Dong H., Wang Z., Gao H. Filtering, Control and Fault Detection with Randomly Occurring Incomplete Information

Издательство John Wiley, 2013, -270 pp.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.Variance-Constrained Finite-Horizon Filtering and Control with Saturations
Filtering and Control with Stochastic Delays and Missing Measurements
Filtering and Control for Systems with Repeated Scalar Nonlinearities
Filtering and Fault Detection for Markov Systems with Varying Nonlinearities
Quantized Fault Detection with Mixed Time-Delays and Packet Dropouts
Distributed Filtering over Sensor Networks with Saturations
Distributed Filtering with Quantization Errors: The Finite-Horizon Case
Distributed Filtering for Markov Jump Nonlinear Time-Delay Systems
A New Finite-Horizon H_∞ Filtering Approach to Mobile Robot Localization
Conclusions and Future Work