Thesis (M.S.)--University of Wisconsin--Madison, 1985. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 162-163).

Zhu Minghui. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 144-149). / Abstracts in English and Chinese. / Abstract --- p.v / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Small Gain Theorem --- p.1 / Chapter 1.2 --- Stabilization for Feedforward Systems --- p.2 / Chapter 1.3 --- Output Regulation for Feedforward Systems --- p.4 / Chapter 1.4 --- Organization and Contributions --- p.5 / Chapter 2 --- Input-to-State Stability for Nonlinear Systems --- p.7 / Chapter 3 --- Small Gain Theorem with Restrictions for Uncertain Time-varying Non- linear Systems --- p.13 / Chapter 3.1 --- Input-to-State Stability Small Gain Theorem with Restrictions for Uncer- tain Nonlinear Time-varying Systems --- p.14 / Chapter 3.1.1 --- Nonlinear Time Invariant Systems Case --- p.14 / Chapter 3.1.2 --- Uncertain Time-varying Nonlinear Systems Case --- p.16 / Chapter 3.1.3 --- Remarks and Corollaries --- p.28 / Chapter 3.2 --- Semi-Uniform Input-to-State Stability Small Gain Theorem with Restric- tions for Uncertain Nonlinear Time-varying Systems --- p.38 / Chapter 3.3 --- Asymptotic Small Gain Theorem with Restrictions for Uncertain Nonlinear Time-varying Systems --- p.44 / Chapter 3.4 --- Input-to-State Stability Small Gain Theorem with Restrictions for Uncer- tain Time-varying Systems of Functional Differential Equations --- p.49 / Chapter 4 --- A Remark on Various Small Gain Conditions --- p.52 / Chapter 4.1 --- Introduction --- p.52 / Chapter 4.2 --- Preliminary --- p.53 / Chapter 4.3 --- The Sufficient and Necessary Condition for Input-to-State Stability of Time-varying Systems --- p.56 / Chapter 4.3.1 --- ISS-Lyapunov functions for Time-varying Systems --- p.56 / Chapter 4.3.2 --- A Remark on Input-to-State Stability for Time-varying Systems --- p.61 / Chapter 4.4 --- Comparison of Various Small Gain Theorems --- p.63 / Chapter 4.4.1 --- Comparison of Theorem 4.1 and Theorem 4.2 --- p.63 / Chapter 4.4.2 --- "Comparison of Theorem 4.1 and Theorem 4.3, Theorem 4.2 and Theorem 4.3" --- p.68 / Chapter 4.5 --- Two Small Gain Theorems for Time-varying Systems --- p.70 / Chapter 4.6 --- Conclusion --- p.73 / Chapter 5 --- Semi-global Robust Stabilization for A Class of Feedforward Systems --- p.74 / Chapter 5.1 --- Introduction --- p.74 / Chapter 5.2 --- Main result --- p.76 / Chapter 5.3 --- Conclusion --- p.91 / Chapter 6 --- Global Robust Stabilization for A Class of Feedforward Systems --- p.93 / Chapter 6.1 --- Main Result --- p.93 / Chapter 6.2 --- Conclusion --- p.104 / Chapter 7 --- Global Robust Stabilization and Output Regulation for A Class of Feedforward Systems --- p.105 / Chapter 7.1 --- Introduction --- p.105 / Chapter 7.2 --- Preliminary --- p.107 / Chapter 7.3 --- Global Robust Stabilization via Partial State Feedback --- p.108 / Chapter 7.3.1 --- RAG with restrictions --- p.110 / Chapter 7.3.2 --- Fulfillment of the restrictions --- p.114 / Chapter 7.3.3 --- Small gain conditions --- p.117 / Chapter 7.3.4 --- Uniform Global Asymptotic Stability of Closed Loop System . . . . --- p.118 / Chapter 7.4 --- Global Robust Output Regulation --- p.118 / Chapter 7.5 --- Conclusion --- p.134 / Chapter 8 --- Conclusion --- p.136 / Chapter A --- Appendix --- p.138 / List of Figures --- p.143 / Bibliography --- p.144 / Biography --- p.150

