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

by Kwok-wai Au. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 55-58). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgments --- p.iii / Contents --- p.iv / List of Figures --- p.vi / List of Tables --- p.viii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Previous work --- p.5 / Chapter 1.3 --- Thesis overview --- p.7 / Chapter 2 --- Dynamics of the Single Wheel Robot --- p.10 / Chapter 2.1 --- Dynamic model of a rolling disk --- p.10 / Chapter 2.1.1 --- Kinematic constraints --- p.11 / Chapter 2.1.2 --- Equations of motion --- p.13 / Chapter 2.1.3 --- Characteristics of the rolling disk --- p.15 / Chapter 2.2 --- Dynamic model of the single wheel robot --- p.18 / Chapter 2.2.1 --- Coordinate frames and generalized coordinates --- p.19 / Chapter 2.2.2 --- Equations of motion --- p.21 / Chapter 2.2.3 --- Model simplification --- p.24 / Chapter 2.3 --- Dynamic properties of the single wheel robot --- p.27 / Chapter 3 --- Stabilization of the Single Wheel Robot --- p.30 / Chapter 3.1 --- Linearized model --- p.30 / Chapter 3.2 --- Controllability and non-minimum phase characteristics --- p.33 / Chapter 3.3 --- Linear state feedback --- p.33 / Chapter 3.4 --- Simulation Study --- p.35 / Chapter 4 --- Path Following of the Single Wheel Robot --- p.37 / Chapter 4.1 --- Path following for nonholonomic systems --- p.37 / Chapter 4.2 --- Definition of path following --- p.39 / Chapter 4.3 --- New configuration --- p.39 / Chapter 4.4 --- Line following --- p.41 / Chapter 4.4.1 --- Velocity control law --- p.42 / Chapter 4.4.2 --- Convergence for the velocity control law --- p.43 / Chapter 4.4.3 --- Torque control law --- p.45 / Chapter 4.5 --- Simulation study --- p.47 / Chapter 4.5.1 --- Effect of the initial heading angle --- p.47 / Chapter 4.5.2 --- Effect of the rolling speed --- p.49 / Chapter 4.5.3 --- Follow a desired line --- p.50 / Chapter 4.5.4 --- Effect of the smoothness parameter --- p.50 / Chapter 5 --- Conclusion --- p.52 / Chapter 5.1 --- Contributions --- p.52 / Chapter 5.2 --- Future work --- p.53 / Bibliography --- p.55

