+publisher:"Colorado State University" +contributor:("Chong, Edwin Kah Pin")

Colorado State University

1. Buehner, Michael R. Perfect tracking for non-minimum phase systems with applications to biofuels from microalgae.

Degree: PhD, Electrical and Computer Engineering, 2010, Colorado State University

► In a causal setting, a closed-loop control system receives reference inputs (with no a priori knowledge) that it must track. For this setting, controllers are… (more)

▼ In a causal setting, a closed-loop control system receives reference inputs (with no a priori knowledge) that it must track. For this setting, controllers are designed that provide both stability and performance (e.g., to meet tracking and disturbance rejection requirements). Often, feedback controllers are designed to satisfy weighted optimization criteria (e.g., weighted tracking error) that are later validated using test signals such as step responses and frequency sweeps. Feedforward controllers may be used to improve the response to measurable external disturbances (e.g., reference inputs). In this way, they can improve the closed-loop response; however, these approaches do not directly specify the closed-loop response. Two controller architectures are developed that allow for directly designing the nominal closed-loop response of non-minimum phase systems. These architectures classify both the signals that may be perfectly tracked by a non-minimum phase plant and the control signals that provide this perfect tracking. For these architectures, perfect tracking means that the feedback error is zero (for all time) in the nominal case (i.e., the plant model is exact) when there are no external disturbances. For the controllers presented here, parts of the feedforward controllers are based on the plant model, while a separate piece is designed to provide the desired level of performance. One of the potential limitations to these designs is that the actual performance will depend upon the quality of the model used. Robustness tools are developed that may be used to determine the expected performance for a given level of model uncertainty. These robustness tools may also be used to design the piece of the feedforward controller that provides performance. There is a tradeoff between model uncertainty and achievable performance. In general, more model uncertainty will result in less achievable performance. Another way to approach the issue of performance is to consider that a good model must either be known a priori or learned via adaptation. In the cases where a good model is difficult to determine a priori, adaptation may be used to improve the models in the feedforward controllers, which will, in turn, improve the performance of the overall control system. We show how adaptive feedforward architectures can improve performance for systems where the model is of limited accuracy. An example application of growing microalgae for biofuel production is presented. Microalgae have the potential to produce enough biofuels to meet the current US fuel demands; however, progress has been limited (in some part) due to a lack of appropriate models and controllers. In the work presented here, models are developed that may be used to monitor the productivity of microalgae inside a photobioreactor and to develop control algorithms. We use experimental data from a functional prototype photobioreactor to validate these models and to demonstrate the advantages of the advanced controller architectures developed here. Advisors/Committee Members: Young, Peter M. (advisor), Chong, Edwin Kah Pin (committee member), Scharf, Louis L. (committee member), Anderson, Charles W. (committee member).

Subjects/Keywords: robust; microalgae; feedforward; control systems; biofuels; adaptive; Adaptive control systems; Feedforward control systems; Biomass energy; Microalgae – Biotechnology

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APA (6^th Edition):

Buehner, M. R. (2010). Perfect tracking for non-minimum phase systems with applications to biofuels from microalgae. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/39322

Chicago Manual of Style (16^th Edition):

Buehner, Michael R. “Perfect tracking for non-minimum phase systems with applications to biofuels from microalgae.” 2010. Doctoral Dissertation, Colorado State University. Accessed February 28, 2021. http://hdl.handle.net/10217/39322.

MLA Handbook (7^th Edition):

Buehner, Michael R. “Perfect tracking for non-minimum phase systems with applications to biofuels from microalgae.” 2010. Web. 28 Feb 2021.

Vancouver:

Buehner MR. Perfect tracking for non-minimum phase systems with applications to biofuels from microalgae. [Internet] [Doctoral dissertation]. Colorado State University; 2010. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/10217/39322.