(i) A pure small gain approach is proposed to handle a disturbance attenuation problem for a class of feedforward systems subject to both dynamic uncertainty and disturbance. Two versions of small gain theorem with restrictions are employed to establish the global attractiveness and local stability of the closed-loop system at the origin, respectively. Unlike Lyapunov's linearization method and asymptotic small gain theorem combined approach, the proposed approach does not require the stabilizability assumption of the Jacobian linearization of the system at the origin. / (i) We first identify structural properties of the plant so that an internal model candidate exists. Then, by looking for a suitable internal model and performing appropriate transformations on the augmented system, we succeed in converting the global robust output regulation problem for a class of feedforward systems into a global robust stabilization problem for a class of feedforward systems subject to both time-varying static and dynamic uncertainties. As a result, the global robust stabilization result obtained in the first part of this thesis is used to solve the global robust output regulation problem for a class of feedforward systems. / (ii) A small gain based bottom-up recursive design is developed to solve a global robust stabilization problem for a class of feedforward systems subject to both time-varying static and dynamic uncertainties. Unlike most existing results, our design does not require the bottom dynamics at each recursion be locally exponentially stable. / (ii) We apply the result of the global robust output regulation problem to solve two trajectory tracking problems for a chain of integrators with uncertain parameters and the Vertical Take-Off and Landing (VTOL) aircraft, respectively. In contrast with the existing designs, for the chain of integrators, our design is low gain and does not need to know the reference trajectory exactly, and for the VTOL aircraft, our design is a complete low gain design and thus is more cost effective. / (iii) The small gain based bottom-up recursive design is further extended to deal with a global robust stabilization problem for a class of feedforward systems which are approximated at the origin by a nonlinear chain of integrators and perturbed by some type of input unmodeled dynamics. Even in the special case where the input unmodeled dynamics is not present, our result is new in the sense that our approach can handle some cases that cannot be handled by any existing approaches. / (iii) We propose a Lyapunov approach to a special case of the output regulation problem, the input disturbance suppression problem for a class of feedforward systems. When the exosystem is known, we solve the problem via dynamic output feedback control. When the exosystem is unknown, we solve the problem via adaptive dynamic state feedback control and we also give the conditions under which an estimated parameter vector can converge to the true parameter vector. / It is now well known from the general framework for tackling the output regulation problem that the robust output regulation problem can be approached in two steps. In the first step, the problem is converted into a robust stabilization problem of a so-called augmented system which consists of the original plant and a suitably defined dynamic system called an internal model candidate, and in the second step, the robust stabilization problem of the augmented system is further pursued. The success of the first step depends on whether or not an internal model candidate exists. Even though the first step succeeds, the success of the second step is by no means guaranteed due to at least two obstacles. First, the stabilizability of the augmented system is dictated not only by the given plant but also by the particular internal model candidate employed. Second, the stabilization problem of the augmented system is much more challenging than that of the original plant with the exogenous signal set to 0, because the structure of the augmented system may be much more complex than that of the original plant. Perhaps, it is because of these difficulties, so far almost all papers on semi-global or global robust output regulation problem are focused on the lower triangular systems, feedback linearizable systems and output feedback systems. The second part of this thesis aims to study the global robust output regulation problem of feedforward systems. The major results are summarized as follows. / The stabilization problem of feedforward systems has absorbed a lot of attention during the past fifteen years. More recently, the stabilization problem of feedforward systems subject to input unmodeled dynamics is studied. Nevertheless, the more realistic case where the system is subject to both time-varying static and dynamic uncertainties has not been adequately investigated. The first part of this thesis focuses on the global robust stabilization problem for various classes of feedforward systems containing both time-varying static and dynamic uncertainties. The major results are summarized as follows. / This thesis contains two parts. The first part studies the global robust stabilization problem of feedforward systems and the second part further addresses the global robust output regulation problem of the same class of nonlinear systems. / Chen, Tianshi. / Adviser: Jie Huang. / Source: Dissertation Abstracts International, Volume: 70-09, Section: B, page: . / Thesis submitted in: December 2008. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 136-143). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1994. / Vita. Abstract. Includes bibliographical references (leaves 87-89). Also available via the Internet.

Thesis (Ph. D.)--Virginia Polytechnic Institute and State University, 1994. / Vita. Abstract. Includes bibliographical references (leaves 156-160). Also available via the Internet.

Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2006. / Includes bibliographical references. Also available in electronic version.

