Filtering, Control and Fault Detection with Randomly Occurring Incomplete Information E-Book

Hongli Dong

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Sprache: Englisch

Seitenzahl: 268

Veröffentlichungsjahr: 2013

Beschreibung

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.

Leseprobe

Contents

Cover

Title Page

Copyright

Dedication

Preface

Acknowledgments

List of Abbreviations

List of Notations

Chapter 1: Introduction

1.1 Background, Motivations, and Research Problems

1.2 Outline

Chapter 2: Variance-Constrained Finite-Horizon Filtering and Control with Saturations

2.1 Problem Formulation for Finite-Horizon Filter Design

2.2 Analysis of H∞ and Covariance Performances

2.3 Robust Finite-Horizon Filter Design

2.4 Robust H∞ Finite-Horizon Control with Sensor and Actuator Saturations

2.5 Illustrative Examples

2.6 Summary

Chapter 3: Filtering and Control with Stochastic Delays and Missing Measurements

3.1 Problem Formulation for Robust Filter Design

3.2 Robust H∞ Filtering Performance Analysis

3.3 Robust H∞ Filter Design

3.4 Robust H∞ Fuzzy Control

3.5 Illustrative Examples

3.6 Summary

Chapter 4: Filtering and Control for Systems with Repeated Scalar Nonlinearities

4.1 Problem Formulation for Filter Design

4.2 Filtering Performance Analysis

4.3 Filter Design

4.4 Observer-Based H∞ Control with Multiple Packet Losses

4.5 Illustrative Examples

4.6 Summary

Chapter 5: Filtering and Fault Detection for Markov Systems with Varying Nonlinearities

5.1 Problem Formulation for Robust H∞ Filter Design

5.2 Performance Analysis of Robust H∞ Filter

5.3 Design of Robust H∞ Filters

5.4 Fault Detection with Sensor Saturations and Randomly Varying Nonlinearities

5.5 Illustrative Examples

5.6 Summary

Chapter 6: Quantized Fault Detection with Mixed Time-Delays and Packet Dropouts

6.1 Problem Formulation for Fault Detection Filter Design

6.2 Main Results

6.3 Fuzzy-Model-Based Robust Fault Detection

6.4 Illustrative Examples

6.5 Summary

Chapter 7: Distributed Filtering over Sensor Networks with Saturations

7.1 Problem Formulation

7.2 Main Results

7.3 An Illustrative Example

7.4 Summary

Chapter 8: Distributed Filtering with Quantization Errors: The Finite-Horizon Case

8.1 Problem Formulation

8.2 Main Results

8.3 An Illustrative Example

8.4 Summary

Chapter 9: Distributed Filtering for Markov Jump Nonlinear Time-Delay Systems

9.1 Problem Formulation

9.2 Main Results

9.3 An Illustrative Example

9.4 Summary

Chapter 10: A New Finite-Horizon Filtering Approach to Mobile Robot Localization

10.1 Mobile Robot Kinematics and Absolute Measurement

10.2 A Stochastic H∞ Filter Design

10.3 Simulation Results

10.4 Summary

Chapter 11: Conclusions and Future Work

11.1 Conclusions

11.2 Contributions

11.3 Future Work

References

Index

This edition first published 2013 © 2013 John Wiley & Sons, Ltd

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Library of Congress Cataloging-in-Publication Data

Dong, Hongli, 1977–  Filtering, control and fault detection with randomly occurring incomplete information / Hongli Dong, Zidong Wang, Huijun Gao.   pages cm  Includes bibliographical references and index.  ISBN 978-1-118-64791-2 (cloth) 1. Automatic control. 2. Electric filters, Digital. 3. Fault tolerance (Engineering) I. Wang, Zidong, 1966– II. Gao, Huijun. III. Title.  TJ213.D655 2013  003′.75–dc23 2013007460

