Linear stochastic systems are successfully used to provide mathematical models for real processes in fields such as aerospace engineering communications manufacturing finance and economy this monograph presents a useful methodology for the control of such stochastic systems with a focus on robust stabilization in the mean square linear quadratic control the disturbance attenuation problem and robust stabilization with respect to dynamic and parametric uncertainty systems with both . This second edition of mathematical methods in the robust control of linear stochastic systems includes a large number of recent results in the control of linear stochastic systems more specifically the new results presented are a unified and abstract framework for riccati type equations arising in the stochastic control. Linear stochastic systems are successfully used to provide mathematical models for real processes in fields such as aerospace engineering communications manufacturing finance and economy this monograph presents a useful methodology for the control of such stochastic systems with a focus on robust stabilization in the mean square linear quadratic control the disturbance attenuation problem and robust stabilization with respect to dynamic and parametric uncertainty systems with both . This second edition of mathematical methods in the robust control of linear stochastic systems includes a large number of recent results in the control of linear stochastic systems more specifically the new results presented are a unified and abstract framework for riccati type equations arising in the stochastic control