subject:(Adaptive fuzzy logic control)

Rochester Institute of Technology

1. Naghshineh, Nastaran. Control of Thermal Power System Using Adaptive Fuzzy Logic Control.

Degree: MS, Electrical Engineering, 2017, Rochester Institute of Technology

URL: https://scholarworks.rit.edu/theses/9615

► Controlling thermal power systems increases the overall system efficiency and satisfies the desired requirements. In such a large system, fuel reduction of even a… (more)

Subjects/Keywords: Adaptive fuzzy logic control; Control; Fuzzy logic; Multi-area power system; PID; Thermal power system

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APA (6^th Edition):

Naghshineh, N. (2017). Control of Thermal Power System Using Adaptive Fuzzy Logic Control. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9615

Chicago Manual of Style (16^th Edition):

Naghshineh, Nastaran. “Control of Thermal Power System Using Adaptive Fuzzy Logic Control.” 2017. Masters Thesis, Rochester Institute of Technology. Accessed January 20, 2021. https://scholarworks.rit.edu/theses/9615.

MLA Handbook (7^th Edition):

Naghshineh, Nastaran. “Control of Thermal Power System Using Adaptive Fuzzy Logic Control.” 2017. Web. 20 Jan 2021.

Vancouver:

Naghshineh N. Control of Thermal Power System Using Adaptive Fuzzy Logic Control. [Internet] [Masters thesis]. Rochester Institute of Technology; 2017. [cited 2021 Jan 20]. Available from: https://scholarworks.rit.edu/theses/9615.

Council of Science Editors:

Naghshineh N. Control of Thermal Power System Using Adaptive Fuzzy Logic Control. [Masters Thesis]. Rochester Institute of Technology; 2017. Available from: https://scholarworks.rit.edu/theses/9615

University of Cincinnati

2. Stockton, Nicklas O. Hybrid Genetic Fuzzy Systems for Control of Dynamic Systems.

Degree: MS, Engineering and Applied Science: Aerospace Engineering, 2018, University of Cincinnati

URL: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1523635312922039

► Aerospace applications are composed of many dynamic systems which are coupled, nonlinear, and difficult to control. Fuzzy logic (FL) systems provides a means by which… (more)

▼ Aerospace applications are composed of many dynamic systems which are coupled, nonlinear, and difficult to control. Fuzzy logic (FL) systems provides a means by which to encode expert knowledge into a set of rules which can produce highly nonlinear control signals; this is possible because FL, like many other soft computational methods is a universal approximator. While FL systems alone excel at encapsulating expert knowledge bases, when coupled with genetic algorithms (GA), they can learn the knowledge base from evolutionary repetition. It is the goal of this work to present the efficacy of hybrid genetic fuzzy systems (GFS) in a variety of applications. This will be achieved through exploring three specific use cases.First, a variation of a benchmark problem presented at the 1990 American Control Conference is used todemonstrate the robustness of FL control as well as the utility of GAs in the learning process. The results are a controller that is far more resistant to even large changes in the plant dynamics compared to a linear controller and a process by which a class of controllers may be quickly tuned for changes to the plant system.The next problem applies the same approach to an elevator actuator for pitch control of an F-4 Phantom. This controller is tuned for a nominal case and ten subjected to the same plant with degraded aerodynamic coefficients. It is compared to a well-tuned PID controller.The effort culminates in a practical application of a FL system to guide a small unmanned aerial system (sUAS) to a precision landing on a target platform moving with uncertain velocity. This was accomplished using custom developed Python software for GFS control in conjunction with Robot Operating System (ROS) and a simulation environment called Gazebo. Heavy emphasis was placed on using only software components which can be easily implemented on popular hardware platforms. ROS was critical to meeting this goal, as well as the open source flight controller project PX4. A controller is presented which is capable of exerting the control necessary to guide the vehicle to a successful landing on both a static and moving platform. Advisors/Committee Members: Cohen, Kelly (Committee Chair).

Subjects/Keywords: Engineering; genetic algorithm; fuzzy logic; dynamic system; nonlinear control; adaptive control

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APA (6^th Edition):

Stockton, N. O. (2018). Hybrid Genetic Fuzzy Systems for Control of Dynamic Systems. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1523635312922039

Chicago Manual of Style (16^th Edition):

Stockton, Nicklas O. “Hybrid Genetic Fuzzy Systems for Control of Dynamic Systems.” 2018. Masters Thesis, University of Cincinnati. Accessed January 20, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1523635312922039.

MLA Handbook (7^th Edition):

Stockton, Nicklas O. “Hybrid Genetic Fuzzy Systems for Control of Dynamic Systems.” 2018. Web. 20 Jan 2021.

Vancouver:

Stockton NO. Hybrid Genetic Fuzzy Systems for Control of Dynamic Systems. [Internet] [Masters thesis]. University of Cincinnati; 2018. [cited 2021 Jan 20]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1523635312922039.

Council of Science Editors:

Stockton NO. Hybrid Genetic Fuzzy Systems for Control of Dynamic Systems. [Masters Thesis]. University of Cincinnati; 2018. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1523635312922039

Virginia Tech

3. Lloyd, John William. Generalized Predictive Control Parameter Adaptation Using a Fuzzy Logic Approach.

Degree: PhD, Mechanical Engineering, 2011, Virginia Tech

URL: http://hdl.handle.net/10919/29306

► A method to adapt the Generalized Predictive Control parameters to improve broadband disturbance rejection was developed and tested. The effect of the parameters on disturbance… (more)

Subjects/Keywords: GPC; generalized predictive control; active control; adaptive control; fuzzy logic; fuzzy logic adaptation; vibration control; disturbance rejection

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APA (6^th Edition):

Lloyd, J. W. (2011). Generalized Predictive Control Parameter Adaptation Using a Fuzzy Logic Approach. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/29306

Chicago Manual of Style (16^th Edition):

Lloyd, John William. “Generalized Predictive Control Parameter Adaptation Using a Fuzzy Logic Approach.” 2011. Doctoral Dissertation, Virginia Tech. Accessed January 20, 2021. http://hdl.handle.net/10919/29306.

MLA Handbook (7^th Edition):

Lloyd, John William. “Generalized Predictive Control Parameter Adaptation Using a Fuzzy Logic Approach.” 2011. Web. 20 Jan 2021.

Vancouver:

Lloyd JW. Generalized Predictive Control Parameter Adaptation Using a Fuzzy Logic Approach. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/10919/29306.

Council of Science Editors:

Lloyd JW. Generalized Predictive Control Parameter Adaptation Using a Fuzzy Logic Approach. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/29306

Ryerson University

4. Huang, Liang. Physical-Rule Based Adaptive Neuro-Fuzzy Inferential Sensor For Optimal Control Of Space Heating Systems.

Degree: 2012, Ryerson University

URL: https://digital.library.ryerson.ca/islandora/object/RULA%3A1454

► The previous research on adaptive neuro-fuzzy inferential sensor (ANFIS) presented an approach to estimate the average indoor temperature and proposed a new method to measure… (more)

Subjects/Keywords: Fuzzy logic; Adaptive control systems; Control theory; Detectors – Design and construction; Detectors – Mathematical models

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APA (6^th Edition):

Huang, L. (2012). Physical-Rule Based Adaptive Neuro-Fuzzy Inferential Sensor For Optimal Control Of Space Heating Systems. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A1454

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):

Huang, Liang. “Physical-Rule Based Adaptive Neuro-Fuzzy Inferential Sensor For Optimal Control Of Space Heating Systems.” 2012. Thesis, Ryerson University. Accessed January 20, 2021. https://digital.library.ryerson.ca/islandora/object/RULA%3A1454.

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

MLA Handbook (7^th Edition):

Huang, Liang. “Physical-Rule Based Adaptive Neuro-Fuzzy Inferential Sensor For Optimal Control Of Space Heating Systems.” 2012. Web. 20 Jan 2021.

Vancouver:

Huang L. Physical-Rule Based Adaptive Neuro-Fuzzy Inferential Sensor For Optimal Control Of Space Heating Systems. [Internet] [Thesis]. Ryerson University; 2012. [cited 2021 Jan 20]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A1454.

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

Council of Science Editors:

Huang L. Physical-Rule Based Adaptive Neuro-Fuzzy Inferential Sensor For Optimal Control Of Space Heating Systems. [Thesis]. Ryerson University; 2012. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A1454

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

Addis Ababa University

5. Daniel, Abebe. Design and Implementation of Feedback Linearization based Adaptive Stabilizing Controller Coupled with Fuzzy Logic Swing-up for Pendulum on a Cart .

