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 H∞ control problems for a
class of stochastic time-delay uncertain systems with Markovian
switching and nonlinear disturbances
- Explores the H∞ state estimator and H∞ output feedback controller
design issues for stochastic time-delay systems with nonlinear
disturbances, sensor nonlinearities, and Markovian jumping parameters
- Analyzes the H∞ 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 H∞ state estimation problem for a class of
discrete-time complex networks with probabilistic missing measurements
and randomly occurring coupling delays
- Addresses the H∞ 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.