Council of Science Editors:

Buehner MR. Perfect tracking for non-minimum phase systems with applications to biofuels from microalgae. [Doctoral Dissertation]. Colorado State University; 2010. Available from: http://hdl.handle.net/10217/39322

Colorado State University

2. Wandler, Damian V. Fiducial approach to extremes and multiple comparisons, A.

Degree: PhD, Statistics, 2010, Colorado State University

URL: http://hdl.handle.net/10217/39056

► Generalized fiducial inference is a powerful tool for many difficult problems. Based on an extension of R. A. Fisher's work, we used generalized fiducial inference… (more)

Subjects/Keywords: extreme values; multiple comparisons; fiducial inference; Mathematical statistics; Extreme value theory; Distribution (Probability theory)

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APA (6^th Edition):

Wandler, D. V. (2010). Fiducial approach to extremes and multiple comparisons, A. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/39056

Chicago Manual of Style (16^th Edition):

Wandler, Damian V. “Fiducial approach to extremes and multiple comparisons, A.” 2010. Doctoral Dissertation, Colorado State University. Accessed February 28, 2021. http://hdl.handle.net/10217/39056.

MLA Handbook (7^th Edition):

Wandler, Damian V. “Fiducial approach to extremes and multiple comparisons, A.” 2010. Web. 28 Feb 2021.

Vancouver:

Wandler DV. Fiducial approach to extremes and multiple comparisons, A. [Internet] [Doctoral dissertation]. Colorado State University; 2010. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/10217/39056.

Council of Science Editors:

Wandler DV. Fiducial approach to extremes and multiple comparisons, A. [Doctoral Dissertation]. Colorado State University; 2010. Available from: http://hdl.handle.net/10217/39056

Colorado State University

3. Watson, Jean-Paul. Empirical modeling and analysis of local search algorithms for the job-shop scheduling problem.

Degree: PhD, Computer Science, 2003, Colorado State University

URL: http://hdl.handle.net/10217/26811

► Local search algorithms are among the most effective approaches for locating high-quality solutions to a wide range of combinatorial optimization problems. However, our theoretical understanding… (more)

▼ Local search algorithms are among the most effective approaches for locating high-quality solutions to a wide range of combinatorial optimization problems. However, our theoretical understanding of these algorithms is very limited, leading to significant problems for both researchers and practitioners. Specifically, the lack of a theory of local search impedes the development of more effective algorithms, prevents practitioners from identifying the algorithm most appropriate for a given problem, and allows widespread conjecture and misinformation regarding the benefits and/or drawbacks of particular algorithms. This thesis represents a significant step toward a theory of local search. Using empirical methods, we develop theoretical models of the behavior of four well-known local search algorithms: a random walk, tabu search, iterated local search, and simulated annealing. The analysis proceeds in the context of the well-known job-shop scheduling problem, one of the most difficult NP-hard problems encountered in practice. The large volume of prior research on the job-shop scheduling problem provides a diverse range of available algorithms and problem instances, in addition to numerous empirical observations regarding local search algorithm behavior; the latter are used to validate our behavioral models. We show that all four local search algorithms can be modeled with high fidelity using straightforward variations of a generalized one-dimensional Markov chain. The states in these models represent sets of solutions a given fixed distance from the nearest optimal solution. The transition probabilities in all of the models are remarkably similar, in that search is consistently biased toward solutions that are roughly equidistant from the nearest optimal solution and solutions that are maximally distant from the nearest optimal solution. Surprisingly, the qualitative form of the transition probabilities is simply due to the structure of the representation used to encode solutions: the binary hypercube. The models account for between 96% and 99% of the variability in the cost required to locate both optimal and sub-optimal solutions to a wide range of problem instances, and provide explanations for numerous phenomena related to problem difficulty for local search in the job-shop scheduling problem. In the course of our analysis, we also disprove many conjectures regarding the behavior and benefits of particular algorithms. Our research indicates that despite their effectiveness, local search algorithms for the job-shop scheduling problem exhibit surprisingly simple run-time dynamics. Further, we observe minimal differences between the dynamical behavior of different algorithms. As expected given similar run-time dynamics, although contrary to numerous reports appearing in the literature, we also show that the performance of different algorithms is largely indistinguishable. Ultimately, our behavioral models serve to unify and provide explanations for a large body of observations regarding problem difficulty for local… Advisors/Committee Members: Howe, Adele E. (advisor), Whitley, L. Darrell (advisor), Chong, Edwin Kah Pin (committee member), Bohm, Anton Willem (committee member).