Degree: 2019, Addis Ababa University

URL: http://etd.aau.edu.et/handle/123456789/20966

► This thesis address an adaptive stabilizing controller for inverted pendulum on a cart based on feedback linearization coupled with an adaptive fuzzy logic based swing… (more)

Subjects/Keywords: Feedback Linearization; Fuzzy Logic; Adaptive Inverse Control; Inverted Pendulum on a Cart; Swing up

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APA (6^th Edition):

Daniel, A. (2019). Design and Implementation of Feedback Linearization based Adaptive Stabilizing Controller Coupled with Fuzzy Logic Swing-up for Pendulum on a Cart . (Thesis). Addis Ababa University. Retrieved from http://etd.aau.edu.et/handle/123456789/20966

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):

Daniel, Abebe. “Design and Implementation of Feedback Linearization based Adaptive Stabilizing Controller Coupled with Fuzzy Logic Swing-up for Pendulum on a Cart .” 2019. Thesis, Addis Ababa University. Accessed January 20, 2021. http://etd.aau.edu.et/handle/123456789/20966.

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

MLA Handbook (7^th Edition):

Daniel, Abebe. “Design and Implementation of Feedback Linearization based Adaptive Stabilizing Controller Coupled with Fuzzy Logic Swing-up for Pendulum on a Cart .” 2019. Web. 20 Jan 2021.

Vancouver:

Daniel A. Design and Implementation of Feedback Linearization based Adaptive Stabilizing Controller Coupled with Fuzzy Logic Swing-up for Pendulum on a Cart . [Internet] [Thesis]. Addis Ababa University; 2019. [cited 2021 Jan 20]. Available from: http://etd.aau.edu.et/handle/123456789/20966.

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

Council of Science Editors:

Daniel A. Design and Implementation of Feedback Linearization based Adaptive Stabilizing Controller Coupled with Fuzzy Logic Swing-up for Pendulum on a Cart . [Thesis]. Addis Ababa University; 2019. Available from: http://etd.aau.edu.et/handle/123456789/20966

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

Central Queensland University

6. Zajaczkowski, Juliusz M. Analysis of the hierarchical fuzzy control using evolutionary algorithms.

Degree: 2010, Central Queensland University

URL: http://hdl.cqu.edu.au/10018/61271

"The research presented in this thesis examines the construction of a fuzzy logic controller for complex nonlinear system by control system decomposition into hierarchial fuzzy logic subsystems ... evolutionary algorithm (EA) based methods are proposed to determine the control system for the hieracrchical fuzzy system (HFS)" – Abstract.

Subjects/Keywords: Fuzzy logic.; Logic devices; Control theory.; Fuzzy systems.; TBA.; TBA.; TBA.

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APA (6^th Edition):

Zajaczkowski, J. M. (2010). Analysis of the hierarchical fuzzy control using evolutionary algorithms. (Thesis). Central Queensland University. Retrieved from http://hdl.cqu.edu.au/10018/61271

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):

Zajaczkowski, Juliusz M. “Analysis of the hierarchical fuzzy control using evolutionary algorithms.” 2010. Thesis, Central Queensland University. Accessed January 20, 2021. http://hdl.cqu.edu.au/10018/61271.

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

MLA Handbook (7^th Edition):

Zajaczkowski, Juliusz M. “Analysis of the hierarchical fuzzy control using evolutionary algorithms.” 2010. Web. 20 Jan 2021.

Vancouver:

Zajaczkowski JM. Analysis of the hierarchical fuzzy control using evolutionary algorithms. [Internet] [Thesis]. Central Queensland University; 2010. [cited 2021 Jan 20]. Available from: http://hdl.cqu.edu.au/10018/61271.

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

Council of Science Editors:

Zajaczkowski JM. Analysis of the hierarchical fuzzy control using evolutionary algorithms. [Thesis]. Central Queensland University; 2010. Available from: http://hdl.cqu.edu.au/10018/61271

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

7. Arsava, Kemal Sarp. Modeling, Control and Monitoring of Smart Structures under High Impact Loads.

Degree: PhD, 2014, Worcester Polytechnic Institute

URL: etd-041214-153536 ; https://digitalcommons.wpi.edu/etd-dissertations/105

► In recent years, response analysis of complex structures under impact loads has attracted a great deal of attention. For example, a collision or an accident… (more)

▼ In recent years, response analysis of complex structures under impact loads has attracted a great deal of attention. For example, a collision or an accident that produces impact loads that exceed the design load can cause severe damage on the structural components. Although the AASHTO specification is used for impact-resistant bridge design, it has many limitations. The AASHTO specification does not incorporate complex and uncertain factors. Thus, a well-designed structure that can survive a collision under specific conditions in one region may be severely damaged if it were impacted by a different vessel, or if it were located elsewhere with different in-situ conditions. With these limitations in mind, we propose different solutions that use smart control technology to mitigate impact hazard on structures. However, it is challenging to develop an accurate mathematical model of the integrated structure-smart control systems. The reason is due to the complicated nonlinear behavior of the integrated nonlinear systems and uncertainties of high impact forces. In this context, novel algorithms are developed for identification, control and monitoring of nonlinear responses of smart structures under high impact forces. To evaluate the proposed approaches, a smart aluminum and two smart reinforced concrete beam structures were designed, manufactured, and tested in the High Impact Engineering Laboratory of Civil and Environmental Engineering at WPI. High-speed impact force and structural responses such as strain, deflection and acceleration were measured in the experimental tests. It has been demonstrated from the analytical and experimental study that: 1) the proposed system identification model predicts nonlinear behavior of smart structures under a variety of high impact forces, 2) the developed structural health monitoring algorithm is effective in identifying damage in time-varying nonlinear dynamic systems under ambient excitations, and 3) the proposed controller is effective in mitigating high impact responses of the smart structures. Advisors/Committee Members: Yeesock Kim, Advisor, Tahar El-Korchi, Department Head, Leonard D. Albano, Committee Member, Jo Woon Chong, Committee Member.

Subjects/Keywords: high impact load; magnetorheological (MR) damper; discrete wavelet transform; fuzzy logic control; structural health monitoring; nonlinear system identification; adaptive neuro-fuzzy inference system (ANFIS)

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APA (6^th Edition):

Arsava, K. S. (2014). Modeling, Control and Monitoring of Smart Structures under High Impact Loads. (Doctoral Dissertation). Worcester Polytechnic Institute. Retrieved from etd-041214-153536 ; https://digitalcommons.wpi.edu/etd-dissertations/105

Chicago Manual of Style (16^th Edition):

Arsava, Kemal Sarp. “Modeling, Control and Monitoring of Smart Structures under High Impact Loads.” 2014. Doctoral Dissertation, Worcester Polytechnic Institute. Accessed January 20, 2021. etd-041214-153536 ; https://digitalcommons.wpi.edu/etd-dissertations/105.

MLA Handbook (7^th Edition):

Arsava, Kemal Sarp. “Modeling, Control and Monitoring of Smart Structures under High Impact Loads.” 2014. Web. 20 Jan 2021.

Vancouver:

Arsava KS. Modeling, Control and Monitoring of Smart Structures under High Impact Loads. [Internet] [Doctoral dissertation]. Worcester Polytechnic Institute; 2014. [cited 2021 Jan 20]. Available from: etd-041214-153536 ; https://digitalcommons.wpi.edu/etd-dissertations/105.

Council of Science Editors:

Arsava KS. Modeling, Control and Monitoring of Smart Structures under High Impact Loads. [Doctoral Dissertation]. Worcester Polytechnic Institute; 2014. Available from: etd-041214-153536 ; https://digitalcommons.wpi.edu/etd-dissertations/105

8. Mohammadzadeh, Soroush. System identification and control of smart structures: PANFIS modeling method and dissipativity analysis of LQR controllers.

