Model Predictive Control For T-S Fuzzy System With Random Actuator Saturation And Packet Losses

This paper studies model predictive control(MPC) for Takagi-Sugeno(T-S) fuzzy system with randomly occurring actuator saturation and packet losses. The nonlinearity of the actuator saturation is transformed into a set of convex hulls, the packet losses are assumed to obey the rules of Bernoulli distribution. Both non-parallel-distributed-compensation(nonPDC) and parallel-distributed compensation(PDC) strategies are adopted to design the controller for the considered system. It can be indicated that the non-PDC strategy leads to a faster convergence speed than using the PDC one. Simulation example is provided to illustrate the proposed method.