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: <ul>
<li>Covers new concepts, new models and new methodologies with theoretical significance in system analysis and control synthesis</li> <li>Includes recent advances in Markovian jump systems, switched hybrid systems, singular systems, stochastic systems and time-delay systems</li> <li>Includes solved problems</li> <li>Introduces advanced techniques</li> </ul>
Sliding 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.

Sliding Mode Control of Uncertain Parameter-Switching Hybrid Systems (Wiley Series in Dynamics and Control of Electromechanical Systems)

Computers & Technology

Shi, Peng

Wu, Ligang

Su, Xiaojie

Computer Science

wiley

Intelligent Control, Filtering and Model Reduction Analysis for Fuzzy-Model-Based Systems (Studies in Systems, Decision and Control)

This book aims to introduce the state-of-the-art research of stability/performance analysis and optimal synthesis methods for fuzzy-model-based systems. 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. Some efficient techniques, such as Lyapunov stability theory, linear matrix inequality, reciprocally convex approach, and cone complementary linearization method, are utilized in the approaches. This book is a comprehensive reference for researchers and practitioners working on intelligent control, model reduction, and fault detection of fuzzy systems, and is also a useful source of information for senior undergraduates and graduates in these areas. The readers will benefit from some new concepts and methodologies with theoretical and practical significance in system analysis and control synthesis.

Intelligent Control, Filtering and Model Reduction Analysis for Fuzzy-Model-Based Systems (Studies in Systems, Decision and Control, 385)

Wen, Yao

Yang, Yue

Springer

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.

Fuzzy Control Systems with Time-Delay and Stochastic Perturbation: Analysis and Synthesis (Studies in Systems, Decision and Control, 12)

Fault-Tolerant Control for Time-Varying Delayed T-S Fuzzy Systems (Intelligent Control and Learning Systems, 9)

Zhang, Huaguang

Sun, Shaoxin

Zhu, Jinyu

Reference

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