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E-grāmata: Linear Systems: Non-Fragile Control and Filtering

, , (Northeastern University, Shenyang, China),
  • Formāts: 288 pages
  • Izdošanas datums: 19-Dec-2017
  • Izdevniecība: CRC Press Inc
  • Valoda: eng
  • ISBN-13: 9781351831819
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Linear Systems: Non-Fragile Control and FilteringPalielināt
  • Formāts: 288 pages
  • Izdošanas datums: 19-Dec-2017
  • Izdevniecība: CRC Press Inc
  • Valoda: eng
  • ISBN-13: 9781351831819
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"Designing controllers/filters such that the resulting closed-loop systems are non-fragile or insensitive with respect to the perturbations in the controller or filter coefficients has become an important research topic in many fields of engineering and science. This book develops a systematic presentation of the newly proposed methods for non-fragile/insensitive control/filtering of linear systems with respect to controller/filter coefficient variations. It provides designs and guidelines that can be used to develop advanced non-fragile control techniques to improve reliability, maintainability, and survivability of complex control systems"--

Chinese researchers Yang (control theory and navigation technology, Northeastern U., Guo (electrical engineering, Tianjin U. of Technology), Che (engineering, Shenyang U.), and Guan (automation, Shenyang Aerospace U.) present the results of their recent research into non-fragile controllers/filters for linear systems. They introduce the algebraic Riccati equation technique to solve the type of additive/multiplicative norm-bounded controller/filter gain uncertainty, while proposing a structured vertex separator to approach the numerical problem by considering interval-bounded coefficient variations. Annotation ©2013 Book News, Inc., Portland, OR (booknews.com)

Linear Systems: Non-Fragile Control and Filtering presents the latest research results and a systematic approach to designing non-fragile controllers and filters for linear systems. The authors combine the algebraic Riccati technique, the linear matrix inequality (LMI) technique, and the sensitivity analysis method to establish a set of new non-fragile (insensitive) control methods. This proposed method can optimize the closed-loop system performance and make the designed controllers or filters tolerant of coefficient variations in controller or filter gain matrices.

A Systematic Approach to Designing Non-Fragile Controllers and Filters for Linear Systems

The text begins with developments and main research methods in non-fragile control. It then systematically presents novel methods for non-fragile control and filtering of linear systems with respect to additive/multiplicative controller/filter gain uncertainties. The book introduces the algebraic Riccati equation technique to solve additive/multiplicative norm-bounded controller/filter gain uncertainty, and proposes a structured vertex separator to deal with the numerical problem resulting from interval-bounded coefficient variations. It also explains how to design insensitive controllers and filters in the framework of coefficient sensitivity theory. Throughout, the book includes numerical examples to demonstrate the effectiveness of the proposed design methods.

More Effective Design Methods for Non-Fragile Controllers and Filters

The design and analysis tools described will help readers to better understand and analyze parameter uncertainties and to design more effective non-fragile controllers and filters. Providing a coherent approach, this book is a valuable reference for researchers, graduate students, and anyone who wants to explore the area of non-fragile control and filtering.

