nonlinear Model Predictive Control Reduction Strategies for Real-time Optimal Control. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/14524

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Maitland, Anson. “Nonlinear Model Predictive Control Reduction Strategies for Real-time Optimal Control.” 2019. Thesis, University of Waterloo. Accessed December 06, 2019. http://hdl.handle.net/10012/14524.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Maitland, Anson. “Nonlinear Model Predictive Control Reduction Strategies for Real-time Optimal Control.” 2019. Web. 06 Dec 2019.

Vancouver:

Maitland A. Nonlinear Model Predictive Control Reduction Strategies for Real-time Optimal Control. [Internet] [Thesis]. University of Waterloo; 2019. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/10012/14524.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Maitland A. Nonlinear Model Predictive Control Reduction Strategies for Real-time Optimal Control. [Thesis]. University of Waterloo; 2019. Available from: http://hdl.handle.net/10012/14524

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Illinois – Urbana-Champaign

24. Lee, Seung Ho. A model predictive control approach to a class of multiplayer minmax differential games.

Degree: PhD, Mechanical Engineering, 2016, University of Illinois – Urbana-Champaign

URL: http://hdl.handle.net/2142/90473

► In this dissertation, we consider a class of two-team adversarial differential games in which there are multiple mobile dynamic agents on each team. We describe… (more)

▼ In this dissertation, we consider a class of two-team adversarial differential games in which there are multiple mobile dynamic agents on each team. We describe such games in terms of semi-infinite minmax Model Predictive Control (MPC) problems, and present a numerical optimization technique for efficiently solving them. We also describe the implementation of the solution method in both indoor and outdoor robotic testbeds. Our solution method requires one to solve a sequence of Quadratic Programs (QPs), which together efficiently solve the original semi-infinite min- max MPC problem. The solution method separates the problem into two subproblems called the inner and outer subproblems, respectively. The inner subproblem is based on a constrained nonlinear numerical optimization technique called the Phase I-Phase II method, and we develop a customized version of this method. The outer subproblem is about judiciously initializing the inner subproblems to achieve overall convergence; our method guarantees exponential convergence. We focus on a specific semi-infinite minmax MPC problem called the harbor defense problem. First, we present foundational work on this problem in a formulation containing a single defender and single intruder. We next extend the basic formulation to various advanced scenarios that include cases in which there are multiple defenders and intruders, and also ones that include varying assumptions about intruder strategies. Another main contribution is that we implemented our solution method for the harbor defense problem on both real-time indoor and outdoor testbeds, and demonstrated its computational effectiveness. The indoor testbed is a custom-built robotic testbed named HoTDeC (Hovercraft Testbed for Decentralized Control). The outdoor testbed involved full-sized US Naval Academy patrol ships, and the experiment was conducted in Chesapeake Bay in collaboration with the US Naval Academy. The scenario used involved one ship (the intruder) being commanded by a human pilot, and the defender ship being controlled automatically by our semi-infinite minmax MPC algorithm.The results of several experiments are presented. Finally, we present an efficient algorithm for solving a class of matrix games, and show how this approach can be directly used to effectively solve our original continuous space semi-infinite minmax problem using an adaptive approximation. Advisors/Committee Members: Dullerud, Geir E (advisor), Dullerud, Geir E (Committee Chair), Basar, Tamer (committee member), Salapaka, Srinivasa (committee member), Mehta, Prashant (committee member).

Subjects/Keywords: model predictive control; min-max; differential games

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Lee, S. H. (2016). A model predictive control approach to a class of multiplayer minmax differential games. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/90473

Chicago Manual of Style (16^th Edition):

Lee, Seung Ho. “A model predictive control approach to a class of multiplayer minmax differential games.” 2016. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed December 06, 2019. http://hdl.handle.net/2142/90473.

MLA Handbook (7^th Edition):

Lee, Seung Ho. “A model predictive control approach to a class of multiplayer minmax differential games.” 2016. Web. 06 Dec 2019.

Vancouver:

Lee SH. A model predictive control approach to a class of multiplayer minmax differential games. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2016. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/2142/90473.

