Robust Model Predictive Control for Uncertain Systems with Nonlinear Disturbance and State-delay

A robust model predictive control approach for a class of uncertain continuous systems with nonlinear disturbance and state-delay is proposed. The designed robust controller guarantees the closed-loop system asymptotically stable and the receding horizon performance index online minimum. Based on receding optimization principle of predictive control, the infinite time domain optimization problem is converted into a convex optimization problem by using the Lyapunov stability theory and the linear matrix inequality (LMI) method. At the same time, some sufficient conditions for the stability of system are given. The feasibility of the optimization problem is ensured via the selected appropriate Lyapunov function, which guarantees the robust stability of the system. Finally, simulation example verifies the effectiveness of the proposed robust predictive control strategy.