Subjects/Keywords: random walk; tabu search; job-shop scheduling problem; empirical methods; local search algorithms; iterated local search; simulated annealing; Production scheduling – Computer simulation

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

APA (6^th Edition):

Watson, J. (2003). Empirical modeling and analysis of local search algorithms for the job-shop scheduling problem. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/26811

Chicago Manual of Style (16^th Edition):

Watson, Jean-Paul. “Empirical modeling and analysis of local search algorithms for the job-shop scheduling problem.” 2003. Doctoral Dissertation, Colorado State University. Accessed February 28, 2021. http://hdl.handle.net/10217/26811.

MLA Handbook (7^th Edition):

Watson, Jean-Paul. “Empirical modeling and analysis of local search algorithms for the job-shop scheduling problem.” 2003. Web. 28 Feb 2021.

Vancouver:

Watson J. Empirical modeling and analysis of local search algorithms for the job-shop scheduling problem. [Internet] [Doctoral dissertation]. Colorado State University; 2003. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/10217/26811.

Council of Science Editors:

Watson J. Empirical modeling and analysis of local search algorithms for the job-shop scheduling problem. [Doctoral Dissertation]. Colorado State University; 2003. Available from: http://hdl.handle.net/10217/26811

Colorado State University

4. Kim, DaeGon. Parameterized and multi-level tiled loop generation.

Degree: PhD, Computer Science, 2010, Colorado State University

URL: http://hdl.handle.net/10217/39103

► Tiling is a loop transformation that decomposes computations into a set of smaller computation blocks. The transformation has been proven to be useful for many… (more)

▼ Tiling is a loop transformation that decomposes computations into a set of smaller computation blocks. The transformation has been proven to be useful for many high-level program optimizations, such as data locality optimization and exploiting coarse-grained parallelism, and crucial for architecture with limited resources, such as embedded systems, GPUs, and the Cell architecture. Data locality and parallelism will continue to serve as major vehicles for achieving high performance on modern architecture in multi-core era. In parameterized tiling the size of blocks is not fixed at compile time but remains a symbolic constant so that it can be selected/changed even at runtime. Parameterized tiled loops facilitate iterative and runtime optimizations, such as iterative compilation, auto-tuning and dynamic program adaption. In this dissertation we present a collection of techniques for generating parameterized and multi-level tiled loops from affine control loops and their parallelization. The tiled loop generation problem even for perfectly nested loops has been believed to have an exponential time complexity due to the heavy machinery like Fourier-Motzkin elimination. Disproving this decade-long belief, we provide a simple technique for generating tiled loop nests even from imperfectly nested loops. Our technique for perfectly nested loops consists of only syntactic processing that is applied only once and independently to each loop bound. Our approach to imperfectly nested loops is composed of a direct extension of the tiled code generation technique for perfectly nested loops and three simple optimizations on the resulting parameterized tiled loops. The generation as well as the optimizations are achieved only with purely syntactic processing, hence loop generation time remains negligible. We also present three schemes for multi-level tiling where tiling is applied more than once. All the schemes are scalable with respect to the number of tiling levels and can be combined to achieve better performance. To facilitate parallelization of parameterized tiled loops, we generate outermost tile-loops that are perfectly nested. We also provide a technique for statically restructuring parameterized tiled loops to the wavefront scheduling on shared memory system. Because the formulation of parameterized tiling does not fit into the well established polyhedral framework, such static restructuring has been a great challenge. However, we achieve this limited restructuring through a syntactic processing without any sophisticated machinery. Advisors/Committee Members: Rajopadhye, Sanjay Vishnu (advisor), Böhm, Anton Pedro Willem, 1948- (committee member), Chong, Edwin Kah Pin (committee member), Strout, Michelle Mills, 1974- (committee member).

Subjects/Keywords: tiling; polyhedral model; parallelization; optimization; compiler; code generation; Loop tiling (Computer science); Compilers (Computer programs); Loops (Group theory); Parallel processing (Electronic computers)

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

APA (6^th Edition):

Kim, D. (2010). Parameterized and multi-level tiled loop generation. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/39103

Chicago Manual of Style (16^th Edition):

Kim, DaeGon. “Parameterized and multi-level tiled loop generation.” 2010. Doctoral Dissertation, Colorado State University. Accessed February 28, 2021. http://hdl.handle.net/10217/39103.