Council of Science Editors:

Lee SH. A model predictive control approach to a class of multiplayer minmax differential games. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2016. Available from: http://hdl.handle.net/2142/90473

University of New South Wales

25. Wang, Xu. Model Predictive Control for UAGV Path Tracking in the Presence of Wheel Slip.

Degree: Mechanical & Manufacturing Engineering, 2017, University of New South Wales

URL: http://handle.unsw.edu.au/1959.4/58474 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:46104/SOURCE02?view=true

► Investigation of Unmanned Agricultural Ground Vehicles (UAGVs) has been on the in- crease in recent decades as UAGVs have great potential in agricultural applications, and… (more)

▼ Investigation of Unmanned Agricultural Ground Vehicles (UAGVs) has been on the in- crease in recent decades as UAGVs have great potential in agricultural applications, and thus UAGVs are expected to rule farms in the future. The use of UAGVs benefits from replacing human operators to do tiresome as well as hazardous work, thus reducing the risk. It can also significantly improve the efficiency to solve food shortages due to the dramatic growth of world. Path Tracking has been an important topic in the development of UAGVs, however the automatic guidance of farm vehicle becomes more difficult and challenging than that of standard mobile robots as farm vehicles are subjected to significant disturbances due to rough terrain and ground engaging operations. The controller of autonomous farm vehicles is required to be sufficiently robust to both guarantee high path tracking accuracy and stability.This thesis mainly researches path tracking control methods for three kinds of UAGVs in the presence of significant wheel slip. In path tracking, UAGVs are guided to follow a de- sired path from an initial position while the controller keeps minimizing offsets with respect to the reference path. To achieve the accuracy required in agriculture, this work utilizes offset models derived based on kinematic models, which take both lateral and longitudinal slips into account. A model predictive controller with receding min-max optimization is then proposed to address the problem of wheel slip in UAGVs. This adaptive min-max model predictive controller provides both robustness and adaptation for path tracking.The superior performance of the proposed controller is verified by kinematic simulation, dynamic simulation as well as field testing, compared to that of the classical model predictive control. Then, the proposed controller is also compared with a well-known robust sliding mode controller and a well-performing backstepping controller, which is carried out by implementing controllers on a UAGV at Elizabeth Macarthur Agricultural Institute. Results from simulations and experiments validate that the proposed adaptive min-max model predictive controller ensures the required accuracy and robustness in the presence of wheel slip without any slip measurement or estimation.Page vii Advisors/Committee Members: Katupitiya, Jay, Mechanical & Manufacturing Engineering, Faculty of Engineering, UNSW.

Subjects/Keywords: Path Tracking; Model Predictive Control; Autonomous Vehicles

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APA (6^th Edition):

Wang, X. (2017). Model Predictive Control for UAGV Path Tracking in the Presence of Wheel Slip. (Masters Thesis). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/58474 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:46104/SOURCE02?view=true

Chicago Manual of Style (16^th Edition):

Wang, Xu. “Model Predictive Control for UAGV Path Tracking in the Presence of Wheel Slip.” 2017. Masters Thesis, University of New South Wales. Accessed December 06, 2019. http://handle.unsw.edu.au/1959.4/58474 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:46104/SOURCE02?view=true.

MLA Handbook (7^th Edition):

Wang, Xu. “Model Predictive Control for UAGV Path Tracking in the Presence of Wheel Slip.” 2017. Web. 06 Dec 2019.

Vancouver:

Wang X. Model Predictive Control for UAGV Path Tracking in the Presence of Wheel Slip. [Internet] [Masters thesis]. University of New South Wales; 2017. [cited 2019 Dec 06]. Available from: http://handle.unsw.edu.au/1959.4/58474 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:46104/SOURCE02?view=true.

Council of Science Editors:

Wang X. Model Predictive Control for UAGV Path Tracking in the Presence of Wheel Slip. [Masters Thesis]. University of New South Wales; 2017. Available from: http://handle.unsw.edu.au/1959.4/58474 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:46104/SOURCE02?view=true

UCLA

26. Anderson, Timothy. Distributed Economic Model Predictive Control of a Catalytic Reactor: Evaluation of Sequential and Iterative Architectures.

