Stephen L Campbell, Ramine Nikoukhah

Auxiliary Signal Design for Failure Detection

• Gebundenes Buch

Produktbeschreibung

"This book describes the first comprehensive methodology for active failure detection over finite and infinite intervals of observation. The authors are the top researchers in this field, and I anticipate their book will prompt other significant contributions."--Bernard Levy, University of California, Davis "This is the first book I have seen that thoroughly and rigorously addresses an important niche in failure detection."--Frank Lewis, University of Texas, Arlington

Produktdetails

• Verlag: Princeton University Press
• Seitenzahl: 224
• Erscheinungstermin: 15. Februar 2004
• Englisch
• Abmessung: 240mm x 168mm x 20mm
• Gewicht: 449g
• ISBN-13: 9780691099873
• ISBN-10: 0691099871
• Artikelnr.: 21310023

Autorenporträt

Stephen L.Campbell is Professor of Mathematics at North Carolina State University. Ramine Nikoukhah is Senior Scientist (Directeur de Recherche) at Institut National de Recherche en Informatique et en Automatique (INRIA) in France.

Inhaltsangabe

Preface vii
Chapter 1. Introduction 1
1.1 The Basic Question 1
1.2 Failure etection 3
1.3 Failure Identification 9
1.4 Active Approach versus Passive Approach 10
1.5 Outline of the Book 13
Chapter 2. Failure Detection 14
2.1 Introduction 14
2.2 Static Case 15
2.3 Continuous-Time Systems 25
2.4 iscrete-Time Systems 36
2.5 Real-Time Implementation Issues 42
2.6 Useful Results 44
Chapter 3. Multimodel Formulation 59
3.1 Introduction 59
3.2 Static Case 60
3.3 Continuous-Time Case 76
3.4 Case of On-line Measured Input 90
3.5 More GeneralCost Functions 92
3.6 iscrete-Time Case 99
3.7 Suspension Example 102
3.8 Asymptotic Behavior 111
3.9 Useful Results 112
Chapter 4. Direct Optimization Formulations 122
4.1 Introduction 122
4.2 Optimization Formulation for Two Models 123
4.3 General-ModelCase 138
4.4 Early etection 142
4.5 Other Extensions 150
4.6 Systems with Delays 155
4.7 Setting Error Bounds 172
4.8 Model Uncertainty 173
Chapter 5. Remaining Problems and Extensions 176
5.1 Direct Extensions 177
5.2 Hybrid and Sampled Data Systems 179
5.3 Relation to Stochastic Modeling 179
Chapter 6. Scilab Programs 181
6.1 Introduction 181
6.2 Riccati-based Solution 181
6.3 The Block iagonalization Approach 185
6.4 Getting Scilab and the Programs 188
Appendix A. List of Symbols 189
Bibliography 193
Index 201