A catalogue record for this book is available from the British Library

ISBN 9781118647912

The time is boring without random occurrence

The research is monotonous without incomplete information

The life is tedious without fault detection

The living is tough without noise filtering

The power is nothing without control

This book is dedicated to the Dream Dynasty, consisting of a group of simple yet happy people who are falling in love with both the random incompleteness and the incomplete randomness by detecting the faults, filtering the noises, and controlling the powers…

Preface

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 modeling 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. Such a phenomenon typically appears in a networked environment. Examples include, but are not limited to, randomly varying nonlinearities (RVNs), randomly occurring mixed time-delays (ROMDs), randomly occurring multiple time-varying communication delays (ROMTCDs), and randomly occurring quantization errors (ROQEs). Randomly occurring incomplete information, if not properly handled, would seriously deteriorate the performance of a control system.

In this book, we investigate the filtering, control, and fault detection problems for several classes of nonlinear systems with randomly occurring incomplete information. Some new concepts are proposed which include RVNs, ROMDs, ROMTCDs, and ROQEs. The incomplete information under consideration mainly includes missing measurements, time delays, sensor and actuator saturations, quantization effects, and time-varying nonlinearities. The content of this book can be divided into three parts. In the first part, we focus on the filtering, control, and fault detection problems for several classes of nonlinear stochastic discrete-time systems with missing measurements, sensor and actuator saturations, RVNs, ROMDs, and ROQEs. Some sufficient conditions are derived for the existence of the desired filters, controllers, and fault detection filters by developing new techniques for the considered nonlinear stochastic systems. In the second part, the theories and techniques developed in the previous part are extended to deal with distributed filtering issues over sensor networks, and some distributed filters are designed for nonlinear time-varying systems and Markovian jump nonlinear time-delay systems. Finally, we apply a new stochastic H∞ filtering approach to study the mobile robot localization problem, which shows the promising application potential of our main results.

The book is organized as follows. Chapter 1 introduces some recent advances on the analysis and synthesis problems with randomly occurring incomplete information. The developments of the filtering, control, and fault detection problems are systematically reviewed, and the research problems to be addressed in each individual chapter are also outlined. Chapter 2 is concerned with the finite-horizon filtering and control problems for nonlinear time-varying stochastic systems where sensor and actuator saturations, variance-constrained and missing measurements are considered. In Chapters 3 and 4, the H∞ filtering and control problems are addressed for several classes of nonlinear discrete systems where ROMTCDs and multiple packet dropouts are taken into account. Chapter 5 investigates the robust H∞ filtering and fault detection problems for nonlinear Markovian jump systems with sensor saturation and RVNs. In Chapter 6, the fault detection problem is considered for two classes of discrete-time systems with randomly occurring nonlinearities, ROMDs, successive packet dropouts and measurement quantizations. Chapters 7, 8, and 9 discuss the distributed H∞ filtering problem over sensor networks. In Chapter 10, a new stochastic H∞ filtering approach is proposed to deal with the localization problem of the mobile robots modeled by a class of discrete nonlinear time-varying systems subject to missing measurements and quantization effects. Chapter 11 summarizes the results of the book and discusses some future work to be investigated further.

This book is a research monograph whose intended audience is graduate and postgraduate students and researchers.

Acknowledgments

We would like to express our deep appreciation to those who have been directly involved in various aspects of the research leading to this book. Special thanks go to Professor Daniel W. C. Ho from City University of Hong Kong, Professor James Lam from the University of Hong Kong, Professor Xiaohui Liu from Brunel University in the UK, Professor Steven X. Ding from the University of Duisburg–Essen in Germany, and Professor Ligang Wu from Harbin Institute of Technology of China for their valuable suggestions, constructive comments, and support. We also extend our thanks to the many colleagues who have offered support and encouragement throughout this research effort. In particular, we would like to acknowledge the contributions from Bo Shen, Liang Hu, Jun Hu, Yurong Liu, Jinling Liang, Guoliang Wei, Xiao He, Lifeng Ma, Derui Ding, Yao Wang, Xiu Kan, Sunjie Zhang, and Nianyin Zeng. Finally, we are especially grateful to our families for their encouragement and never-ending support when it was most required.