by Wai-Kuen Yu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 83-87). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Robot Concept --- p.1 / Chapter 1.2 --- Motivations --- p.3 / Chapter 1.3 --- Related Work --- p.5 / Chapter 1.4 --- Overview --- p.6 / Chapter 2 --- Single Wheel Robot --- p.8 / Chapter 2.1 --- Mathematical Model --- p.8 / Chapter 2.1.1 --- Coordinate Frame --- p.9 / Chapter 2.1.2 --- Equations of Motion --- p.10 / Chapter 2.1.3 --- Model Simplification --- p.12 / Chapter 2.2 --- Hardware Descriptions --- p.13 / Chapter 2.2.1 --- Actuators --- p.14 / Chapter 2.2.2 --- Sensors --- p.14 / Chapter 2.2.3 --- Communication Subsystem --- p.15 / Chapter 2.2.4 --- Computer Subsystem --- p.16 / Chapter 2.3 --- Software Descriptions --- p.16 / Chapter 2.3.1 --- Operating System --- p.17 / Chapter 2.3.2 --- Software Architecture --- p.18 / Chapter 3 --- Human-based Control --- p.21 / Chapter 3.1 --- Why Human-based Control --- p.21 / Chapter 3.2 --- Modeling Human Control Strategy --- p.22 / Chapter 3.2.1 --- Human Control Strategy --- p.22 / Chapter 3.2.2 --- Neural Network for Modeling --- p.23 / Chapter 3.2.3 --- Learning Procedure --- p.24 / Chapter 3.3 --- Task Descriptions --- p.28 / Chapter 3.4 --- Modeling HCS in Controlling the Robot --- p.29 / Chapter 3.4.1 --- Model Input and Output --- p.30 / Chapter 3.4.2 --- Human-based Controller --- p.31 / Chapter 3.5 --- Result and Discussion --- p.31 / Chapter 4 --- Input Selection --- p.38 / Chapter 4.1 --- Why Input Selection --- p.38 / Chapter 4.2 --- Model Validation --- p.39 / Chapter 4.2.1 --- Why Model Validation --- p.39 / Chapter 4.2.2 --- Root Mean Square Error Measure --- p.40 / Chapter 4.3 --- Experimental Setup --- p.40 / Chapter 4.4 --- Model-based Method --- p.41 / Chapter 4.4.1 --- Problem Definition --- p.41 / Chapter 4.4.2 --- Input Representation --- p.43 / Chapter 4.4.3 --- Sensitivity Analysis --- p.44 / Chapter 4.4.4 --- Experimental Result --- p.47 / Chapter 4.5 --- Model-free Method --- p.51 / Chapter 4.5.1 --- Problems Definition --- p.51 / Chapter 4.5.2 --- Factor Analysis --- p.54 / Chapter 4.5.3 --- Experimental Result --- p.63 / Chapter 4.6 --- Model-based Method versus Model-free Method --- p.66 / Chapter 5 --- Conclusion and Future Work --- p.71 / Chapter 5.1 --- Contributions --- p.71 / Chapter 5.2 --- Future Work --- p.72 / Chapter Appendix A --- Dynamic Model of the Robot --- p.74 / Chapter A.1 --- Kinematic Constraints: Holonomic and Nonholonomic --- p.74 / Chapter A.1.1 --- Coordinate Frame --- p.74 / Chapter A.2 --- Robot Dynamics --- p.76 / Chapter A.2.1 --- Single Wheel --- p.77 / Chapter A.2.2 --- Internal Mechanism and Spinning Flywheel --- p.77 / Chapter A.2.3 --- Lagrangians of the System --- p.78 / Chapter Appendix B --- Similarity Measure --- p.80 / Bibliography --- p.82

by Loi-Wah Sun. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 77-81). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgments --- p.iii / Contents --- p.v / List of Figures --- p.vii / List of Tables --- p.viii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.1.1 --- Literature review --- p.2 / Chapter 1.1.2 --- Gyroscopic precession --- p.5 / Chapter 1.2 --- Thesis overview --- p.7 / Chapter 2 --- Dynamics of the robot on ground --- p.9 / Chapter 2.1 --- System model re-derivation --- p.10 / Chapter 2.1.1 --- Linearized model --- p.15 / Chapter 2.2 --- A state feedback control --- p.16 / Chapter 2.3 --- Dynamic characteristics of the system --- p.18 / Chapter 2.4 --- Simulation study --- p.19 / Chapter 2.4.1 --- The self-stabilizing dynamics effect of the single wheel robot --- p.21 / Chapter 2.4.2 --- The Tilting effect of flywheel on the robot --- p.23 / Chapter 2.5 --- Dynamic parameters analysis --- p.25 / Chapter 2.5.1 --- Swinging pendulum --- p.25 / Chapter 2.5.2 --- Analysis of radius ratios --- p.27 / Chapter 2.5.3 --- Analysis of mass ratios --- p.30 / Chapter 3 --- Dynamics of the robot on incline --- p.33 / Chapter 3.1 --- Modeling of rolling disk on incline --- p.33 / Chapter 3.1.1 --- Disk rolls up on an inclined plane --- p.37 / Chapter 3.2 --- Modeling of single wheel robot on incline --- p.39 / Chapter 3.2.1 --- Kinematic constraints --- p.40 / Chapter 3.2.2 --- Equations of motion --- p.41 / Chapter 3.2.3 --- Model simplification --- p.43 / Chapter 3.2.4 --- Linearized model --- p.46 / Chapter 4 --- Control of the robot on incline --- p.47 / Chapter 4.1 --- A state feedback control --- p.47 / Chapter 4.1.1 --- Simulation study --- p.49 / Chapter 4.2 --- Backstepping-based control --- p.51 / Chapter 4.2.1 --- Simulation study --- p.53 / Chapter 4.2.2 --- The effect of the spinning rate of flywheel --- p.56 / Chapter 4.2.3 --- Simulation study --- p.58 / Chapter 4.2.4 --- Roll up case --- p.58 / Chapter 4.2.5 --- Roll down case --- p.58 / Chapter 5 --- Motion planning --- p.61 / Chapter 5.1 --- Performance index --- p.61 / Chapter 5.2 --- Condition of rolling up --- p.62 / Chapter 5.3 --- Motion planning of rolling Up --- p.65 / Chapter 5.3.1 --- Method I : Orientation change --- p.65 / Chapter 5.3.2 --- Method II : Change the initial velocities --- p.69 / Chapter 5.4 --- Wheel rolls Down --- p.70 / Chapter 5.4.1 --- Terminal velocity of rolling body down --- p.73 / Chapter 6 --- Summary --- p.75 / Chapter 6.1 --- Contributions --- p.75 / Chapter 6.2 --- Future Works --- p.76 / Bibliography --- p.78