Degree: Chemical Engineering, 2014, UCLA

URL: http://www.escholarship.org/uc/item/7qm043kq

► In this work, the development and application of distributed economic model predictive control (DEMPC) methodologies to a catalytic reactor is considered. Specifically, two DEMPC methodologies… (more)

Subjects/Keywords: Chemical engineering; distributed model predictive control; economic model predictive control; nonlinear systems; process control

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APA (6^th Edition):

Anderson, T. (2014). Distributed Economic Model Predictive Control of a Catalytic Reactor: Evaluation of Sequential and Iterative Architectures. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/7qm043kq

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Anderson, Timothy. “Distributed Economic Model Predictive Control of a Catalytic Reactor: Evaluation of Sequential and Iterative Architectures.” 2014. Thesis, UCLA. Accessed December 06, 2019. http://www.escholarship.org/uc/item/7qm043kq.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Anderson, Timothy. “Distributed Economic Model Predictive Control of a Catalytic Reactor: Evaluation of Sequential and Iterative Architectures.” 2014. Web. 06 Dec 2019.

Vancouver:

Anderson T. Distributed Economic Model Predictive Control of a Catalytic Reactor: Evaluation of Sequential and Iterative Architectures. [Internet] [Thesis]. UCLA; 2014. [cited 2019 Dec 06]. Available from: http://www.escholarship.org/uc/item/7qm043kq.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Anderson T. Distributed Economic Model Predictive Control of a Catalytic Reactor: Evaluation of Sequential and Iterative Architectures. [Thesis]. UCLA; 2014. Available from: http://www.escholarship.org/uc/item/7qm043kq

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Sydney

27. Lamburn, Darren James. Efficient Constrained Algebraic Model Predictive Control for Aerospace Applications .

Degree: 2016, University of Sydney

URL: http://hdl.handle.net/2123/16331

► The major drawback of MPC is the computational burden associated with the large number of parameters it can be optimised over. One method that improves… (more)

Subjects/Keywords: Explicit model predictive control; efficient model predictive control; constraints; continuous linear systems.

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APA (6^th Edition):

Lamburn, D. J. (2016). Efficient Constrained Algebraic Model Predictive Control for Aerospace Applications . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/16331

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Lamburn, Darren James. “Efficient Constrained Algebraic Model Predictive Control for Aerospace Applications .” 2016. Thesis, University of Sydney. Accessed December 06, 2019. http://hdl.handle.net/2123/16331.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Lamburn, Darren James. “Efficient Constrained Algebraic Model Predictive Control for Aerospace Applications .” 2016. Web. 06 Dec 2019.

Vancouver:

Lamburn DJ. Efficient Constrained Algebraic Model Predictive Control for Aerospace Applications . [Internet] [Thesis]. University of Sydney; 2016. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/2123/16331.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lamburn DJ. Efficient Constrained Algebraic Model Predictive Control for Aerospace Applications . [Thesis]. University of Sydney; 2016. Available from: http://hdl.handle.net/2123/16331

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Pretoria

28. Le Roux, Johan Derik. Grinding mill circuit control from a plant-wide control perspective.

Degree: PhD, Electrical, Electronic and Computer Engineering, 2016, University of Pretoria

URL: http://hdl.handle.net/2263/61307

► 'n Generiese aanlegwye beheerstruktuur vir die optimale beheer van 'n maalmeulkring word voorgehou. 'n Ekonomiese doelwitfunksie is gedefinieer vir die maalmeulkringbaan met verwysing tot die… (more)

