Robust Model Predictive Control for Fuzzy Systems Subject to Actuator Saturation

In this paper, a robust fuzzy model predictive control (MPC) scheme is presented for a class of discrete-time nonlinear systems which can be described by uncertain T-S fuzzy models subject to actuator saturation. The system uncertainties under consideration are assumed to be time-varying and norm-bounded. A sufficient condition of minimizing upper bound of the cost function and asymptotical stability of the closed-loop system is established based on Lyapunov function. The proposed controller is obtained by using semi-definite programming (SDP) which can be easily solved by means of linear matrix inequalities (LMIs). Finally, a numerical example is given to verify the feasibility and efficiency of the proposed method.