by Dong Sun. / Thesis (Ph.D.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (p. 116-121). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web.

No description available.

(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.

After capturing the object, the space robot must complete the following two tasks: one is to berth the object, and the other is to re-orientate the attitude of the whole robot system for communication and power supply. Therefore, I propose a method to accomplish these two tasks simultaneously using manipulator motion only. / Finally I propose a novel approach based on Genetic Algorithms (GAs) to optimize the approach trajectory of space robots in order to realize effective and stable operations. I complete the minimum-torque path planning in order to save the limited energy in space, and design the minimum jerk trajectory for the stabilization of the space manipulator and its space base. These optimal algorithms are very important and useful for the application of space robot. / In this thesis, I study and analyze the dynamics and control problems of space robot for capturing objects. This work has potential impact in space robotic applications. I first study the contact and impact dynamics of space robot and objects. I specifically focus on analyzing the impact dynamics and mapping the relationship of influence and speed. Then, I develop the fundamental theory for planning the minimum-collision based trajectory of space robot and designing the configuration of space robot at the moment of capture. / Space robots are expected to perform intricate tasks in future space services, such as satellite maintenance, refueling, and replacing the orbital replacement unit (ORU). To realize these missions, the capturing operation may not be avoided. Such operations will encounter some challenges because space robots have some unique characteristics unfound on ground-based robots, such as, dynamic singularities, dynamic coupling between manipulator and space base, limited energy supply and working without a fixed base, and so on. In addition, since contacts and impacts may not be avoided during capturing operation. Therefore, dynamics and control problems of space robot for capturing objects are significant research topics if the robots are to be deployed for the space services. A typical servicing operation mainly includes three phases: capturing the object, berthing and docking the object, then repairing the target. Therefore, this thesis will focus on resolving some challenging problems during capturing the object, berthing and docking, and so on. / The ultimate goal of space services is to realize the capture and manipulation autonomously. Therefore, I propose an affective approach based on learning human skill to track and capture the objects automatically in space. With human-teaching demonstration, the space robot is able to learn and abstract human tracking and capturing skill using an efficient neural-network learning architecture that combines flexible Cascade Neural Networks with Node Decoupled Extended Kalman Filtering (CNN-NDEKF). The simulation results attest that this approach is useful and feasible in tracking trajectory planning and capturing of space robot. / To compensate for the attitude of the space base during the capturing approach operation, a new balance control concept which can effectively balance the attitude of the space base using the dynamic couplings is developed. The developed balance control concept helps to understand of the nature of space dynamic coupling, and can be readily applied to compensate or minimize the disturbance to the space base. / Huang Panfeng. / "December 2005." / Adviser: Yang Sheng Xu. / Source: Dissertation Abstracts International, Volume: 67-11, Section: B, page: 6693. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (p. 133-143). / 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.

No description available.

Reliable controller designs have been developed in this thesis for a number of finite-horizon and infinite-horizon problems with possibly non-zero initial conditions. These reliable controllers assure that system stability and system performance will be maintained despite certain system faults. The performance measure used in this thesis is an "H[subscript ���]-like norm", which is an induced two-norm from all exogenous signals and initial conditions to the regulated output and final states. Controller designs and existence conditions are presented for a reliable controller for faults in any pre-selected subset of actuators or sensors. Also, controller designs and an existence condition are presented for a reliable controller for any single sensor or actuator fault using sensor and actuator redundancy. / Graduation date: 1999