Mathematical Methods in Robust Control of Linear Stochastic Systems

Linear stochastic systems are successfully used to provide mathematical models for real processes. This book covers the necessary pre-requisites from probability theory, stochastic processes, stochastic integrals and stochastic differential equations.

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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.