Linear stochastic systems are successfully used to provide mathematical models for real processes in fields such as aerospace engineering, communications, manuafacturing, finance and economy. This monograph presents a useful methodology for the control of such stochastic systems, with both multiplicative white noise and Markovian jumping. An important feature is the inclusion of the necessary pre-requisites from probability theory, stochastic processes, stochastic integrals and stochastic differential equations. The systematic style of presentation leads the reader in a natural way to the original results. This unique monograph is geared to researchers and graduate students in advanced control engineering, mathematical systems theory and finance, numerical analysis. It is also accessible to undergraduate students with a fundamental knowledge of the theory of stochastic systems.

Inhalt
Preliminaries to Probability Theory and Stochastic Differential Equations.- Exponential Stability and Lyapunov-Type Linear Equations.- Structural Properties of Linear Stochastic Systems.- The Riccati Equations of Stochastic Control.- Linear Quadratic Control Problem for Linear Stochastic Systems.- Stochastic Version of the Bounded Real Lemma and Applications.- Robust Stabilization of Linear Stochastic Systems.