Degree: MS, 2013, Worcester Polytechnic Institute

URL: etd-053013-222736 ; https://digitalcommons.wpi.edu/etd-theses/868

► "Maintaining an efficient and reliable infrastructure requires continuous monitoring and control. In order to accomplish these tasks, algorithms are needed to process large sets of… (more)

Subjects/Keywords: Magnetorheological Damper; Neural network; Adaptive Neuro-Fuzzy Inference System; Earthquake; System Identification; Dissipativity; Linear Quadratic Regulator; Structural Control; Smart Structures; Fuzzy Logic; Principal Component Analysis

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APA (6^th Edition):

Mohammadzadeh, S. (2013). System identification and control of smart structures: PANFIS modeling method and dissipativity analysis of LQR controllers. (Thesis). Worcester Polytechnic Institute. Retrieved from etd-053013-222736 ; https://digitalcommons.wpi.edu/etd-theses/868

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):

Mohammadzadeh, Soroush. “System identification and control of smart structures: PANFIS modeling method and dissipativity analysis of LQR controllers.” 2013. Thesis, Worcester Polytechnic Institute. Accessed January 20, 2021. etd-053013-222736 ; https://digitalcommons.wpi.edu/etd-theses/868.

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

MLA Handbook (7^th Edition):

Mohammadzadeh, Soroush. “System identification and control of smart structures: PANFIS modeling method and dissipativity analysis of LQR controllers.” 2013. Web. 20 Jan 2021.

Vancouver:

Mohammadzadeh S. System identification and control of smart structures: PANFIS modeling method and dissipativity analysis of LQR controllers. [Internet] [Thesis]. Worcester Polytechnic Institute; 2013. [cited 2021 Jan 20]. Available from: etd-053013-222736 ; https://digitalcommons.wpi.edu/etd-theses/868.

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

Council of Science Editors:

Mohammadzadeh S. System identification and control of smart structures: PANFIS modeling method and dissipativity analysis of LQR controllers. [Thesis]. Worcester Polytechnic Institute; 2013. Available from: etd-053013-222736 ; https://digitalcommons.wpi.edu/etd-theses/868

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

Texas Tech University

9. Workman, Mark E. Hardware requirements for fuzzy logic control systems.

Degree: Computer Science, 1996, Texas Tech University

URL: http://hdl.handle.net/2346/19473

► The FUzzy Design GEnerator (FUDGE) is an inexpensive, but surprisingly powerful, fuzzy logic design tool. It can be used to develop, test and implement fuzzy… (more)

Subjects/Keywords: Adaptive control systems; Computation intelligence; Fuzzy logic; Neural networks; FUDGE (Fuzzy Design Generator)

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APA (6^th Edition):

Workman, M. E. (1996). Hardware requirements for fuzzy logic control systems. (Thesis). Texas Tech University. Retrieved from http://hdl.handle.net/2346/19473

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):

Workman, Mark E. “Hardware requirements for fuzzy logic control systems.” 1996. Thesis, Texas Tech University. Accessed January 20, 2021. http://hdl.handle.net/2346/19473.

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

MLA Handbook (7^th Edition):

Workman, Mark E. “Hardware requirements for fuzzy logic control systems.” 1996. Web. 20 Jan 2021.

Vancouver:

Workman ME. Hardware requirements for fuzzy logic control systems. [Internet] [Thesis]. Texas Tech University; 1996. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2346/19473.

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

Council of Science Editors:

Workman ME. Hardware requirements for fuzzy logic control systems. [Thesis]. Texas Tech University; 1996. Available from: http://hdl.handle.net/2346/19473

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

University of Johannesburg

10. Schepers, Gideon Gustaf. The development of a multi-input-single-output fuzzy logic greenhouse controller.

Degree: 2012, University of Johannesburg

URL: http://hdl.handle.net/10210/7272

►

M.Ing.

Fuzzy controllers are increasingly being accepted by engineers and scientists alike as a viable alternative for classical controllers. The processes involved in fuzzy controllers… (more)

Subjects/Keywords: Feedback control systems; Control systems; Fuzzy systems; Fuzzy logic

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APA (6^th Edition):

Schepers, G. G. (2012). The development of a multi-input-single-output fuzzy logic greenhouse controller. (Thesis). University of Johannesburg. Retrieved from http://hdl.handle.net/10210/7272

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):

Schepers, Gideon Gustaf. “The development of a multi-input-single-output fuzzy logic greenhouse controller.” 2012. Thesis, University of Johannesburg. Accessed January 20, 2021. http://hdl.handle.net/10210/7272.

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

MLA Handbook (7^th Edition):

Schepers, Gideon Gustaf. “The development of a multi-input-single-output fuzzy logic greenhouse controller.” 2012. Web. 20 Jan 2021.

Vancouver:

Schepers GG. The development of a multi-input-single-output fuzzy logic greenhouse controller. [Internet] [Thesis]. University of Johannesburg; 2012. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/10210/7272.

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

Council of Science Editors:

Schepers GG. The development of a multi-input-single-output fuzzy logic greenhouse controller. [Thesis]. University of Johannesburg; 2012. Available from: http://hdl.handle.net/10210/7272

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

Texas A&M University

11. Sunberg, Zachary Nolan. A Real Time Expert Control System for Helicopter Autorotation.

Degree: MS, Aerospace Engineering, 2013, Texas A&M University

URL: http://hdl.handle.net/1969.1/149553

► Autorotation maneuvers are required to perform a safe landing of a helicopter in cases of engine loss in a single engine vehicle and transmission or… (more)

Subjects/Keywords: Autorotation; Expert System; Fuzzy Logic; Control; Helicopter

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APA (6^th Edition):

Sunberg, Z. N. (2013). A Real Time Expert Control System for Helicopter Autorotation. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/149553

Chicago Manual of Style (16^th Edition):

Sunberg, Zachary Nolan. “A Real Time Expert Control System for Helicopter Autorotation.” 2013. Masters Thesis, Texas A&M University. Accessed January 20, 2021. http://hdl.handle.net/1969.1/149553.

MLA Handbook (7^th Edition):

Sunberg, Zachary Nolan. “A Real Time Expert Control System for Helicopter Autorotation.” 2013. Web. 20 Jan 2021.

Vancouver:

Sunberg ZN. A Real Time Expert Control System for Helicopter Autorotation. [Internet] [Masters thesis]. Texas A&M University; 2013. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1969.1/149553.

Council of Science Editors:

Sunberg ZN. A Real Time Expert Control System for Helicopter Autorotation. [Masters Thesis]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/149553

KTH

12. Lundin, Gustav Öman. Enhancements of an auto-thrustfunction using fuzzy logic.

Degree: Optimization and Systems Theory, 2014, KTH

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-153940

► This master's thesis aims to investigate how fuzzy logic can be used to adapt the tuning of a speed control law during certain conditions… (more)

▼ This master's thesis aims to investigate how fuzzy logic can be used to adapt the tuning of a speed control law during certain conditions such as turbulence. The objective is to lower the speed overshoot caused by the auto-thrust function as well as the general engine agitation. The main modifications studied are direct lowering of the closed loop gains, hybridisation and filtering of the longitudinal acceleration estimation. Finally, saturations or limits on the control signal as well as on the coordination with the longitudinal control law are studied in order to cope with the possible consequences of a softer control law. To detect the turbulence, an already existing turbulence detector is used. In addition, a wind gradient detector is designed in order to increase the gain during such wind conditions to counter ramp errors. It is found that a general lowering of the closed loop gain in combination with a slow hybridisation, all proportional to the detected turbulence level, together with a limitation of the coordination gives a satisfactory result. In scenarios including severe turbulence and wind gradients, the forced limits are shown to be indispensable. A conclusion is drawn that the fuzzy tuning is better adapted to turbulent conditions but that the wind gradient detection and the forced limits must be studied further. It is also concluded that the coupling between the closed loop gain and the acceleration hybridisation can be interesting to investigate. Moreover, additional realistic scenarios should be simulated in order to further validate the design. For future studies on the subject; it is recommended that the controller tuning is validated with the help of expert knowledge. Alternatively, the tuning could be handled by an ANFIS (Adaptive Neuro Fuzzy Inference System). Finally the tuning of the controller should be validated for a wider range of flight points, most importantly the forced limits since the engine response varies a lot between different points in the flight envelope.

Subjects/Keywords: Fuzzy logic; aircraft speed control; turbulence

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APA (6^th Edition):

Lundin, G. �. (2014). Enhancements of an auto-thrustfunction using fuzzy logic. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-153940

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):

Lundin, Gustav Öman. “Enhancements of an auto-thrustfunction using fuzzy logic.” 2014. Thesis, KTH. Accessed January 20, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-153940.

