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E-raamat: Sliding Mode Control of Uncertain Parameter-Switching Hybrid Systems

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Wu, Shi, and Su present up-to-date research developments and novel methodologies on the sliding mode control (SMC) of uncertain parameter-switching, hybrid systems in a unified matrix inequality setting. They cover Markovian jump singular systems, switched state-delayed hybrid systems, and switched stochastic hybrid systems. The topics include state estimation and SMC of Markovian jump singular systems, SMC of Markovian jump singular systems with stochastic perturbation, the stability and stabilization of switched state-delayed hybrid systems, SMC of switched state-delayed hybrid systems in continuous-time and discrete-time cases, the control of switched stochastic hybrid systems in the continuous-time and discrete-time cases, and SMC with dissipativity of switched stochastic hybrid systems. Annotation ©2014 Ringgold, Inc., Portland, OR (protoview.com)

Presents new, state-of-the-art sliding mode control (SMC) methodologies for uncertain parameter-switching hybrid systems

Sliding Mode Control of Uncertain Parameter-Switching Hybrid Systems presentsnew, state-of-the-art sliding mode control (SMC) methodologies for uncertain parameter-switching hybrid systems (including Markovian jump systems, switched hybrid systems, singular systems, stochastic systems and time-delay systems).

The first part of this book establishes a unified framework for SMC of Markovian jump singular systems and proposes new SMC methodologies based on the analysis results. In the second part, the problem of SMC of switched state-delayed hybrid systems is investigated, and finally the parallel theories and techniques that have been developed are extended to deal with switched stochastic hybrid systems.

Solved problems with new approaches for analysis and synthesis of continuous- and discrete-time switched hybrid systems, (including stability analysis and stabilization, dynamic output feedback control,) are also included throughout.

