In this monograph the authors develop a theory for the robust control of discrete-time stochastic systems, subjected to both independent random perturbations and to Markov chains. Such systems are widely used to provide mathematical models for real processes in fields such as aerospace engineering, communications, manufacturing, finance and economy. The theory is a continuation of the authors work presented in their previous book entitled "Mathematical Methods in Robust Control of Linear Stochastic Systems" published by Springer in 2006.

Key features:

- Provides a common unifying framework for discrete-time stochastic systems corrupted with both independent random perturbations and with Markovian jumps which are usually treated separately in the control literature;

- Covers preliminary material on probability theory, independent random variables, conditional expectation and Markov chains;

- Proposes new numerical algorithms to solve coupled matrix algebraic Riccati equations;

- Leads the reader in a natural way to the original results through a systematic presentation;

- Presents new theoretical results with detailed numerical examples.

The monograph is geared to researchers and graduate students in advanced control engineering, applied mathematics, mathematical systems theory and finance. It is also accessible to undergraduate students with a fundamental knowledge in the theory of stochastic systems."

OO It is a matter of general consensus that in the last decade the H _ optimization for robust control has dominated the research effort in control systems theory. Much attention has been paid equally to the mathematical instrumentation and the computational aspects. There are several excellent monographs that cover the standard topics in the area. Among the recent issues we have to cite here Linear Robust Control authored by Green and Limebeer (Prentice Hall 1995), Robust Controller Design Using Normalized Coprime Factor Plant Descriptions - by McFarlane and Glover (Springer Verlag 1989), Robust and Optimal Control - by Zhou, Doyle and Glover (Prentice Hall 1996). Thus, when the authors of the present monograph decided to start the work they were confronted with a very rich literature on the subject. However two reasons motivated their initiative. The first concerns the theory in which the whole development of the book was embedded. As is well known, there are several ways of approach oo ing H and robust control theory. Here we mention three relevant direc tions chronologically ordered: a) the first makes use of a generalization of the Beurling-Lax theorem to Krein spaces; b) the second makes use of a generalization of Nevanlinna-Pick interpolation theory and commutant lifting theorem; c) the third, and probably the most attractive from an el evate engineering viewpoint, is the two Riccati equations based approach which offers a complete solution in state space form."

The book covers the necessary pre-requisites from probability theory, stochastic processes, stochastic integrals and stochastic differential equations. It includes detailed treatment of the fundamental properties of stochastic systems subjected both to multiplicative white noise and to jump Markovian perturbations. Systematic presentation leads the reader in a natural way to the original results. New theoretical results accompanied by detailed numerical examples, and the book proposes new numerical algorithms to solve coupled matrix algebraic Riccati equations.