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

MLA Handbook (7^th Edition):

Lundin, Gustav Öman. “Enhancements of an auto-thrustfunction using fuzzy logic.” 2014. Web. 20 Jan 2021.

Vancouver:

Lundin G�. Enhancements of an auto-thrustfunction using fuzzy logic. [Internet] [Thesis]. KTH; 2014. [cited 2021 Jan 20]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-153940.

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

Council of Science Editors:

Lundin G�. Enhancements of an auto-thrustfunction using fuzzy logic. [Thesis]. KTH; 2014. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-153940

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

North Carolina State University

13. Al-mutairi, Naif Bejad. Adaptive Fuzzy Modulation for Networked PI Control Systems.

Degree: PhD, Electrical Engineering, 2002, North Carolina State University

URL: http://www.lib.ncsu.edu/resolver/1840.16/5831

► Networks and their applications have been evolving substantially in the last two decades. Network-based control systems, also called Networked Control Systems (NCS), are one of… (more)

Subjects/Keywords: fuzzy logic; networked control systems; PI control; adaptive systems; network-based control

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

APA (6^th Edition):

Al-mutairi, N. B. (2002). Adaptive Fuzzy Modulation for Networked PI Control Systems. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/5831

Chicago Manual of Style (16^th Edition):

Al-mutairi, Naif Bejad. “Adaptive Fuzzy Modulation for Networked PI Control Systems.” 2002. Doctoral Dissertation, North Carolina State University. Accessed January 20, 2021. http://www.lib.ncsu.edu/resolver/1840.16/5831.

MLA Handbook (7^th Edition):

Al-mutairi, Naif Bejad. “Adaptive Fuzzy Modulation for Networked PI Control Systems.” 2002. Web. 20 Jan 2021.

Vancouver:

Al-mutairi NB. Adaptive Fuzzy Modulation for Networked PI Control Systems. [Internet] [Doctoral dissertation]. North Carolina State University; 2002. [cited 2021 Jan 20]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/5831.

Council of Science Editors:

Al-mutairi NB. Adaptive Fuzzy Modulation for Networked PI Control Systems. [Doctoral Dissertation]. North Carolina State University; 2002. Available from: http://www.lib.ncsu.edu/resolver/1840.16/5831

Delft University of Technology

14. Bindiganavile Nagesh, S. (author). Adaptive fuzzy observer and robust controller for a 2-DOF robot arm.

Degree: 2011, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:1aba8c30-3269-4cc3-b913-e3d4eb15912f

►

Adaptive fuzzy observers have been introduced in the recent past, which are capable of estimating uncertainties along with the states of a nonlinear system represented… (more)

▼

Adaptive fuzzy observers have been introduced in the recent past, which are capable of estimating uncertainties along with the states of a nonlinear system represented by an uncertain Takagi-Sugeno (TS) model. Application of such an observer to obtain estimates of the uncertainties in the state matrices and subsequently use them in the control of TS fuzzy models is the subject matter of this thesis. To demonstrate the adaptive observer and the controller design we use a 2-DOF robot arm model. The parameters of the robot arm are estimated for a laboratory-scale setup. The nonlinear model of the robot arm, consisting of six nonlinearities is simplified to contain only two nonlinearities. Then a four-rule TS fuzzy model is constructed using sector nonlinearity approach. The simplified nonlinear model and hence the fuzzy model almost exactly represent the complete nonlinear model. The mismatch in the plant and the nonlinear model is attributed to unmodelled dynamics in the state matrices. Assuming constant uncertainties in specific locations of the state matrices, an adaptive observer is used to estimate them and the simulation results are presented. The possibility to use the information about the structure of the uncertainties in the TS fuzzy model in designing the uncertainty estimation experiment is also presented. The uncertainty estimates provided by the adaptive observer are used to update the fuzzy model of the nonlinear system. The new model is used in the design of a robust state feedback stabilizing controller. Since the estimates obtained from the adaptive observer are used in controller design, the uncertainty distribution structure used in the design of both adaptive observer and the robust controller need to be same. Hence, a robust controller design is developed that uses the same uncertainty distribution structure as the adaptive observer. From the experimental results, it is concluded that stability can be guaranteed with a higher decay rate when using the updated model in robust controller design.

Embedded Systems

Delft Center for Systems and Control

Electrical Engineering, Mathematics and Computer Science

Advisors/Committee Members: Babuska, R. (mentor), Lendek, Z. (mentor), Khalate, A.A. (mentor).

Subjects/Keywords: adaptive fuzzy observer; robust fuzzy control; LMI; sector nonlinearity; nonlinear control

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

APA (6^th Edition):

Bindiganavile Nagesh, S. (. (2011). Adaptive fuzzy observer and robust controller for a 2-DOF robot arm. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:1aba8c30-3269-4cc3-b913-e3d4eb15912f

Chicago Manual of Style (16^th Edition):

Bindiganavile Nagesh, S (author). “Adaptive fuzzy observer and robust controller for a 2-DOF robot arm.” 2011. Masters Thesis, Delft University of Technology. Accessed January 20, 2021. http://resolver.tudelft.nl/uuid:1aba8c30-3269-4cc3-b913-e3d4eb15912f.

MLA Handbook (7^th Edition):

Bindiganavile Nagesh, S (author). “Adaptive fuzzy observer and robust controller for a 2-DOF robot arm.” 2011. Web. 20 Jan 2021.

Vancouver:

Bindiganavile Nagesh S(. Adaptive fuzzy observer and robust controller for a 2-DOF robot arm. [Internet] [Masters thesis]. Delft University of Technology; 2011. [cited 2021 Jan 20]. Available from: http://resolver.tudelft.nl/uuid:1aba8c30-3269-4cc3-b913-e3d4eb15912f.

Council of Science Editors:

Bindiganavile Nagesh S(. Adaptive fuzzy observer and robust controller for a 2-DOF robot arm. [Masters Thesis]. Delft University of Technology; 2011. Available from: http://resolver.tudelft.nl/uuid:1aba8c30-3269-4cc3-b913-e3d4eb15912f

Texas Tech University

15. Kreesuradej, Worapoj. Adaptive fuzzy nonlinear internal model control strategy.

Degree: Electrical and Computer Engineering, 1996, Texas Tech University

URL: http://hdl.handle.net/2346/18396

► Proportional-Integratal Derivative like Fuzzy Logic Controllers (PID-FLCs), have been used for a variety of nonlinear control problems. Basically, a PID-FLC contains a control algorithm in… (more)

Subjects/Keywords: Computational intelligence; Adaptive control systems; Nonlinear control theory; Fuzzy logic – Industrial applications

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APA (6^th Edition):

Kreesuradej, W. (1996). Adaptive fuzzy nonlinear internal model control strategy. (Thesis). Texas Tech University. Retrieved from http://hdl.handle.net/2346/18396

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):

Kreesuradej, Worapoj. “Adaptive fuzzy nonlinear internal model control strategy.” 1996. Thesis, Texas Tech University. Accessed January 20, 2021. http://hdl.handle.net/2346/18396.

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

MLA Handbook (7^th Edition):

Kreesuradej, Worapoj. “Adaptive fuzzy nonlinear internal model control strategy.” 1996. Web. 20 Jan 2021.

Vancouver:

Kreesuradej W. Adaptive fuzzy nonlinear internal model control strategy. [Internet] [Thesis]. Texas Tech University; 1996. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2346/18396.

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

Council of Science Editors:

Kreesuradej W. Adaptive fuzzy nonlinear internal model control strategy. [Thesis]. Texas Tech University; 1996. Available from: http://hdl.handle.net/2346/18396

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

University of Johannesburg

16. Mors, Winfried. 'n Wasige beheerder vir 'n elektriese hooflynlokomotief.

Degree: 2012, University of Johannesburg

URL: http://hdl.handle.net/10210/5927

►

M.Ing.

The principal reasons for the development of a prototype improved control system are the high maintenance costs and unreliability of Spoomet's fleet of class… (more)

Subjects/Keywords: Fuzzy systems; Fuzzy logic; Automatic control; Electric locomotives

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APA (6^th Edition):

Mors, W. (2012). 'n Wasige beheerder vir 'n elektriese hooflynlokomotief. (Thesis). University of Johannesburg. Retrieved from http://hdl.handle.net/10210/5927

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):

Mors, Winfried. “'n Wasige beheerder vir 'n elektriese hooflynlokomotief.” 2012. Thesis, University of Johannesburg. Accessed January 20, 2021. http://hdl.handle.net/10210/5927.

