Mean square stabilization for stochastic switched fuzzy systems

In this paper, a mean square stabilization criterion for stochastic switched fuzzy (SSF) systems is proposed. SSF system, which differs from existing ones, can often incorporate discrete states, continuous dynamics and randomness as well as their interactions in complex real-world systems. In the beginning, switching parallel distributed compensation controller is introduced. The multiple Lyapunov function methods are adopted to establish the stability results. Moreover, sufficient conditions for mean square stability are presented and stabilizing switching laws of the state-dependent form are designed. Simultaneously, switching techniques are used to derive the criteria, some subsystems are allowed to be unstable. Finally, the elaborated illustrative example demonstrates the effectiveness of the proposed method.