  • Presents new, state-of-the-art sliding mode control (SMC) methodologies for uncertain parameter-switching hybrid systems
  • Provides a unified, systematic framework for handling SMC problems
  • Introduces new concepts, models and techniques
  • Includes solved problems throughout
Series Preface xi
Preface xiii
Acknowledgments xv
Abbreviations and Notations xvii
1 Introduction
1(34)
1.1 Sliding Mode Control
1(15)
1.1.1 Fundamental Theory of SMC
1(12)
1.1.2 Overview of SMC Methodologies
13(3)
1.2 Uncertain Parameter-Switching Hybrid Systems
16(9)
1.2.1 Analysis and Synthesis of Switched Hybrid Systems
16(7)
1.2.2 Analysis and Synthesis of Markovian Jump Linear Systems
23(2)
1.3 Contribution of the Book
25(1)
1.4 Outline of the Book
26(9)
Part One SMC Of Markovian Jump Singular Systems
2 State Estimation and SMC of Markovian Jump Singular Systems
35(14)
2.1 Introduction
35(1)
2.2 System Description and Preliminaries
36(1)
2.3 Stochastic Stability Analysis
37(3)
2.4 Main Results
40(6)
2.4.1 Observer and SMC Law Design
40(2)
2.4.2 Sliding Mode Dynamics Analysis
42(4)
2.5 Illustrative Example
46(2)
2.6 Conclusion
48(1)
3 Optimal SMC of Markovian Jump Singular Systems with Time Delay
49(16)
3.1 Introduction
49(1)
3.2 System Description and Preliminaries
50(1)
3.3 Bounded L2 Gain Performance Analysis
51(4)
3.4 Main Results
55(6)
3.4.1 Sliding Mode Dynamics Analysis
55(5)
3.4.2 SMC Law Design
60(1)
3.5 Illustrative Example
61(3)
3.6 Conclusion
64(1)
4 SMC of Markovian Jump Singular Systems with Stochastic Perturbation
65(22)
4.1 Introduction
65(1)
4.2 System Description and Preliminaries
66(1)
4.3 Integral SMC
67(4)
4.3.1 Sliding Mode Dynamics Analysis
67(3)
4.3.2 SMC Law Design
70(1)
4.4 Optimal Hinfinity Integral SMC
71(7)
4.4.1 Performance Analysis and SMC Law Design
71(6)
4.4.2 Computational Algorithm
77(1)
4.5 Illustrative Example
78(6)
4.6 Conclusion
84(3)
Part Two SMC Of Switched State-Delayed Hybrid Systems
5 Stability and Stabilization of Switched State-Delayed Hybrid Systems
87(20)
5.1 Introduction
87(1)
5.2 Continuous-Time Systems
88(7)
5.2.1 System Description
88(1)
5.2.2 Main Results
89(5)
5.2.3 Illustrative Example
94(1)
5.3 Discrete-Time Systems
95(9)
5.3.1 System Description
95(1)
5.3.2 Main Results
96(7)
5.3.3 Illustrative Example
103(1)
5.4 Conclusion
104(3)
6 Optimal DOF Control of Switched State-Delayed Hybrid Systems
107(34)
6.1 Introduction
107(1)
6.2 Optimal L2-Linfinity DOF Controller Design
108(17)
6.2.1 System Description and Preliminaries
108(1)
6.2.2 Main Results
109(12)
6.2.3 Illustrative Example
121(4)
6.3 Guaranteed Cost DOF Controller Design
125(15)
6.3.1 System Description and Preliminaries
125(1)
6.3.2 Main Results
126(10)
6.3.3 Illustrative Example
136(4)
6.4 Conclusion
140(1)
7 SMC of Switched State-Delayed Hybrid Systems: Continuous-Time Case
141(18)
7.1 Introduction
141(1)
7.2 System Description and Preliminaries
142(1)
7.3 Main Results
143(8)
7.3.1 Sliding Mode Dynamics Analysis
143(4)
7.3.2 SMC Law Design
147(4)
7.4 Illustrative Example
151(6)
7.5 Conclusion
157(2)
8 SMC of Switched State-Delayed Hybrid Systems: Discrete-Time Case
159(16)
8.1 Introduction
159(1)
8.2 System Description and Preliminaries
160(1)
8.3 Main Results
161(8)
8.3.1 Sliding Mode Dynamics Analysis
161(6)
8.3.2 SMC Law Design
167(2)
8.4 Illustrative Example
169(2)
8.5 Conclusion
171(4)
Part Three SMC Of Switched Stochastic Hybrid Systems
9 Control of Switched Stochastic Hybrid Systems: Continuous-Time Case
175(22)
9.1 Introduction
175(1)
9.2 System Description and Preliminaries
176(2)
9.3 Stability Analysis and Stabilization
178(4)
9.4 Hinfinity Control
182(8)
9.4.1 Hinfinity Performance Analysis
182(3)
9.4.2 State Feedback Control
185(1)
9.4.3 Hinfinity DOF Controller Design
186(4)
9.5 Illustrative Example
190(5)
9.6 Conclusion
195(2)
10 Control of Switched Stochastic Hybrid Systems: Discrete-Time Case
197(18)
10.1 Introduction
197(1)
10.2 System Description and Preliminaries
197(2)
10.3 Stability Analysis and Stabilization
199(6)
10.4 Hinfinity Control
205(5)
10.5 Illustrative Example
210(4)
10.6 Conclusion
214(1)
11 State Estimation and SMC of Switched Stochastic Hybrid Systems
215(18)
11.1 Introduction
215(1)
11.2 System Description and Preliminaries
215(2)
11.3 Main Results
217(3)
11.3.1 Sliding Mode Dynamics Analysis
217(2)
11.3.2 SMC Law Design
219(1)
11.4 Observer-Based SMC Design
220(6)
11.5 Illustrative Example
226(6)
11.6 Conclusion
232(1)
12 SMC with Dissipativity of Switched Stochastic Hybrid Systems
233(18)
12.1 Introduction
233(1)
12.2 Problem Formulation and Preliminaries
234(2)
12.2.1 System Description
234(1)
12.2.2 Dissipativity
235(1)
12.3 Dissipativity Analysis
236(5)
12.4 Sliding Mode Control
241(5)
12.4.1 Sliding Mode Dynamics
241(1)
12.4.2 Sliding Mode Dynamics Analysis
242(3)
12.4.3 SMC Law Design
245(1)
12.5 Illustrative Example
246(4)
12.6 Conclusion
250(1)
References 251(12)
Index 263
Ligang Wu received the PhD degree in Control Theory and Control Engineering in 2006 from Harbin Institute of Technology, China. He was a Research Associate at Imperial College London, UK, and The University of Hong Kong, Hong Kong; a Senior Research Associate at City University of Hong Kong, Hong Kong. Now, he is a Professor of Control Science and Engineering at Harbin Institute of Technology, Harbin, China. Prof. Wus current research interests include sliding mode control, switched hybrid systems, optimal control and filtering, aircraft control, and model reduction. Prof. Wu has been in the editorial board of a number of international journals, including IEEE Transactions on Automatic Control, IEEE Access, Information Sciences, Signal Processing, IET Control Theory and Applications, Circuits Systems and Signal Processing, Multidimensional Systems and Signal Processing, and Neurocomputing. He is also an Associate Editor for the Conference Editorial Board, IEEE Control Systems Society.

Peng Shi received the PhD degree in Electrical Engineering from the University of Newcastle, Australia; the PhD degree in Mathematics from the University of South Australia; and the DSc degree from the University of Glamorgan, UK. He was a lecturer at the University of South Australia; a senior scientist in the Defence Science and Technology Organisation, Australia; and a professor at the University of Glamorgan, UK. Now, he is a professor at The University of Adelaide; and Victoria University, Australia. Prof. Shi's research interests include system and control theory, computational intelligence, and operational research. Prof. Shi is a Fellow of the Institution of Engineering and Technology, and a Fellow of the Institute of Mathematics and its Applications. He has been in the editorial board of a number of international journals, including IEEE Transactions on Automatic Control; Automatica; IEEE Transactions on Fuzzy Systems; IEEE Transactions on Cybernetics; and IEEE Transactions on Circuits and Systems-I.

Xiaojie Su was born in Henan, China, in 1985. He received the B.E. degree in automation from Jiamusi University, Jiamusi, China, in 2008, the M.S. degree in Control Science and Engineering from Harbin Institute of Technology, Harbin, China, in 2010, and the PhD degree in Control Science and Engineering from Harbin Institute of Technology, Harbin, China, in 2013. Currently, he is a Professor of College of Automation at Chongqing University, Chongqing, China. His research interests include sliding mode control, robust filtering, T-S fuzzy systems, and model reduction. As a Guest Editor, he has organized two special issues in Mathematical Problems in Engineering and Abstract and Applied Analysis, respectively.