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

MLA Handbook (7^th Edition):

Mors, Winfried. “'n Wasige beheerder vir 'n elektriese hooflynlokomotief.” 2012. Web. 20 Jan 2021.

Vancouver:

Mors W. 'n Wasige beheerder vir 'n elektriese hooflynlokomotief. [Internet] [Thesis]. University of Johannesburg; 2012. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/10210/5927.

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

Council of Science Editors:

Mors W. 'n Wasige beheerder vir 'n elektriese hooflynlokomotief. [Thesis]. University of Johannesburg; 2012. Available from: http://hdl.handle.net/10210/5927

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

Universidade Nova

17. Martins, Filipe Miguel Guerreiro. eVentos 2 - Autonomous sailboat control.

Degree: 2013, Universidade Nova

URL: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/11211

►

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Sailboat navigation started as a way to explore the world. Even though… (more)

Subjects/Keywords: Autonomous sailboat; Fuzzy logic control; Fuzzy set; Rule base; Sailing; Arduino

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APA (6^th Edition):

Martins, F. M. G. (2013). eVentos 2 - Autonomous sailboat control. (Thesis). Universidade Nova. Retrieved from http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/11211

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):

Martins, Filipe Miguel Guerreiro. “eVentos 2 - Autonomous sailboat control.” 2013. Thesis, Universidade Nova. Accessed January 20, 2021. http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/11211.

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

MLA Handbook (7^th Edition):

Martins, Filipe Miguel Guerreiro. “eVentos 2 - Autonomous sailboat control.” 2013. Web. 20 Jan 2021.

Vancouver:

Martins FMG. eVentos 2 - Autonomous sailboat control. [Internet] [Thesis]. Universidade Nova; 2013. [cited 2021 Jan 20]. Available from: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/11211.

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

Council of Science Editors:

Martins FMG. eVentos 2 - Autonomous sailboat control. [Thesis]. Universidade Nova; 2013. Available from: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/11211

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

Delft University of Technology

18. Jager, R. Fuzzy Logic in Control.

Degree: 1995, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:418ca337-3518-4a0c-ba87-6117d114cf94 ; urn:NBN:nl:ui:24-uuid:418ca337-3518-4a0c-ba87-6117d114cf94 ; urn:NBN:nl:ui:24-uuid:418ca337-3518-4a0c-ba87-6117d114cf94 ; http://resolver.tudelft.nl/uuid:418ca337-3518-4a0c-ba87-6117d114cf94

Subjects/Keywords: fuzzy logic; fuzzy control

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APA (6^th Edition):

Jager, R. (1995). Fuzzy Logic in Control. (Doctoral Dissertation). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:418ca337-3518-4a0c-ba87-6117d114cf94 ; urn:NBN:nl:ui:24-uuid:418ca337-3518-4a0c-ba87-6117d114cf94 ; urn:NBN:nl:ui:24-uuid:418ca337-3518-4a0c-ba87-6117d114cf94 ; http://resolver.tudelft.nl/uuid:418ca337-3518-4a0c-ba87-6117d114cf94

Chicago Manual of Style (16^th Edition):

Jager, R. “Fuzzy Logic in Control.” 1995. Doctoral Dissertation, Delft University of Technology. Accessed January 20, 2021. http://resolver.tudelft.nl/uuid:418ca337-3518-4a0c-ba87-6117d114cf94 ; urn:NBN:nl:ui:24-uuid:418ca337-3518-4a0c-ba87-6117d114cf94 ; urn:NBN:nl:ui:24-uuid:418ca337-3518-4a0c-ba87-6117d114cf94 ; http://resolver.tudelft.nl/uuid:418ca337-3518-4a0c-ba87-6117d114cf94.

MLA Handbook (7^th Edition):

Jager, R. “Fuzzy Logic in Control.” 1995. Web. 20 Jan 2021.

Vancouver:

Jager R. Fuzzy Logic in Control. [Internet] [Doctoral dissertation]. Delft University of Technology; 1995. [cited 2021 Jan 20]. Available from: http://resolver.tudelft.nl/uuid:418ca337-3518-4a0c-ba87-6117d114cf94 ; urn:NBN:nl:ui:24-uuid:418ca337-3518-4a0c-ba87-6117d114cf94 ; urn:NBN:nl:ui:24-uuid:418ca337-3518-4a0c-ba87-6117d114cf94 ; http://resolver.tudelft.nl/uuid:418ca337-3518-4a0c-ba87-6117d114cf94.

Council of Science Editors:

Jager R. Fuzzy Logic in Control. [Doctoral Dissertation]. Delft University of Technology; 1995. Available from: http://resolver.tudelft.nl/uuid:418ca337-3518-4a0c-ba87-6117d114cf94 ; urn:NBN:nl:ui:24-uuid:418ca337-3518-4a0c-ba87-6117d114cf94 ; urn:NBN:nl:ui:24-uuid:418ca337-3518-4a0c-ba87-6117d114cf94 ; http://resolver.tudelft.nl/uuid:418ca337-3518-4a0c-ba87-6117d114cf94

Anna University

19. Muthamizhan T. Design and development of web based Embedded controller For electric drives;.

Degree: Design and development of web based Embedded controller For electric drives, 2015, Anna University

URL: http://shodhganga.inflibnet.ac.in/handle/10603/55924

►

The main objective of this research work is to design and develop a newlineweb based embedded controller for a PV powered low cost batteryless newlineelectric… (more)

Subjects/Keywords: Fuzzy Logic based Direct Torque Control; Fuzzy Logic Controller; Maximum Power Point Tracking

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APA (6^th Edition):

T, M. (2015). Design and development of web based Embedded controller For electric drives;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/55924

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):

T, Muthamizhan. “Design and development of web based Embedded controller For electric drives;.” 2015. Thesis, Anna University. Accessed January 20, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/55924.

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

MLA Handbook (7^th Edition):

T, Muthamizhan. “Design and development of web based Embedded controller For electric drives;.” 2015. Web. 20 Jan 2021.

Vancouver:

T M. Design and development of web based Embedded controller For electric drives;. [Internet] [Thesis]. Anna University; 2015. [cited 2021 Jan 20]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/55924.

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

Council of Science Editors:

T M. Design and development of web based Embedded controller For electric drives;. [Thesis]. Anna University; 2015. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/55924

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

University of Ottawa

20. Zhu, Jiayi. Adaptive Fuzzy Logic Control for Time-Delayed Bilateral Teleoperation .

Degree: 2012, University of Ottawa

URL: http://hdl.handle.net/10393/20626

► In recent years, teleoperation has shown great potentials in different fields such as spatial, mining, under-water, etc. When teleoperation is required to be bilateral, the… (more)

Subjects/Keywords: fuzzy logic; bilateral teleoperation; fuzzy logic control for medicine,; teleoperation for medicine

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APA (6^th Edition):

Zhu, J. (2012). Adaptive Fuzzy Logic Control for Time-Delayed Bilateral Teleoperation . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/20626

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):

Zhu, Jiayi. “Adaptive Fuzzy Logic Control for Time-Delayed Bilateral Teleoperation .” 2012. Thesis, University of Ottawa. Accessed January 20, 2021. http://hdl.handle.net/10393/20626.

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

MLA Handbook (7^th Edition):

Zhu, Jiayi. “Adaptive Fuzzy Logic Control for Time-Delayed Bilateral Teleoperation .” 2012. Web. 20 Jan 2021.

Vancouver:

Zhu J. Adaptive Fuzzy Logic Control for Time-Delayed Bilateral Teleoperation . [Internet] [Thesis]. University of Ottawa; 2012. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/10393/20626.

