Multiobjective State-Feedback Control for Stochastic Large-Scale System via LMI Approach

This paper investigates a state-feedback control such that multiobjective performance requirements for stochastic large-scale systems can be achieved. The required objectives consist of disturbance attenuation, upper bound on state covariance, and regional constraint on pole placement. Based on the feasibility of a matching condition, three controller design approaches, the decoupled, centralized, and decentralized control, are addressed accordingly. By assuming suitable form of the quadratic Lyapunov function, the constructive conditions to deliver the desired multiobjective performance for the considered stochastic large-scale systems are derived in terms of linear matrix inequalities (LMIs). The effectiveness of the proposed methods is illustrated by a numerical example.

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