Introduction Background, Motivation, and Research Problems Outline Robust Stabilization for Stochastic Time-Delay Interval Systems Problem Formulation Robust Stability Analysis Delay-Dependent Robust Stabilization An Illustrative Example Summary Robust H Control for Markov Systems with Nonlinear Disturbance Problem Formulation Robust Stabilization H Control An Illustrative Example Summary H Filtering and Control for Markov Systems with Sensor Nonlinearities Problem Formulation H Filtering H Dynamical Output Feedback Control Summary H Analysis for Stochastic Differential Systems by Razumikhin Theory Problem Formulation Main Results The L2 Gain Problem for Nonlinear Stochastic Delay System Examples Summary Robust Filtering with Nonlinearities and Multiple Missing Measurements Problem Formulation Main Results An Illustrative Example Summary Probability-Dependent Control with Randomly Occurring Nonlinearities Problem Formulation Gain-Scheduled Controller Design Computationally Accessible Solution An Illustrative Example Summary Probability-Dependent Filtering with Missing Measurements Problem Formulation Main Results An Illustrative Example Summary Controller Design for 2-D Stochastic Nonlinear Roesser Model Problem Formulation and Preliminaries Main Results An Illustrative Example Summary Filtering for Networked Control Systems with Multiple Delays Problem Formulation Main Results An Illustrative Example Summary State Estimation for Stochastic Delayed Gene Regulatory Networks Problem Formulation Main Results An Illustrative Example Summary State Estimation for Complex Networks with ROCD Problem Formulation Main Results An Illustrate Example Summary H Synchronization for Complex Networks with RVN Problem Formulation Main Results An Illustrative Example Summary.

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.