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

Council of Science Editors:

Zhu J. Adaptive Fuzzy Logic Control for Time-Delayed Bilateral Teleoperation . [Thesis]. University of Ottawa; 2012. Available from: http://hdl.handle.net/10393/20626

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

21. Palakeerthi, Ramesh. Sensorless SR drive for non linear and automotive control applications using fuzzy and ANN.

Degree: 2015, INFLIBNET

URL: http://shodhganga.inflibnet.ac.in/handle/10603/45943

► This thesis presents a sensorless controlled lowcost low power variable speed drive system suitable for automotive applications Switched Reluctance Motor is attractive to researchers because… (more)

▼ This thesis presents a sensorless controlled lowcost low power variable speed drive system suitable for automotive applications Switched Reluctance Motor is attractive to researchers because of the increased reliability robustness and cost reduction compared to conventional drives Sensorless drive is particularly useful in automotive control applications where the environment is too hostile for physical position sensors such as inside an electric vehchiles The main advantages of this drive system are the Stucture of converter is simple but robust sensorless control technique and system cost is low The drive motor is a special This work presents a new method to estimate the motor positions during startup or at and#64258;ying restart A position sensorless scheme is described which uses fuzzy modeling estimation and prediction An important feature is that saturation and real time nonideal effects are not ignored but that no mathematical model is required Instead a fuzzy logic based model is constructed from both static and real time motor data and from this model the rotor position is estimated Artificial Neural networks have established to be useful in approximating nonlinear systems and in many applications including automotive control previously NNs advocated in switched reluctancemotor control have a large number of neurons in the hiddenlayer This has impeded the in real time implementation with DSPs particularly at high rotational speeds because of the large number of operations required by the ANN controller within a sampling interval One of the ideal applications of NNs in SRM control is in rotor position estimation using only current or voltage signals The non linear control of the fast scale period doubling bifurcation in the SRM drive by the alteration of the Saltation matrix component of the Monodromy matrix is discussed Three stabilization options based on Saltation matrix manipulation were explored and the results of the control action confirmed the effectiveness of these stabilization techniques The system also incorporates Nuero Fuzzy based methods to provide a high robustness It is shown that by using ANFIS the estimation scheme offers a high robustness and reliability and is thus well suited to a wide range of control applications The algorithm is and#64257;rst simulated through MATLAB SIMULINK and then tested The Experimental veriand#64257;cation of this motor drive system is provided to demonstrate the viability of the proposed approach for the development of robustness reliability and low cost motor drives Advisors/Committee Members: Subbaiah, P.

Subjects/Keywords: Motor drives Fuzzy logic Artificial Neural Networks Adaptive Neuro Fuzzy Interface System Switched Reluctance Motor

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

APA (6^th Edition):

Palakeerthi, R. (2015). Sensorless SR drive for non linear and automotive control applications using fuzzy and ANN. (Thesis). INFLIBNET. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/45943

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):

Palakeerthi, Ramesh. “Sensorless SR drive for non linear and automotive control applications using fuzzy and ANN.” 2015. Thesis, INFLIBNET. Accessed January 20, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/45943.

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

MLA Handbook (7^th Edition):

Palakeerthi, Ramesh. “Sensorless SR drive for non linear and automotive control applications using fuzzy and ANN.” 2015. Web. 20 Jan 2021.

Vancouver:

Palakeerthi R. Sensorless SR drive for non linear and automotive control applications using fuzzy and ANN. [Internet] [Thesis]. INFLIBNET; 2015. [cited 2021 Jan 20]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/45943.

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

Council of Science Editors:

Palakeerthi R. Sensorless SR drive for non linear and automotive control applications using fuzzy and ANN. [Thesis]. INFLIBNET; 2015. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/45943

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

Brunel University

22. Shekarriz, Mona. The foundation of capability modelling : a study of the impact and utilisation of human resources.

Degree: PhD, 2011, Brunel University

URL: http://bura.brunel.ac.uk/handle/2438/5257 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.535948

► This research aims at finding a foundation for assessment of capabilities and applying the concept in a human resource selection. The research identifies a common… (more)

▼ This research aims at finding a foundation for assessment of capabilities and applying the concept in a human resource selection. The research identifies a common ground for assessing individuals’ applied capability in a given job based on literature review of various disciplines in engineering, human sciences and economics. A set of criteria is found to be common and appropriate to be used as the basis of this assessment. Applied Capability is then described in this research as the impact of the person in fulfilling job requirements and also their level of usage from their resources with regards to the identified criteria. In other words how their available resources (abilities, skills, value sets, personal attributes and previous performance records) can be used in completing a job. Translation of the person’s resources and task requirements using the proposed criteria is done through a novel algorithm and two prevalent statistical inference techniques (OLS regression and Fuzzy) are used to estimate quantitative levels of impact and utilisation. A survey on post graduate students is conducted to estimate their applied capabilities in a given job. Moreover, expert academics are surveyed on their views on key applied capability assessment criteria, and how different levels of match between job requirement and person’s resources in those criteria might affect the impact levels. The results from both surveys were mathematically modelled and the predictive ability of the conceptual and mathematical developments were compared and further contrasted with the observed data. The models were tested for robustness using experimental data and the results for both estimation methods in both surveys are close to one another with the regression models being closer to observations. It is believed that this research has provided sound conceptual and mathematical platforms which can satisfactorily predict individuals’ applied capability in a given job. This research has contributed to the current knowledge and practice by a) providing a comparison of capability definitions and uses in different disciplines, b) defining criteria for applied capability assessment, c) developing an algorithm to capture applied capabilities, d) quantification of an existing parallel model and finally e) estimating impact and utilisation indices using mathematical methods.

Subjects/Keywords: 331.2; Capability theory; Person-environment fit; Job evaluation; Adaptive neuro fuzzy inference system; Fuzzy logic

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

APA (6^th Edition):

Shekarriz, M. (2011). The foundation of capability modelling : a study of the impact and utilisation of human resources. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/5257 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.535948

Chicago Manual of Style (16^th Edition):

Shekarriz, Mona. “The foundation of capability modelling : a study of the impact and utilisation of human resources.” 2011. Doctoral Dissertation, Brunel University. Accessed January 20, 2021. http://bura.brunel.ac.uk/handle/2438/5257 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.535948.

MLA Handbook (7^th Edition):

Shekarriz, Mona. “The foundation of capability modelling : a study of the impact and utilisation of human resources.” 2011. Web. 20 Jan 2021.

Vancouver:

Shekarriz M. The foundation of capability modelling : a study of the impact and utilisation of human resources. [Internet] [Doctoral dissertation]. Brunel University; 2011. [cited 2021 Jan 20]. Available from: http://bura.brunel.ac.uk/handle/2438/5257 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.535948.

Council of Science Editors:

Shekarriz M. The foundation of capability modelling : a study of the impact and utilisation of human resources. [Doctoral Dissertation]. Brunel University; 2011. Available from: http://bura.brunel.ac.uk/handle/2438/5257 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.535948

New Jersey Institute of Technology

23. Chang, Shu-Chieh. Adaptive nonlinear control using fuzzy logic and neural networks.

Degree: PhD, Mechanical and Industrial Engineering, 1994, New Jersey Institute of Technology

URL: https://digitalcommons.njit.edu/dissertations/1083

► The problem of adaptive nonlinear control, i.e. the control of nonlinear dynamic systems with unknown parameters, is considered. Current techniques usually assume that either… (more)

Subjects/Keywords: Adaptive control systems.; Neural networks (Computer science); Fuzzy logic.; Mechanical Engineering

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APA (6^th Edition):

Chang, S. (1994). Adaptive nonlinear control using fuzzy logic and neural networks. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/1083

Chicago Manual of Style (16^th Edition):

Chang, Shu-Chieh. “Adaptive nonlinear control using fuzzy logic and neural networks.” 1994. Doctoral Dissertation, New Jersey Institute of Technology. Accessed January 20, 2021. https://digitalcommons.njit.edu/dissertations/1083.

MLA Handbook (7^th Edition):

Chang, Shu-Chieh. “Adaptive nonlinear control using fuzzy logic and neural networks.” 1994. Web. 20 Jan 2021.

Vancouver:

Chang S. Adaptive nonlinear control using fuzzy logic and neural networks. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 1994. [cited 2021 Jan 20]. Available from: https://digitalcommons.njit.edu/dissertations/1083.

Council of Science Editors:

Chang S. Adaptive nonlinear control using fuzzy logic and neural networks. [Doctoral Dissertation]. New Jersey Institute of Technology; 1994. Available from: https://digitalcommons.njit.edu/dissertations/1083

24. CHEN XUETAO. Adaptive Interval Type-2 Fuzzy Logic Control of Marine Vessels.

Degree: 2012, National University of Singapore

URL: http://scholarbank.nus.edu.sg/handle/10635/36571

Subjects/Keywords: adaptive fuzzy control; interval type-2 fuzzy logic system; marine vessel control; function approximation; dynamic positioning; tracking control

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APA (6^th Edition):

XUETAO, C. (2012). Adaptive Interval Type-2 Fuzzy Logic Control of Marine Vessels. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/36571

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):

XUETAO, CHEN. “Adaptive Interval Type-2 Fuzzy Logic Control of Marine Vessels.” 2012. Thesis, National University of Singapore. Accessed January 20, 2021. http://scholarbank.nus.edu.sg/handle/10635/36571.

