Zidong Wang

Nonlinear Stochastic Control and Filtering with Engineering-oriented Complexities presents a series of control and filtering approaches for stochastic systems with traditional and emerging engineering-oriented complexities. The book begins with an overview of the relevant background, motivation, and research problems, and then:Discusses the robust stability and stabilization problems for a class of stochastic time-delay interval systems with nonlinear disturbancesInvestigates the robust stabilization and H8 control problems for a class of stochastic time-delay uncertain systems with Markovian switching and nonlinear disturbancesExplores the H8 state estimator and H8 output feedback controller design issues for stochastic time-delay systems with nonlinear disturbances, sensor nonlinearities, and Markovian jumping parametersAnalyzes the H8 performance for a general class of nonlinear stochastic systems with time delays, where the addressed systems are described by general stochastic functional differential equationsStudies the filtering problem for a class of discrete-time stochastic nonlinear time-delay systems with missing measurement and stochastic disturbancesUses gain-scheduling techniques to tackle the probability-dependent control and filtering problems for time-varying nonlinear systems with incomplete informationEvaluates the filtering problem for a class of discrete-time stochastic nonlinear networked control systems with multiple random communication delays and random packet lossesExamines the filtering problem for a class of nonlinear genetic regulatory networks with state-dependent stochastic disturbances and state delaysConsiders the H8 state estimation problem for a class of discrete-time complex networks with probabilistic missing measurements and randomly occurring coupling delaysAddresses the H8 synchronization control problem for a class of dynamical networks with randomly varying nonlinearitiesNonlinear Stochastic Control and Filtering with Engineering-oriented Complexities describes novel methodologies that can be applied extensively in lab simulations, field experiments, and real-world engineering practices. Thus, this text provides a valuable reference for researchers and professionals in the signal processing and control engineering communities.

The book addresses the system performance with a focus on the network-enhanced complexities and developing the engineering-oriented design framework of controllers and filters with potential applications in system sciences, control engineering and signal processing areas. Therefore, it provides a unified treatment on the analysis and synthesis for discrete-time stochastic systems with guarantee of certain performances against network-enhanced complexities with applications in sensor networks and mobile robotics. Such a result will be of great importance in the development of novel control and filtering theories including industrial impact.Key Features Provides original methodologies and emerging concepts to deal with latest issues in the control and filtering with an emphasis on a variety of network-enhanced complexities Gives results of stochastic control and filtering distributed control and filtering, and security control of complex networked systems Captures the essence of performance analysis and synthesis for stochastic control and filtering Concepts and performance indexes proposed reflect the requirements of engineering practice Methodologies developed in this book include backward recursive Riccati difference equation approach and the discrete-time version of input-to-state stability in probability

?Stochastic Control and Filtering over Constrained Communication Networks presents up-to-date research developments and novel methodologies on stochastic control and filtering for networked systems under constrained communication networks. It provides a framework of optimal controller/filter design, resilient filter design, stability and performance analysis for the systems considered, subject to various kinds of communication constraints, including signal-to-noise constraints, bandwidth constraints, and packet drops. Several techniques are employed to develop the controllers and filters desired, including:recursive Riccati equations;matrix decomposition;optimal estimation theory; andmathematical optimization methods.Readers will benefit from the book’s new concepts, models and methodologies that have practical significance in control engineering and signal processing. Stochastic Control and Filtering over Constrained Communication Networks is a practical research reference for engineers dealing with networked control and filtering problems. It is also of interest to academics and students working in control and communication networks.

?Stochastic Control and Filtering over Constrained Communication Networks presents up-to-date research developments and novel methodologies on stochastic control and filtering for networked systems under constrained communication networks. It provides a framework of optimal controller/filter design, resilient filter design, stability and performance analysis for the systems considered, subject to various kinds of communication constraints, including signal-to-noise constraints, bandwidth constraints, and packet drops. Several techniques are employed to develop the controllers and filters desired, including:recursive Riccati equations;matrix decomposition;optimal estimation theory; andmathematical optimization methods.Readers will benefit from the book’s new concepts, models and methodologies that have practical significance in control engineering and signal processing. Stochastic Control and Filtering over Constrained Communication Networks is a practical research reference for engineers dealing with networked control and filtering problems. It is also of interest to academics and students working in control and communication networks.