This dissertation deals with the problem of analyzing feed-forward priority queueing systems. In this type of system incoming units enter one of n priority queues if the service facility is busy. Units in the highest priority queue are served on a first-come-first-served basis while units in the lower priority queues will only be serviced if there are no higher priority units. A predefined delay time is employed for each queue so that a unit waiting in a lower priority queue is able to transfer to the next higher queue. The waiting unit will transfer to a higher priority queue if its waiting time becomes equal to the predefined delay time. Otherwise, the unit enters the service facility. Units receive service until completion, and at that time, leave the queueing system. The initial approach in this dissertation to analyze such a system is to develop the steady state mathematical expressions for a feed-forward system with two priority queues (FF₂). This represents the simplest case for feed-forward queueing systems (FF_n), and development of the mathematical expressions for this model indicates the tractability of higher order models. Numerical results are obtained from the FF₂ mathematical model by defining input parameters for the delay process, interarrival distribution, and service distribution. To aid in validating the cumulative waiting time results, W_m(t), produced by the mathematical model, an FF₂ simulation model is developed. Results from the two procedures compare favorably which aids in substantiating the notion that the FF₂ model is correct as well as the notion that the simulation model is operating properly. As is often the case, when systems become too complex to be analyzed mathematically, simulation is warranted. Such is the case in this research. Thus, a general simulation model is developed for analyzing higher order systems. This model is capable of representing any FF_n queueing system by simple manipulation. A modified Runge-Kutta procedure is developed for an FF₇ system to ascertain the behavior of the system under transient conditions. Transient results are also obtained from the simulation model. A comparison of the results from the Runge-Kutta and simulation procedures indicate that they agree quite favorably. This agreement aids in substantiating that both methods are properly formulated. The major goal of this research, to develop a model for analyzing FF_n queueing systems, has been accomplished. Various mathematical expressions for analyzing FF₂ systems have been developed. Because higher order models are mathematically intractable, a general simulation model has been developed and substantiated for both steady state and transient conditions. A modified Runge-Kutta procedure has also been developed to aid in analyzing the transient case. / Ph. D.

Call number: LD2668 .T4 1986 B34 / Master of Science

Ng Chi-fai. / Thesis submitted in: December 2000. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 69-73). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgments --- p.iii / List of Figures --- p.viii / List of Tables --- p.ix / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation and Objectives --- p.1 / Chapter 1.2 --- Principles of Feedforward Neural Network Approximation --- p.1 / Chapter 1.3 --- Contribution of The Thesis --- p.5 / Chapter 1.4 --- Outline of The Thesis --- p.5 / Chapter 2 --- Feedforward Neural Networks: An Approximator for Nonlinear Control Law --- p.8 / Chapter 2.1 --- Optimization Methods Applied in Feedforward Neural Network Approximation --- p.8 / Chapter 2.2 --- Example in Supervised Learning --- p.10 / Chapter 2.2.1 --- Problem Description --- p.10 / Chapter 2.2.2 --- Neural Network Configuration and Training --- p.12 / Chapter 2.2.3 --- Simulation Result --- p.13 / Chapter 3 --- Neural Based Approximation of Center Manifold Equations --- p.19 / Chapter 3.1 --- Solving Center Manifold Equations by Feedforward Neural Network Approx- imation --- p.19 / Chapter 3.2 --- Example --- p.21 / Chapter 3.2.1 --- Problem Description --- p.21 / Chapter 3.2.2 --- Simulation Result --- p.24 / Chapter 3.2.3 --- Discussion --- p.24 / Chapter 4 --- Connection of Center Manifold Equations to Output Regulation Problem --- p.29 / Chapter 4.1 --- Output Regulation Theory --- p.29 / Chapter 4.2 --- Reduction of Regulator Equation into Center Manifold Equations --- p.31 / Chapter 5 --- Application to the Control Design of Ball and Beam System --- p.34 / Chapter 5.1 --- Problem Description --- p.34 / Chapter 5.2 --- Neural Approximation Solution of Center Manifold Equations --- p.37 / Chapter 5.3 --- Simulation Results --- p.38 / Chapter 5.4 --- Discussion --- p.45 / Chapter 6 --- Neural Based Disturbance Rejection of Nonlinear Benchmark Problem (TORA System) --- p.48 / Chapter 6.1 --- Problem Description --- p.48 / Chapter 6.2 --- Neural based Approximation of the Center Manifold Equations of TORA System --- p.51 / Chapter 6.3 --- Simulation Results --- p.53 / Chapter 6.4 --- Discussion --- p.59 / Chapter 7 --- Conclusion --- p.62 / Chapter 7.1 --- Future Works --- p.63 / Chapter A --- Center Manifold Theory --- p.64 / Chapter B --- Relation between Center Manifold Equation and Output Regulation Prob- lem --- p.66 / Biography --- p.68 / References --- p.69

by Jan C. Willems. / Bibliography: p. 11. / "August, 1981." / Supported in part by the U.S. Dept. of Energy under Contract DOE/ET-76-A-012295