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Full Description
In the context of systems and control, incomplete information refers to a dynamical system in which knowledge about the system states is limited due to the difficulties in modelling complexity in a quantitative way. The well-known types of incomplete information include parameter uncertainties and norm-bounded nonlinearities. Recently, in response to the development of network technologies, the phenomenon of randomly occurring incomplete information has become more and more prevalent.
Filtering, Control and Fault Detection with Randomly Occurring Incomplete Information reflects the state-of-the-art of the research area for handling randomly occurring incomplete information from three interrelated aspects of control, filtering and fault detection. Recent advances in networked control systems and distributed filtering over sensor networks are covered, and application potential in mobile robotics is also considered. The reader will benefit from the introduction of new concepts, new models and new methodologies with practical significance in control engineering and signal processing.
Key Features:
Establishes a unified framework for filtering, control and fault detection problem for various discrete-time nonlinear stochastic systems with randomly occurring incomplete information
Investigates several new concepts for randomly occurring phenomena and proposes a new system model to better describe network-induced problems
Demonstrates how newly developed techniques can handle emerging mathematical and computational challenges
Contains the latest research results
Filtering, Control and Fault Detection with Randomly Occurring Incomplete Information provides a unified yet neat framework for control/filtering/fault-detection with randomly occurring incomplete information. It is a comprehensive textbook for graduate students and is also a useful practical research reference for engineers dealing with control, filtering and fault detection problems for networked systems.
Contents
Preface xi Acknowledgments xiii
List of Abbreviations xv
List of Notations xvii
1 Introduction 1
1.1 Background, Motivations, and Research Problems 2
1.2 Outline 7
2 Variance-Constrained Finite-Horizon Filtering and Control with Saturations 11
2.1 Problem Formulation for Finite-Horizon Filter Design 12
2.2 Analysis of H∞ and Covariance Performances 14
2.3 Robust Finite-Horizon Filter Design 19
2.4 Robust H∞ Finite-Horizon Control with Sensor and Actuator Saturations 22
2.5 Illustrative Examples 30
2.6 Summary 36
3 Filtering and Control with Stochastic Delays and Missing Measurements 41
3.1 Problem Formulation for Robust Filter Design 42
3.2 Robust H∞ Filtering Performance Analysis 45
3.3 Robust H∞ Filter Design 50
3.4 Robust H∞ Fuzzy Control 53
3.5 Illustrative Examples 59
3.6 Summary 72
4 Filtering and Control for Systems with Repeated Scalar Nonlinearities 73
4.1 Problem Formulation for Filter Design 74
4.2 Filtering Performance Analysis 78
4.3 Filter Design 80
4.4 Observer-Based H∞ Control with Multiple Packet Losses 83
4.5 Illustrative Examples 89
4.6 Summary 99
5 Filtering and Fault Detection for Markov Systems with Varying Nonlinearities 101
5.1 Problem Formulation for Robust H∞ Filter Design 102
5.2 Performance Analysis of Robust H∞ Filter 105
5.3 Design of Robust H∞ Filters 109
5.4 Fault Detection with Sensor Saturations and Randomly Varying Nonlinearities 115
5.5 Illustrative Examples 122
5.6 Summary 138
6 Quantized Fault Detection with Mixed Time-Delays and Packet Dropouts 139
6.1 Problem Formulation for Fault Detection Filter Design 140
6.2 Main Results 143
6.3 Fuzzy-Model-Based Robust Fault Detection 150
6.4 Illustrative Examples 158
6.5 Summary 170
7 Distributed Filtering over Sensor Networks with Saturations 171
7.1 Problem Formulation 171
7.2 Main Results 176
7.3 An Illustrative Example 182
7.4 Summary 187
8 Distributed Filtering with Quantization Errors: The Finite-Horizon Case 189
8.1 Problem Formulation 189
8.2 Main Results 194
8.3 An Illustrative Example 198
8.4 Summary 203
9 Distributed Filtering for Markov Jump Nonlinear Time-Delay Systems 205
9.1 Problem Formulation 205
9.2 Main Results 211
9.3 An Illustrative Example 220
9.4 Summary 223
10 A New Finite-Horizon H∞ Filtering Approach to Mobile Robot Localization 227
10.1 Mobile Robot Kinematics and Absolute Measurement 227
10.2 A Stochastic H∞ Filter Design 232
10.3 Simulation Results 242
10.4 Summary 245
11 Conclusions and Future Work 247
11.1 Conclusions 247
11.2 Contributions 249
11.3 Future Work 250
References 253
Index 261