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

MLA Handbook (7^th Edition):

XUETAO, CHEN. “Adaptive Interval Type-2 Fuzzy Logic Control of Marine Vessels.” 2012. Web. 20 Jan 2021.

Vancouver:

XUETAO C. Adaptive Interval Type-2 Fuzzy Logic Control of Marine Vessels. [Internet] [Thesis]. National University of Singapore; 2012. [cited 2021 Jan 20]. Available from: http://scholarbank.nus.edu.sg/handle/10635/36571.

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

Council of Science Editors:

XUETAO C. Adaptive Interval Type-2 Fuzzy Logic Control of Marine Vessels. [Thesis]. National University of Singapore; 2012. Available from: http://scholarbank.nus.edu.sg/handle/10635/36571

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

Clemson University

25. Pandit, Chinmay. A Model-free Approach to Vehicle Stability Control.

Degree: MS, Mechanical Engineering, 2013, Clemson University

URL: https://tigerprints.clemson.edu/all_theses/1637

► This project explored the feasibility of using measured responses of a passenger car together with a fuzzy logic based control algorithm to sense the… (more)

▼ This project explored the feasibility of using measured responses of a passenger car together with a fuzzy logic based control algorithm to sense the onset of under-steer (or loss of steering control) and mitigate or eliminate it. The controller is simple and robust and, unlike existing controllers, instead of comparing the vehicle response to that of an idealized model it makes decisions based solely upon the measured response of the car. Simulations were conducted (using CarSim) of various vehicles executing the skid pad and the double lane change tests to characterize the vehicle behavior. Consistent and qualitatively similar patterns in vehicle response during the inception of and at limit under-steer were observed. A fuzzy logic routine was developed that analyzes real-time measurements of steering wheel angle (SWA) and lateral acceleration (A_y). Based on the relative `trends' of the signals, the control algorithm decides upon the presence and extent of under-steer in the vehicle. The degree of under-steer then defines the corrective action. The fundamental concept is to measure a drop in the instantaneous lateral acceleration gain, i.e., A_y/SWA, indicating a lack of response. It is quantified as a normalized error and transformed into an under-steer number between 0 and 10 using a pair of fuzzy inference systems. Once incipient under-steer is detected, the brakes and engine throttle are managed to limit the lateral deviation from the travel lane. The controller also senses vehicle velocity, master cylinder brake pressure and normalized throttle input to improve controllability. This approach eliminates the need for either a simple or a complex vehicle model and the associated dependence on the model parameters. Controller performance was validated using a braking-in-turn maneuver developed by the author and the standard double lane change maneuver. The results have shown clear improvement in the tracking ability of a vehicle. The simulations were conducted at different speeds with each of several vehicles and with different tire-to-ground friction values without any changes to the control algorithm. This has shown that the controller is robust across different conditions. The controller is successful in increasing the maximum safe speed for a negotiating a curve for all vehicles on various road conditions. The last part of the controller was to combine it with an existing over-steer controller, developed at Clemson University, which also uses fuzzy logic. This was successfully completed to obtain a fully functional ESC system, independent of a vehicle model. Future work will include tuning the controller based on track data from real vehicles. Advisors/Committee Members: Law, E. Harry, Wagner , John R, Ayalew , Beshah.

Subjects/Keywords: Electronic Stability Control; Fuzzy Logic; Robust Control; Mechanical Engineering

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APA (6^th Edition):

Pandit, C. (2013). A Model-free Approach to Vehicle Stability Control. (Masters Thesis). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_theses/1637

Chicago Manual of Style (16^th Edition):

Pandit, Chinmay. “A Model-free Approach to Vehicle Stability Control.” 2013. Masters Thesis, Clemson University. Accessed January 20, 2021. https://tigerprints.clemson.edu/all_theses/1637.

MLA Handbook (7^th Edition):

Pandit, Chinmay. “A Model-free Approach to Vehicle Stability Control.” 2013. Web. 20 Jan 2021.

Vancouver:

Pandit C. A Model-free Approach to Vehicle Stability Control. [Internet] [Masters thesis]. Clemson University; 2013. [cited 2021 Jan 20]. Available from: https://tigerprints.clemson.edu/all_theses/1637.

Council of Science Editors:

Pandit C. A Model-free Approach to Vehicle Stability Control. [Masters Thesis]. Clemson University; 2013. Available from: https://tigerprints.clemson.edu/all_theses/1637

Baylor University

26. Opado, Frederick Odhiambo, 1987-. Governor control optimization of hydro power plants using hybrid fuzzy logic and PID control.

Degree: M.S.E.C.E., Baylor University. Dept. of Electrical & Computer Engineering., 2017, Baylor University

URL: http://hdl.handle.net/2104/10150

► Control of hydro power plants has been an issue of concern for researchers; moreover, more emphasis has always been put on governor control which naturally… (more)

Subjects/Keywords: Fuzzy logic.

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APA (6^th Edition):

Opado, Frederick Odhiambo, 1. (2017). Governor control optimization of hydro power plants using hybrid fuzzy logic and PID control. (Masters Thesis). Baylor University. Retrieved from http://hdl.handle.net/2104/10150

Chicago Manual of Style (16^th Edition):

Opado, Frederick Odhiambo, 1987-. “Governor control optimization of hydro power plants using hybrid fuzzy logic and PID control.” 2017. Masters Thesis, Baylor University. Accessed January 20, 2021. http://hdl.handle.net/2104/10150.

MLA Handbook (7^th Edition):

Opado, Frederick Odhiambo, 1987-. “Governor control optimization of hydro power plants using hybrid fuzzy logic and PID control.” 2017. Web. 20 Jan 2021.

Vancouver:

Opado, Frederick Odhiambo 1. Governor control optimization of hydro power plants using hybrid fuzzy logic and PID control. [Internet] [Masters thesis]. Baylor University; 2017. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2104/10150.

Council of Science Editors:

Opado, Frederick Odhiambo 1. Governor control optimization of hydro power plants using hybrid fuzzy logic and PID control. [Masters Thesis]. Baylor University; 2017. Available from: http://hdl.handle.net/2104/10150

Pontifical Catholic University of Rio de Janeiro

27. CRISTHIAN JULIAN GOMEZ LIZCANO. [en] FUZZY CONTROL OF AN AUXILIARY NAVIGATION SYSTEM FOR A HYBRID AMBIENT ROBOT.

Degree: 2016, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=26406

►

[pt] Nas últimas décadas o avanço tecnológico tem atingido altos níveis de desenvolvimento, sendo as técnicas de inteligência computacional um dos principais campos em expansão… (more)

▼

[pt] Nas últimas décadas o avanço tecnológico tem atingido altos níveis de desenvolvimento, sendo as técnicas de inteligência computacional um dos principais campos em expansão devido à sua aplicabilidade nas diferentes áreas industriais. Uma das principais técnicas com aplicabilidade no setor da robótica é a Lógica Fuzzy, que permite aumentar as características de autonomia dos robôs. Atualmente a indústria brasileira vem desenvolvendo novos métodos robotizados para as tarefas de monitoramento e inspeção de gasodutos. No caso particular do gasoduto Coari-Manaus, foi desenvolvido o Robô Ambiental Híbrido Médio (RAHM), o qual possui um Sistema Primário de Navegação (SPN), mas não um Sistema Auxiliar de Navegação (SAN) para uso em caso de falha. Este trabalho tem como principal objetivo desenvolver um Sistema de Navegação Auxiliar controlado através da Lógica Fuzzy, de forma a auxiliar a navegação autônoma do robô em case de falha do SPN. O trabalho envolveu o projeto da eletrônica e de um sistema de inferência fuzzy para oferecer um controle adequado na navegação do robô em casos de emergência. O SAN é avaliado através de um estudo de caso comparativo, confirmando os benefícios que a Lógica Fuzzy oferece para o Sistema Auxiliar de Navegação.

