For perturbed continuous-time systems, this paper proposes a robust model predictive control (RMPC) strategy for the regulation problem, exploiting a sliding mode disturbance observer. The main advantage is that it effectively enables the RMPC to be designed based on a model with reduced uncertainties. The proposed sliding mode observer (SMO) is finite-time convergent allowing the estimation error of the additive disturbance to be explicitly bounded by a predictable and decreasing limit. Due to the compensation of the estimated disturbance, the uncertainty that the RMPC has to handle is reduced from the original disturbance to the estimation error of the disturbance. This ensures all the admissible state trajectories are limited within a shrinking neighborhood of the origin and the steady-state error is therefore reduced. Simulation results show the effectiveness of the proposed method.

对于扰动的连续时间系统，本文针对调节问题提出了鲁棒模型预测控制 (RMPC) 策略，利用滑模扰动观测器。主要优点是它有效地使 RMPC 能够基于模型进行设计，减少了不确定性。所提出的滑模观测器 (SMO) 是有限时间收敛的，允许加性扰动的估计误差明确受可预测和递减限制的限制。由于对估计扰动的补偿，RMPC要处理的不确定性从原来的扰动减少到扰动的估计误差。这确保了所有允许的状态轨迹都限制在原点的缩小邻域内，因此减少了稳态误差。