The book addresses the system performance with a focus on the network-enhanced complexities and developing the engineering-oriented design framework of controllers and filters with potential applications in system sciences, control engineering and signal processing areas. Therefore, it provides a unified treatment on the analysis and synthesis for discrete-time stochastic systems with guarantee of certain performances against network-enhanced complexities with applications in sensor networks and mobile robotics. Such a result will be of great importance in the development of novel control and filtering theories including industrial impact.Key Features Provides original methodologies and emerging concepts to deal with latest issues in the control and filtering with an emphasis on a variety of network-enhanced complexities Gives results of stochastic control and filtering distributed control and filtering, and security control of complex networked systems Captures the essence of performance analysis and synthesis for stochastic control and filtering Concepts and performance indexes proposed reflect the requirements of engineering practice Methodologies developed in this book include backward recursive Riccati difference equation approach and the discrete-time version of input-to-state stability in probability

This book focuses on filtering, control and model-reduction problems for two-dimensional (2-D) systems with imperfect information. The time-delayed 2-D systems covered have system parameters subject to uncertain, stochastic and parameter-varying changes.After an initial introduction of 2-D systems and the ideas of linear repetitive processes, the text is divided into two parts detailing:· General theory and methods of analysis and optimal synthesis for 2-D systems; and· Application of the general theory to the particular case of differential/discrete linear repetitive processes.The methods developed provide a framework for stability and performance analysis, optimal and robust controller and filter design and model approximation for the systems considered. Solutions to the design problems are couched in terms of linear matrix inequalities.For readers interested in the state of the art in linear filtering, control and model reduction, Filtering and Control for Classes of Two-Dimensional Systems will be a useful reference for exploring the field of 2-D systems either from a purely theoretical research perspective or from the point of view of a multitude of potential applications including image processing, and the study of seismographic data or thermal processes.

Nonlinear Stochastic Control and Filtering with Engineering-oriented Complexities presents a series of control and filtering approaches for stochastic systems with traditional and emerging engineering-oriented complexities. The book begins with an overview of the relevant background, motivation, and research problems, and then:Discusses the robust stability and stabilization problems for a class of stochastic time-delay interval systems with nonlinear disturbancesInvestigates the robust stabilization and H8 control problems for a class of stochastic time-delay uncertain systems with Markovian switching and nonlinear disturbancesExplores the H8 state estimator and H8 output feedback controller design issues for stochastic time-delay systems with nonlinear disturbances, sensor nonlinearities, and Markovian jumping parametersAnalyzes the H8 performance for a general class of nonlinear stochastic systems with time delays, where the addressed systems are described by general stochastic functional differential equationsStudies the filtering problem for a class of discrete-time stochastic nonlinear time-delay systems with missing measurement and stochastic disturbancesUses gain-scheduling techniques to tackle the probability-dependent control and filtering problems for time-varying nonlinear systems with incomplete informationEvaluates the filtering problem for a class of discrete-time stochastic nonlinear networked control systems with multiple random communication delays and random packet lossesExamines the filtering problem for a class of nonlinear genetic regulatory networks with state-dependent stochastic disturbances and state delaysConsiders the H8 state estimation problem for a class of discrete-time complex networks with probabilistic missing measurements and randomly occurring coupling delaysAddresses the H8 synchronization control problem for a class of dynamical networks with randomly varying nonlinearitiesNonlinear Stochastic Control and Filtering with Engineering-oriented Complexities describes novel methodologies that can be applied extensively in lab simulations, field experiments, and real-world engineering practices. Thus, this text provides a valuable reference for researchers and professionals in the signal processing and control engineering communities.

This book focuses on filtering, control and model-reduction problems for two-dimensional (2-D) systems with imperfect information. The time-delayed 2-D systems covered have system parameters subject to uncertain, stochastic and parameter-varying changes.After an initial introduction of 2-D systems and the ideas of linear repetitive processes, the text is divided into two parts detailing:· General theory and methods of analysis and optimal synthesis for 2-D systems; and· Application of the general theory to the particular case of differential/discrete linear repetitive processes.The methods developed provide a framework for stability and performance analysis, optimal and robust controller and filter design and model approximation for the systems considered. Solutions to the design problems are couched in terms of linear matrix inequalities.For readers interested in the state of the art in linear filtering, control and model reduction, Filtering and Control for Classes of Two-Dimensional Systems will be a useful reference for exploring the field of 2-D systems either from a purely theoretical research perspective or from the point of view of a multitude of potential applications including image processing, and the study of seismographic data or thermal processes.