[en] Technological progress has reached high levels of development in the last decades and computational intelligence techniques have been one of the main expanding fields due to their applicability in different industrial areas. One of those techniques that can be used in the field of robotics is Fuzzy Logic, which contributes to an increase in the autonomy of robots. Brazilian industry has been developing new robotics methods for monitoring and inspection tasks of pipelines. In the particular case of Coari-Manaus pipeline the Environmental Hybrid Medium Robot (RAHM) has been developed. This robot has a primary navigation system (PNS), but lacks an Auxiliary Navigation System (ANS) to be used in the case of failure. This dissertation has as its main objective developing an Auxiliary Navigation System controlled through Fuzzy Logic to help autonomous navigation in the case of the PNS failure. The work has involoved the electronic project and the design of a fuzzy inference system for an adequate control of the robot navigation of Robot in an emergency. The ANS is evaluated through a comparative case study and results confirm the benefits from using Fuzzy Logic in the design of the Auxiliary Navigation System.

Advisors/Committee Members: MARLEY MARIA BERNARDES REBUZZI VELLASCO.

Subjects/Keywords: [pt] LOGICA FUZZY; [en] FUZZY LOGIC; [pt] NAVEGACAO; [en] NAVIGATION; [pt] ROBOTICA; [en] ROBOTICS; [pt] CONTROLE FUZZY; [en] FUZZY CONTROL

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APA (6^th Edition):

LIZCANO, C. J. G. (2016). [en] FUZZY CONTROL OF AN AUXILIARY NAVIGATION SYSTEM FOR A HYBRID AMBIENT ROBOT. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=26406

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):

LIZCANO, CRISTHIAN JULIAN GOMEZ. “[en] FUZZY CONTROL OF AN AUXILIARY NAVIGATION SYSTEM FOR A HYBRID AMBIENT ROBOT.” 2016. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 20, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=26406.

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

MLA Handbook (7^th Edition):

LIZCANO, CRISTHIAN JULIAN GOMEZ. “[en] FUZZY CONTROL OF AN AUXILIARY NAVIGATION SYSTEM FOR A HYBRID AMBIENT ROBOT.” 2016. Web. 20 Jan 2021.

Vancouver:

LIZCANO CJG. [en] FUZZY CONTROL OF AN AUXILIARY NAVIGATION SYSTEM FOR A HYBRID AMBIENT ROBOT. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2016. [cited 2021 Jan 20]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=26406.

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

Council of Science Editors:

LIZCANO CJG. [en] FUZZY CONTROL OF AN AUXILIARY NAVIGATION SYSTEM FOR A HYBRID AMBIENT ROBOT. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2016. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=26406

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

28. Sattar, Muhammad Awais. Adaptive Fuzzy Control of Quadrotor.

Degree: MS, 2017, Rochester Institute of Technology

URL: https://scholarworks.rit.edu/theses/9618

► In this thesis, intelligent controllers are designed to control attitude for quadrotor UAV (Unmanned Aerial Vehicle).Quadrotors have a variety of applications in real time… (more)

Subjects/Keywords: Adaptive fuzzy PD; Dynamics; Fuzzy logic control; PD control; Roll pitch yaw; UAV

…controller design techniques 1. PD Control 2. Fuzzy logic Control 3. Adaptive Fuzzy PD Control… …36 Chapter 4 Fuzzy Logic Control of Quadrotor… …47 Chapter 5 Adaptive Fuzzy PD Control of Quadrotor… …50 5.2 Adaptive Fuzzy PD Control… …69 B.2 Block Diagrams with Fuzzy Logic Control…

12 more images…

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

APA (6^th Edition):

Sattar, M. A. (2017). Adaptive Fuzzy Control of Quadrotor. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9618

Chicago Manual of Style (16^th Edition):

Sattar, Muhammad Awais. “Adaptive Fuzzy Control of Quadrotor.” 2017. Masters Thesis, Rochester Institute of Technology. Accessed January 20, 2021. https://scholarworks.rit.edu/theses/9618.

MLA Handbook (7^th Edition):

Sattar, Muhammad Awais. “Adaptive Fuzzy Control of Quadrotor.” 2017. Web. 20 Jan 2021.

Vancouver:

Sattar MA. Adaptive Fuzzy Control of Quadrotor. [Internet] [Masters thesis]. Rochester Institute of Technology; 2017. [cited 2021 Jan 20]. Available from: https://scholarworks.rit.edu/theses/9618.

Council of Science Editors:

Sattar MA. Adaptive Fuzzy Control of Quadrotor. [Masters Thesis]. Rochester Institute of Technology; 2017. Available from: https://scholarworks.rit.edu/theses/9618

29. Severo, Rosane Beatriz Oliveira. Identificação de planta medicinal baseada em espectrocospia e lógica fuzzy.

Degree: PhD, Sistemas Eletrônicos, 2009, University of São Paulo

URL: http://www.teses.usp.br/teses/disponiveis/3/3142/tde-11082010-165539/ ;

►

A presente tese de doutorado discorre sobre o método da espectroscopia na região do Infravermelho Próximo, usando Transformada de Fourier (IVP-TF), aplicada à identificação de… (more)

Subjects/Keywords: Espectroscopia; Fitoterapia (controle de qualidade); Fuzzy logic; Lógica fuzzy; Quality control of herbal medicines; Spectrocospy

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APA (6^th Edition):

Severo, R. B. O. (2009). Identificação de planta medicinal baseada em espectrocospia e lógica fuzzy. (Doctoral Dissertation). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/3/3142/tde-11082010-165539/ ;

Chicago Manual of Style (16^th Edition):

Severo, Rosane Beatriz Oliveira. “Identificação de planta medicinal baseada em espectrocospia e lógica fuzzy.” 2009. Doctoral Dissertation, University of São Paulo. Accessed January 20, 2021. http://www.teses.usp.br/teses/disponiveis/3/3142/tde-11082010-165539/ ;.

MLA Handbook (7^th Edition):

Severo, Rosane Beatriz Oliveira. “Identificação de planta medicinal baseada em espectrocospia e lógica fuzzy.” 2009. Web. 20 Jan 2021.

Vancouver:

Severo RBO. Identificação de planta medicinal baseada em espectrocospia e lógica fuzzy. [Internet] [Doctoral dissertation]. University of São Paulo; 2009. [cited 2021 Jan 20]. Available from: http://www.teses.usp.br/teses/disponiveis/3/3142/tde-11082010-165539/ ;.

Council of Science Editors:

Severo RBO. Identificação de planta medicinal baseada em espectrocospia e lógica fuzzy. [Doctoral Dissertation]. University of São Paulo; 2009. Available from: http://www.teses.usp.br/teses/disponiveis/3/3142/tde-11082010-165539/ ;

Universidade do Rio Grande do Norte

30. Costa, Bruno Sielly Jales. Ambiente para desenvolvimento de aplicações fuzzy industriais .

Degree: 2009, Universidade do Rio Grande do Norte

URL: http://repositorio.ufrn.br/handle/123456789/15307

► This paper describes the design, implementation and enforcement of a system for industrial process control based on fuzzy logic and developed using Java, with support… (more)

Subjects/Keywords: Lógica fuzzy; autimação industrial; controle de processos; OPC; Fuzzy logic; industrial automation; process control; OPC

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APA (6^th Edition):

Costa, B. S. J. (2009). Ambiente para desenvolvimento de aplicações fuzzy industriais . (Thesis). Universidade do Rio Grande do Norte. Retrieved from http://repositorio.ufrn.br/handle/123456789/15307

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):

Costa, Bruno Sielly Jales. “Ambiente para desenvolvimento de aplicações fuzzy industriais .” 2009. Thesis, Universidade do Rio Grande do Norte. Accessed January 20, 2021. http://repositorio.ufrn.br/handle/123456789/15307.

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

MLA Handbook (7^th Edition):

Costa, Bruno Sielly Jales. “Ambiente para desenvolvimento de aplicações fuzzy industriais .” 2009. Web. 20 Jan 2021.

Vancouver:

Costa BSJ. Ambiente para desenvolvimento de aplicações fuzzy industriais . [Internet] [Thesis]. Universidade do Rio Grande do Norte; 2009. [cited 2021 Jan 20]. Available from: http://repositorio.ufrn.br/handle/123456789/15307.

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

Council of Science Editors:

Costa BSJ. Ambiente para desenvolvimento de aplicações fuzzy industriais . [Thesis]. Universidade do Rio Grande do Norte; 2009. Available from: http://repositorio.ufrn.br/handle/123456789/15307

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

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Open Access Theses and Dissertations