MLA Handbook (7^th Edition):

Kim, DaeGon. “Parameterized and multi-level tiled loop generation.” 2010. Web. 28 Feb 2021.

Vancouver:

Kim D. Parameterized and multi-level tiled loop generation. [Internet] [Doctoral dissertation]. Colorado State University; 2010. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/10217/39103.

Council of Science Editors:

Kim D. Parameterized and multi-level tiled loop generation. [Doctoral Dissertation]. Colorado State University; 2010. Available from: http://hdl.handle.net/10217/39103

Colorado State University

5. Gupta, Gautam. Some advances in the polyhedral model.

Degree: PhD, Computer Science, 2010, Colorado State University

URL: http://hdl.handle.net/10217/40288

► The polyhedral model is a mathematical formalism and a framework for the analysis and transformation of regular computations. It provides a unified approach to the… (more)

▼ The polyhedral model is a mathematical formalism and a framework for the analysis and transformation of regular computations. It provides a unified approach to the optimization of computations from different application domains. It is now gaining wide use in optimizing compilers and automatic parallelization. In its purest form, it is based on a declarative model where computations are specified as equations over domains defined by "polyhedral sets". This dissertation presents two results. First is an analysis and optimization technique that enables us to simplify – reduce the asymptotic complexity – of such equations. The second is an extension of the model to richer domains called Ƶ-Polyhedra. Many equational specifications in the polyhedral model have reductions – application of an associative and commutative operator to collections of values to produce a collection of answers. Moreover, expressions in such equations may also exhibit reuse where intermediate values that are computed or used at different index points are identical. We develop various compiler transformations to automatically exploit this reuse and simplify the computational complexity of the specification. In general, there is an infinite set of applicable simplification transformations. Unfortunately, different choices may result in equivalent specifications with different asymptotic complexity. We present an algorithm for the optimal application of simplification transformations resulting in a final specification with minimum complexity. This dissertation also presents the Ƶ-Polyhedral model, an extension to the polyhedral model to more general sets, thereby providing a transformation framework for a larger set of regular computations. For this, we present a novel representation and interpretation of Ƶ-Polyhedra and prove a number of properties of the family of unions of Ƶ-Polyhedra that are required to extend the polyhedral model. Finally, we present value based dependence analysis and scheduling analysis for specifications in the Ƶ-Polyhedral model. These are direct extensions of the corresponding analyses of specifications in the polyhedral model. One of the benefits of our results in the Ƶ-Polyhedral model is that our abstraction allows the reuse of previously developed tools in the polyhedral model with straightforward pre- and post-processing. Advisors/Committee Members: Rajopadhye, Sanjay Vishnu (advisor), Böhm, Anton Pedro Willem, 1948- (committee member), Chong, Edwin Kah Pin (committee member), McConnell, Ross M. (committee member).

Subjects/Keywords: polyhedra models; compilers; program analysis; polyhedral model; loop optimization; Polyhedral functions; Code generators; Compilers (Computer programs); Computer science-Mathematics

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

APA (6^th Edition):

Gupta, G. (2010). Some advances in the polyhedral model. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/40288

Chicago Manual of Style (16^th Edition):

Gupta, Gautam. “Some advances in the polyhedral model.” 2010. Doctoral Dissertation, Colorado State University. Accessed February 28, 2021. http://hdl.handle.net/10217/40288.

MLA Handbook (7^th Edition):

Gupta, Gautam. “Some advances in the polyhedral model.” 2010. Web. 28 Feb 2021.

Vancouver:

Gupta G. Some advances in the polyhedral model. [Internet] [Doctoral dissertation]. Colorado State University; 2010. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/10217/40288.

Council of Science Editors:

Gupta G. Some advances in the polyhedral model. [Doctoral Dissertation]. Colorado State University; 2010. Available from: http://hdl.handle.net/10217/40288

Colorado State University

6. Hoover, Randy C. Pose estimation of spherically correlated images using eigenspace decomposition in conjunction with spectral theory.

