Robust constrained model predictive control using linear matrix inequalities
Automatica (Journal of IFAC)
Multi-model predictive control based on the Takagi-Sugeno fuzzy models: a case study
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Informatics and computer science intelligent systems applications
Automatica (Journal of IFAC)
Reliable LQ fuzzy control for nonlinear discrete-time systems via LMIs
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Fuzzy Systems
Brief Robust one-step receding horizon control of discrete-time Markovian jump uncertain systems
Automatica (Journal of IFAC)
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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.