Robust model predictive control of time-delay systems

A robust model predictive control (MPC) is proposed for the discrete-time linear time-delay systems with constrained control input, where the uncertainties also known as polytope exist in state matrices and input matrices. The sufficient conditions of stability and a new upper bound on the robust performance index are presented based on Lyapunov-Krasovskii function. At each sampling time optimal control action is computed by minimizing the upper bound on "worst-case" of an infinite horizon quadratic objective function subject to constraints on inputs, moreover, receding horizon implementation of feasible solutions guarantees closed-loop stability. The simulation results verify the effectiveness of the proposed method. It is shown that, based on linear matrix inequalities (LMIs) constraints, it is easy to get the robust model predictive control for the uncertain time-delay systems and is suitable for practical application.