Output-Dependent Switching Laws for Quadratic Stabilization of Switched Linear Stochastic Systems

We consider global quadratic stabilization in probability for switched linear stochastic systems (SLSS). Assuming that no single subsystem is globally quadratically stable in probability (GQS-P), we propose both static and dynamic output-dependent switching laws such that the entire switched system is GQS-P. In the case of static output-dependent switching, the sufficient condition is expressed by a set of matrix inequalities, while the design of dynamic output-dependent switching is based on a convex combination of subsystems and a robust Luenberger observer for each subsystem. A numerical example is provided to show effectiveness of the proposed approach.