Xiaojie Su - Böcker

In control theory, sliding mode control (SMC) is a nonlinear control method that alters the dynamics of a nonlinear system by application of a discontinuous control signal that forces the system to slide along a cross-section of the system's normal behaviour. In recent years, SMC has been successfully applied to a wide variety of practical engineering systems including robot manipulators, aircraft, underwater vehicles, spacecraft, flexible space structures, electrical motors, power systems, and automotive engines. Sliding Mode Control of Uncertain Parameter-Switching Hybrid Systems addresses the increasing demand for developing SMC technologies and comprehensively presents the new, state-of-the-art sliding mode control methodologies for uncertain parameter-switching hybrid systems. It establishes a unified framework for SMC of Markovian jump singular systems and proposes new SMC methodologies based on the analysis results. A series of problems are solved with new approaches for analysis and synthesis of switched hybrid systems, including stability analysis and stabilization, dynamic output feedback control, and SMC. A set of newly developed techniques (e.g. average dwell time, piecewise Lyapunov function, parameter-dependent Lyapunov function, cone complementary linearization) are exploited to handle the emerging mathematical/computational challenges.Key features: Covers new concepts, new models and new methodologies with theoretical significance in system analysis and control synthesisIncludes recent advances in Markovian jump systems, switched hybrid systems, singular systems, stochastic systems and time-delay systemsIncludes solved problemsIntroduces advanced techniquesSliding Mode Control of Uncertain Parameter-Switching Hybrid Systems is a comprehensive reference for researchers and practitioners working in control engineering, system sciences and applied mathematics, and is also a useful source of information for senior undergraduate and graduates studying in these areas.

A series of problems are solved with new approaches of design, analysis and synthesis of fuzzy systems, including stabilization control and stability analysis, dynamic output feedback control, fault detection filter design, and reduced-order model approximation.

A series of problems are solved with new approaches of design, analysis and synthesis of fuzzy systems, including stabilization control and stability analysis, dynamic output feedback control, fault detection filter design, and reduced-order model approximation.

This book presents up-to-date research developments and novel methodologies on fuzzy control systems. It presents solutions to a series of problems with new approaches for the analysis and synthesis of fuzzy time-delay systems and fuzzy stochastic systems, including stability analysis and stabilization, dynamic output feedback control, robust filter design, and model approximation. A set of newly developed techniques such as fuzzy Lyapunov function approach, delay-partitioning, reciprocally convex, cone complementary linearization approach are presented. Fuzzy Control Systems with Time-Delay and Stochastic Perturbation: Analysis and Synthesis is a comprehensive reference for researcher and practitioners working in control engineering, system sciences and applied mathematics, and is also a useful source of information for senior undergraduates and graduates in these areas. The readers will benefit from some new concepts, new models and new methodologies with practical significance in control engineering and signal processing.

This book presents up-to-date research developments and novel methodologies on fuzzy control systems. It presents solutions to a series of problems with new approaches for the analysis and synthesis of fuzzy time-delay systems and fuzzy stochastic systems, including stability analysis and stabilization, dynamic output feedback control, robust filter design, and model approximation. A set of newly developed techniques such as fuzzy Lyapunov function approach, delay-partitioning, reciprocally convex, cone complementary linearization approach are presented. Fuzzy Control Systems with Time-Delay and Stochastic Perturbation: Analysis and Synthesis is a comprehensive reference for researcher and practitioners working in control engineering, system sciences and applied mathematics, and is also a useful source of information for senior undergraduates and graduates in these areas. The readers will benefit from some new concepts, new models and new methodologies with practical significance in control engineering and signal processing.

This book delves into the complexities of fault estimation and fault-tolerant control for nonlinear time-delayed systems. Through the use of multiple-integral observers, it addresses fault estimation and active fault-tolerant control for time-delayed fuzzy systems with actuator faults and both actuator and sensor faults. Additionally, the book explores the use of sliding mode control to solve issues of sensor fault estimation, intermittent actuator fault estimation, and active fault-tolerant control for time-delayed switched fuzzy systems. Furthermore, it presents the use of H∞ guaranteed cost control for both time-delayed switched fuzzy systems and time-delayed switched fuzzy stochastic systems with intermittent actuator and sensor faults. Finally, the problem of delay-dependent finite-time fault-tolerant control for uncertain switched T-S fuzzy systems with multiple time-varying delays, intermittent process faults and intermittent sensor faults is studied. The research on fault estimation and tolerant control has drawn attention from engineers and scientists in various fields such as electrical, mechanical, aerospace, chemical, and nuclear engineering. The book provides a comprehensive framework for this topic, placing a strong emphasis on the importance of stability analysis and the impact of result conservatism on the design and implementation of observers and controllers. It is intended for undergraduate and graduate students interested in fault diagnosis and tolerant control technology, researchers studying time-varying delayed T-S fuzzy systems, and observer/controller design engineers working on system stability applications.