Degree: PhD, Electrical and Computer Engineering, 2009, Colorado State University

URL: http://hdl.handle.net/10217/37438

► Eigenspace decomposition represents one computationally efficient approach for dealing with object recognition and pose estimation, as well as other vision-based problems, and has been applied… (more)

▼ Eigenspace decomposition represents one computationally efficient approach for dealing with object recognition and pose estimation, as well as other vision-based problems, and has been applied to sets of correlated images for this purpose. The general idea behind eigenspace decomposition is that a large set of highly correlated images can be approximately represented by a much smaller subspace. Unfortunately, determining the dimension of the subspace, as well as computing the subspace itself is computationally prohibitive. To make matters worse, this off-line expense increases drastically as the number of correlated images becomes large (which is the case when doing fully general three-dimensional pose estimation or illumination invariant pose estimation). However, previous work has shown that for data correlated in one-dimension, Fourier analysis can help reduce the computational burden of this off-line expense. The first part of this dissertation extends some of the ideas developed for one-dimensionally correlated image data to data correlated in two- and three-dimensions making fully general three-dimensional pose estimation possible (assuming the object is illuminated from a single distant light source). The first step in this extension is to determine how to capture training images of the object by sampling the two-sphere (S2), and the rotation group (SO(3)) appropriately. Therefore, a thorough analysis of spherical tessellations is performed as applied to the problem of pose estimation. An algorithm is then developed for reducing the off-line computational burden associated with computing the eigenspace by exploiting the spectral information of this spherical data set. The algorithm is based on the fact that, similar to Fourier analysis on the line or circle, spherically correlated functions can be expanded into a finite series using spherical harmonics. It is then shown that the algorithm can be extended to higher dimensions by applying a proper rotation to each of the samples defined on the surface of the sphere. Using this sampling technique, a parameterization of SO(3) is obtained. It is shown that SO(3) correlated functions can be expanded into a finite series by applying a rotation to the set of spherical harmonics and expanding the function using Wigner-D matrices. Experimental results are presented to compare the proposed algorithm to the true eigenspace decomposition, as well as assess the computational savings. The second part of this dissertation deals with the problem of pose estimation when variations in illumination conditions exist. It is shown that the dimensionality of a set of images of an object under a wide range of illumination conditions and fixed pose can be significantly reduced by expanding the image data in a series of spherical harmonics. This expansion results in a reduced dimensional set of \harmonic images". It is shown that the set of harmonic images are capable of recovering a significant amount of information from a set of images captured when both single and multiple… Advisors/Committee Members: Maciejewski, Anthony A. (advisor), Peterson, Christopher Scott, 1963- (committee member), Roberts, Rodney G. (committee member), Chong, Edwin Kah Pin (committee member), Young, Peter M. (committee member).

Subjects/Keywords: spherical harmonics; eigenspace decomposition; correlated images; pose estimation; Fourier analysis; Spherical harmonics; Fourier analysis

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

APA (6^th Edition):

Hoover, R. C. (2009). Pose estimation of spherically correlated images using eigenspace decomposition in conjunction with spectral theory. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/37438

Chicago Manual of Style (16^th Edition):

Hoover, Randy C. “Pose estimation of spherically correlated images using eigenspace decomposition in conjunction with spectral theory.” 2009. Doctoral Dissertation, Colorado State University. Accessed February 28, 2021. http://hdl.handle.net/10217/37438.

MLA Handbook (7^th Edition):

Hoover, Randy C. “Pose estimation of spherically correlated images using eigenspace decomposition in conjunction with spectral theory.” 2009. Web. 28 Feb 2021.

Vancouver:

Hoover RC. Pose estimation of spherically correlated images using eigenspace decomposition in conjunction with spectral theory. [Internet] [Doctoral dissertation]. Colorado State University; 2009. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/10217/37438.

Council of Science Editors:

Hoover RC. Pose estimation of spherically correlated images using eigenspace decomposition in conjunction with spectral theory. [Doctoral Dissertation]. Colorado State University; 2009. Available from: http://hdl.handle.net/10217/37438

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