Preface ix
Symbol Description xiii
1 Introduction
1(6)
2 Preliminaries
7(12)
2.1 Delta Operator Definition
7(1)
2.2 H∞ Performance Index
8(1)
2.3 Operations on Systems
9(2)
2.4 Some Other Definitions and Lemmas
11(8)
3 Non-Fragile State Feedback Control with Norm-Bounded Gain Uncertainty
19(18)
3.1 Introduction
19(1)
3.2 Problem Statement
19(3)
3.3 Non-Fragile Guaranteed Cost Controller Design
22(12)
3.3.1 Additive Controller Gain Uncertainty Case
22(4)
3.3.2 Multiplicative Controller Gain Uncertainty Case
26(8)
3.4 Example
34(1)
3.5 Conclusion
35(2)
4 Non-Fragile Dynamic Output Feedback Control with Norm-Bounded Gain Uncertainty
37(24)
4.1 Introduction
37(1)
4.2 Problem Statement
38(3)
4.3 Non-Fragile H∞ Dynamic Output Feedback Controller Design
41(16)
4.3.1 Additive Controller Gain Uncertainty Case
41(7)
4.3.2 Multiplicative Controller Gain Uncertainty Case
48(9)
4.4 Example
57(3)
4.5 Conclusion
60(1)
5 Robust Non-Fragile Kalman Filtering with Norm-Bounded Gain Uncertainty
61(24)
5.1 Introduction
61(1)
5.2 Problem Statement
62(2)
5.3 Robust Non-Fragile Filter Design
64(18)
5.3.1 Additive Gain Uncertainty Case
64(9)
5.3.2 Multiplicative Gain Uncertainty Case
73(9)
5.4 Example
82(1)
5.5 Conclusion
83(2)
6 Non-Fragile Output Feedback Control with Interval-Bounded Coefficient Variations
85(46)
6.1 Introduction
85(1)
6.2 Non-Fragile H∞ o Controller Design for Discrete-Time Systems
86(17)
6.2.1 Problem Statement
86(1)
6.2.2 Non-Fragile H∞ Controller Design Methods
87(12)
6.2.3 Example
99(4)
6.3 Non-Fragile H∞ Controller Design for Continuous-Time Systems
103(11)
6.3.1 Problem Statement
104(1)
6.3.2 Non-Fragile H∞ Controller Design Methods
104(6)
6.3.3 Example
110(4)
6.4 Non-Fragile H∞ Controller Designs with Sparse Structures
114(14)
6.4.1 Problem Statement
114(5)
6.4.2 Sparse Structured Controller Design
119(5)
6.4.3 Example
124(4)
6.5 Conclusion
128(3)
7 Non-Fragile H∞ Filtering with Interval-Bounded Coefficient Variations
131(36)
7.1 Introduction
131(1)
7.2 Non-Fragile H∞ Filtering for Discrete-Time Systems
132(13)
7.2.1 Problem Statement
132(1)
7.2.2 Non-Fragile H∞ Filter Design Methods
133(9)
7.2.3 Example
142(3)
7.3 Non-Fragile H∞ Filter Design for Linear Continuous-Time Systems
145(10)
7.3.1 Problem Statement
145(1)
7.3.2 Non-Fragile H∞ Filter Design Methods
146(5)
7.3.3 Example
151(4)
7.4 Sparse Structured Filter Design
155(11)
7.4.1 Problem Statement
155(5)
7.4.2 Non-Fragile H∞ Filter Design with Sparse Structures
160(4)
7.4.3 Example
164(2)
7.5 Conclusion
166(1)
8 Insensitive H∞ Filtering of Continuous-Time Systems
167(24)
8.1 Introduction
167(1)
8.2 Problem Statement
168(4)
8.3 Insensitive H∞ Filter Design
172(8)
8.3.1 Additive Filter Coefficient Variation Case
173(4)
8.3.2 Multiplicative Filter Coefficient Variation Case
177(3)
8.4 Computation of Robust H∞ Performance Index
180(2)
8.5 Comparison with the Existing Design Method
182(1)
8.6 Example
183(6)
8.7 Conclusion
189(2)
9 Insensitive H∞ Filtering of Delta Operator Systems
191(20)
9.1 Introduction
191(1)
9.2 Problem Statement
192(6)
9.3 Insensitive H∞ Filter Design
198(8)
9.3.1 Additive Coefficient Variation Case 1-
98(104)
9.3.2 Multiplicative Filter Coefficient Variation Case
202(4)
9.4 Example
206(4)
9.5 Conclusion
210(1)
10 Insensitive H∞ Output Tracking Control
211(16)
10.1 Introduction
211(1)
10.2 Problem Statement
212(6)
10.3 Insensitive H∞ Tracking Control Design
218(2)
10.4 Example
220(5)
10.5 Conclusion
225(2)
11 Insensitive H∞ Dynamic Output Feedback Control
227(36)
11.1 Introduction
227(1)
11.2 Problem Statement
228(3)
11.2.1 Sensitivity Function
228(3)
11.2.2 Sensitivity Measures
231(1)
11.2.3 Insensitive H∞ Control with Controller Coefficient Variations
231(1)
11.3 Insensitive H∞ Controller Design
231(21)
11.3.1 Step 1 General Conditions for the Existence of Insensitive H∞ Controllers
231(5)
11.3.2 Step 2 Non-Fragile H∞ Controller Design with Interval Bounded Controller Coefficient Variations
236(7)
11.3.3 Summary of the Approach
243(1)
11.3.4 Insensitive H∞ Control with Multiplicative Controller Coefficient Variations
244(8)
11.4 Example
252(6)
11.5 Conclusion
258(5)
Bibliography 263(14)
Index 277
Guang-Hong Yang is currently a professor and director of the Institute of Control Theory and Navigation Technology at the College of Information Science and Engineering, Northeastern University, China. His research interests include fault tolerant control, fault detection and isolation, non-fragile control systems design, robust control, networked control, nonlinear control, and flight control systems. Dr. Yang has published more than 200 fully-refereed papers in technical journals and conference proceedings and has coauthored two books. He is an associate editor for the IEEE Transactions on Fuzzy Systems and the International Journal of Systems Science (IJSS). He is the chair of the IEEE Harbin Section Control Systems Society Chapter and general chair/program chair of the Chinese Control and Decision Conference (CCDC) (2008-2013).

Xiang-Gui Guo is a lecturer in the School of Electrical Engineering at Tianjin University of Technology, China. His research interests include insensitive control, non-fragile control, reliable control, and their applications to flight control systems design.

Wei-Wei Che is currently an associate professor at Shenyang University, China. She is a member of the IEEE. Her research interest includes non-fragile control, quantization control, and their applications to networked control system design.

Wei Guan is a lecturer in the School of Automation at Shenyang Aerospace University, China. His research interests include non-fragile control, actuator saturation, and state constraints.
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