▼ 'n Generiese aanlegwye beheerstruktuur vir die optimale beheer van 'n maalmeulkring word voorgehou. 'n Ekonomiese doelwitfunksie is gedefinieer vir die maalmeulkringbaan met verwysing tot die ekonomiese doelwit van die groter mineraalverwerkingsaanleg. 'n Mineraalverwerkingsaanleg bestaan in hierdie studie slegs uit die vergruisings- en skeidingskringbane. Die ekstraktiewe metallurgie by die metaal raffinadery word uitgesluit. Die vergruisingskringbaan se operasionele werksverrigting is hoofsaaklik van die maalmeul se werksverrigting afhanklik. Aangesien maalkurwes die bereik van die maalmeul se werksverrigting beskryf, kan die maalkurwes gebruik word om die stelpunte van die ekonomiese beheerveranderlikes te definieer vir werking by optimale gestadigde toestand. Gegewe 'n bepaalde metaalprys, bedryfskoste, en vervoerkoste, kan die voorgestelde struktuur gebruik word om die optimale werksgebied vir die maalmeulkring te definieer vir die beste ekonomiese gewin van die algehele mineraalverwerkingsaanleg. Die aanlegwye beheerstruktuur omskryf die beheerveranderlikes en manipuleerbare veranderlikes wat benodig word om die maalmeulkring by die gewenste werksgebied te handhaaf. Die aanlegwye beheerstruktuur spesifiseer regulatoriese en toesighoudende beheer doelwitte. Hierdie doelwitte kan bereik word deur gebruik te maak van nie-lineêre model gebaseerde beheer. Die probleem is dat die bewerkingskoste om nie-lineëre optimeringsfunksies op te los 'n struikelblok is om model gebaseerde beheer op industriële aanlegte toe te pas. Ter oplossing hiervan, word die stelpunt-volg weergawe van model gebaseerde voorspellende statiese programmering (MVSP) toegepas op 'n maalmeulkringbaan. MVSP is 'n innoverende optimale beheertegniek, en bestaan uit 'n kombinasie van die filosofieë van model gebaseerder voorspellende beheer (MVB) en aanpassende dinamiese programmering. Die verrigting van die voorgestelde MVSP beheertegniek word vergelyk met die verrigting van 'n standaard nie-lineëre MVB (NMVB) tegniek deur beide beheertegnieke op dieselfde aanleg vir dieselfde toestande toe te pas. Resultate dui aan dat die MVSP beheertegniek in staat is om die gekose stelpunt te midde van model-aanleg wanaanpassing, steurnisse, en metingsgeraas te volg. Die verrigting van MVSP en NMVB vergelyk goed, maar MVSP bied duidelike voordele. Die bewerkingspoed vir MVSP word vinniger gemaak deur die dinamiese optimeringsprobleem in 'n laeorde statiese optimeringsprobleem te omskep, die sensitiwiteitsmatrikse rekursief uit te werk, en deur 'n geslote uitdrukking ter opdatering van die beheeraksie te gebruik. Die MVSP beheertegniek benodig normaalweg slegs 'n paar iterasies om tot 'n oplossing te konvergeer, selfs indien beperkings op die insette toegepas word. Om die rede word MVSP as 'n potensiële kandidaat beskou vir aanlyntoepasings van die NMVB filosofie op industriële aanlegte. Die MVSP en NMVB simulasie studies hierbo neem aan dat volle toestandterugvoer moontlik is. Hierdie is nie altyd moontlik vir industriële… Advisors/Committee Members: Craig, Ian K. (advisor).

Subjects/Keywords: UCTD; Mineral processing; Model predictive control; Model predictive static programming; State and parameter estimation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Le Roux, J. D. (2016). Grinding mill circuit control from a plant-wide control perspective. (Doctoral Dissertation). University of Pretoria. Retrieved from http://hdl.handle.net/2263/61307

Chicago Manual of Style (16^th Edition):

Le Roux, Johan Derik. “Grinding mill circuit control from a plant-wide control perspective.” 2016. Doctoral Dissertation, University of Pretoria. Accessed December 06, 2019. http://hdl.handle.net/2263/61307.

MLA Handbook (7^th Edition):

Le Roux, Johan Derik. “Grinding mill circuit control from a plant-wide control perspective.” 2016. Web. 06 Dec 2019.

Vancouver:

Le Roux JD. Grinding mill circuit control from a plant-wide control perspective. [Internet] [Doctoral dissertation]. University of Pretoria; 2016. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/2263/61307.

Council of Science Editors:

Le Roux JD. Grinding mill circuit control from a plant-wide control perspective. [Doctoral Dissertation]. University of Pretoria; 2016. Available from: http://hdl.handle.net/2263/61307

Cornell University

29. Dobbs, Justin. Toward A Streamlined Software Tool Chain For Cyber-Physical Buildings .

Degree: 2015, Cornell University

URL: http://hdl.handle.net/1813/41112

► Heating, ventilation, and air conditioning (HVAC) systems account for more than half of commercial building energy usage. Unfortunately, bottlenecks in early-stage design, control system implementation,… (more)

Subjects/Keywords: model order reduction; model predictive control; Markov occupancy model

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APA (6^th Edition):

Dobbs, J. (2015). Toward A Streamlined Software Tool Chain For Cyber-Physical Buildings . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/41112

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Dobbs, Justin. “Toward A Streamlined Software Tool Chain For Cyber-Physical Buildings .” 2015. Thesis, Cornell University. Accessed December 06, 2019. http://hdl.handle.net/1813/41112.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Dobbs, Justin. “Toward A Streamlined Software Tool Chain For Cyber-Physical Buildings .” 2015. Web. 06 Dec 2019.