The writing of this book was supported in part by the National 973 Project under Grant 2009CB320600, the National Natural Science Foundation of China under Grants 61273156, 61134009, 61004067, and 61104125, the Engineering and Physical Sciences Research Council (EPSRC) of the UK, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany. The support of these organizations is gratefully acknowledged.

List of Abbreviations

CCLcone complementarity linearizationDFDdistributed filter designDKFdistributed Kalman filteringFHFDfinite-horizon H∞ filter designHCMDLH∞ control with multiple data lossesHFDLH∞ filtering with data lossHinfFCH∞ fuzzy controlHinfFH∞ filteringLMIlinear matrix inequalityMJSMarkovian jump systemNCSnetworked control systemOFDFDoptimized fault detection filter designRFDrobust filter designRHFDrobust H∞ filter designRLMIrecursive linear matrix inequalityRMMrandomly missing measurementROMDrandomly occurring mixed time-delayROMTCDrandomly occurring multiple time-varying communication delayROPDrandomly occurring packet dropoutROQErandomly occurring quantization errorROSSrandomly occurring sensor saturationRVNrandomly varying nonlinearityRDERiccati difference equationSASsensor and actuator saturationSPDsuccessive packet dropoutTPtransition probabilityT–STakagi–Sugeno

List of Notations

the n-dimensional Euclidean spacethe set of all real matricesthe set of all nonnegative real numbersthe set of all nonnegative integersthe set of all negative integersOLthe class of all continuous nondecreasing convex functions such that and for r>0the norm of matrix A defined by ATthe transpose of the matrix Athe Moore–Penrose pseudo inverse of Ithe identity matrix of compatible dimension0the zero matrix of compatible dimensionthe occurrence probability of the event “”the expectation of the stochastic variable xthe expectation of the stochastic variable x conditional on ythe complete probability spacethe smallest eigenvalue of a square matrix Athe largest eigenvalue of a square matrix Athe ellipsis for terms induced by symmetry, in symmetric block matricesdiag{}the block-diagonal matrixthe space of square summable sequencesthe usual l2 normtr(A)the trace of a matrix Amin tr(A)the minimization of tr(A)Var{xi}the variance of xithe Kronecker producteiX>Ythe X−Y is positive definite, where x and y are real symmetric matricesthe X−Y is positive semi-definite, where x and y are real symmetric matrices

1

Introduction

In the past decade, networked control systems (NCSs) have attracted much attention owing to their successful applications in a wide range of areas for the advantage of decreasing the hardwiring, the installation cost, and implementation difficulties. Nevertheless, network-related challenging problems inevitably arise due to the physical equipment constraints, the complexity, and uncertainty of the external environment in the process of modeling or information transmission, which would drastically degrade the system performance. Such network-induced problems include, but are not limited to, missing measurements, communication delays, sensor and actuator saturations, signal quantization, and randomly varying nonlinearities. These phenomena may occur in a probabilistic way that is customarily referred to as randomly occurring incomplete information.

For several decades, nonlinear analysis and stochastic analysis have arguably been two of the most active research areas in systems and control. This is simply because (1) nonlinear control problems are of interest to engineers, physicists, and mathematicians as most physical systems are inherently nonlinear in nature, and (2) stochastic modeling has come to play an important role in many branches of science and industry as many real-world system and natural processes may be subject to stochastic disturbances. There has been a rich literature on the general nonlinear stochastic control problems. A great number of techniques have been developed on filtering, control, and fault detection problems for nonlinear stochastic systems in order to meet the needs of practical engineering. Recently, with the development of NCSs, the analysis and synthesis problems for nonlinear stochastic systems with the aforementioned network-induced phenomena have become interesting and imperative, yet challenging, topics. Therefore, the aim of this book is to deal with the filtering, control, and fault detection problems for nonlinear stochastic systems with randomly occurring incomplete information.