Asynchronous Fuzzy Control for a Class of Constrained Fuzzy Stochastic Switching Systems via Bumpless MPC

This paper addresses the problem of bumpless stabilization for a class of T-S fuzzy hidden Markovian jump systems with bounded inputs and states. The asynchronous scenario between the real mode and the observed one under consideration is described by hidden Markovian chains. Moreover, the stabilizing controller dependent on both the fuzzy rule and the observed mode is constructed. By virtue of the bumpless model predictive control, the controller not only maintains the system within constraints but also reduces excessive bumps of system states in switching instants. Then, relying on the stochastic stability criteria, a numerically attainable receding horizon optimization problem is established to obtain the recursive feasible and stabilizing controller with the smooth evolution of states by introducing some mathematical techniques. Finally, demonstrating the validity and potential of the developed control strategy is achieved through the presentation of a numerical example.