Vancouver:

Dobbs J. Toward A Streamlined Software Tool Chain For Cyber-Physical Buildings . [Internet] [Thesis]. Cornell University; 2015. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/1813/41112.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Dobbs J. Toward A Streamlined Software Tool Chain For Cyber-Physical Buildings . [Thesis]. Cornell University; 2015. Available from: http://hdl.handle.net/1813/41112

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Alberta

30. Iqbal, Mohammad Hasan. Advanced control of the twin screw extruder.

Degree: PhD, Department of Chemical and Materials Engineering, 2010, University of Alberta

URL: https://era.library.ualberta.ca/files/2f75r837g

► This research deals with the modeling and control of a plasticating twin screw extruder (TSE) that will be used to obtain consistent product quality. The… (more)

▼ This research deals with the modeling and control of a plasticating twin screw extruder (TSE) that will be used to obtain consistent product quality. The TSE is a widely used process technology for compounding raw polymers. Compounding creates a polymer with improved properties that satisfy the demand of modern plastic applications. Modeling and control of a TSE is challenging because of its high nonlinearity, inherent time delay, and multiple interactive dynamic behavior. A complete methodology is proposed in this thesis to design an advanced control scheme for a TSE. This methodology was used to develop a model predictive control scheme for a laboratory scale plasticating TSE and to implement the control scheme in real-time. The TSE has a processing length of 925 mm and a length to screw diameter ratio (L/D) of 37. High density polyethylenes with different melt indices were used as processing materials. Manipulated variables and disturbance variables were selected based on knowledge of the process. Controlled variables were selected using a selection method that includes a steady state correlation between process output variables and product quality variables, and dynamic considerations. Two process output variables, melt temperature (Tm) at the die and melt pressure (Pm) at the die, were selected as controlled variables. A new modeling approach was proposed to develop grey box models based on excitation in the extruder screw speed (N), one of the manipulated variables. The extruder was excited using a predesigned random binary sequence (RBS) type excitation in N and nonlinear models relating Tm and Pm to N were developed using this approach. System identification techniques were used to obtain model parameters. The obtained models have an autoregressive moving average with exogenous (ARMAX) input structure and the models explain the physics of the extrusion process successfully. The TSE was also excited using a predesigned RBS in the feed rate (F) as a manipulated variable. Models relating Tm and Pm to F were developed using a classical system identification technique; both models have ARMAX structures. The model between Pm and F was found to give excellent prediction for data obtained from a stair type excitation, indicating that the obtained models provide a good representation of the dynamics of the twin screw extruder. Analysis of the TSE open loop process indicated two manipulated variables, N and F, and two controlled variables, Tm and Pm. Thus, a model predictive controller (MPC) was designed using the developed models for this 2X2 system and implemented in real-time. The performance of the MPC was studied by checking its set-point tracking ability. The robustness of the MPC was also examined by imposing external disturbances. Finally, a multimodel operating regime was used to model Tm and N. The operating regime was divided based on the screw speed, N. Local models were developed using system identification techniques. The global model was developed by combining local models using fuzzy logic methodology.…

Subjects/Keywords: Model predictive controller; Grey box model; Twin screw extruder; Process Identification

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Iqbal, M. H. (2010). Advanced control of the twin screw extruder. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/2f75r837g

Chicago Manual of Style (16^th Edition):

Iqbal, Mohammad Hasan. “Advanced control of the twin screw extruder.” 2010. Doctoral Dissertation, University of Alberta. Accessed December 06, 2019. https://era.library.ualberta.ca/files/2f75r837g.

MLA Handbook (7^th Edition):

Iqbal, Mohammad Hasan. “Advanced control of the twin screw extruder.” 2010. Web. 06 Dec 2019.

Vancouver:

Iqbal MH. Advanced control of the twin screw extruder. [Internet] [Doctoral dissertation]. University of Alberta; 2010. [cited 2019 Dec 06]. Available from: https://era.library.ualberta.ca/files/2f75r837g.

Council of Science Editors:

Iqbal MH. Advanced control of the twin screw extruder. [Doctoral Dissertation]. University of Alberta; 2010. Available from: https://era.library.ualberta.ca/files/2f75r837g

Open Access Theses and Dissertations