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 disturbances Investigates the robust stabilization and Hâž control problems for a class of stochastic time-delay uncertain systems with Markovian switching and nonlinear disturbances Explores the Hâž state estimator and Hâž output feedback controller design issues for stochastic time-delay systems with nonlinear disturbances sensor nonlinearities and Markovian jumping parameters Analyzes the Hâž performance for a general class of nonlinear stochastic systems with time delays where the addressed systems are described by general stochastic functional differential equations Studies the filtering problem for a class of discrete-time stochastic nonlinear time-delay systems with missing measurement and stochastic disturbances Uses gain-scheduling techniques to tackle the probability-dependent control and filtering problems for time-varying nonlinear systems with incomplete information Evaluates the filtering problem for a class of discrete-time stochastic nonlinear networked control systems with multiple random communication delays and random packet losses Examines the filtering problem for a class of nonlinear genetic regulatory networks with state-dependent stochastic disturbances and state delays Considers the Hâž state estimation problem for a class of discrete-time complex networks with probabilistic missing measurements and randomly occurring coupling delays Addresses the Hâž synchronization control problem for a class of dynamical networks with randomly varying nonlinearities Nonlinear 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. . Language: English