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This paper investigates the robust output feedback model predictive control (ROFMPC) for the discrete-time linear system with norm-bound uncertainty and disturbance. An LMI approach is proposed in this paper, and its computational burden is much less than the approach of previous work. Besides, in previous work, the estimation error set is updated online at each sampling time by the set-membership state estimation algorithm, which may lose recursive feasibility. This paper overcomes the drawback by imposing a new updating condition. The closed-loop system is asymptotically stable by the recursive feasibility of the optimization problem. A numerical example demonstrates the advantage of the proposed approach.

Robust Output Feedback Model Predictive Control for Systems With Norm-Bounded Uncertainty: An LMI Approach