基于输入状态稳定的离散广义系统预测控制

针对一类具有持续扰动和输入约束的离散广义系统, 研究其鲁棒预测控制器的设计问题. 将输入状态稳定的概念引入广义系统预测控制, 在quasi-min-max 性能指标下, 提出了广义系统双模鲁棒预测控制器的设计方法, 证明了基于双模鲁棒预测控制器的闭环广义系统输入状态稳定, 且具有正则、因果性. 数值仿真结果验证了所提出方法的有效性.

Model predictive control of discrete-time singular systems based on input-to-state stability

Robust model predictive control (MPC) is studied for a class of discrete-time singular system subject to persistent disturbance and input constrains. The notion of input-to-state stability is introduced to the model predictive control of singular systems. The design method of the singular system dual-mode MPC is proposed under the index of quasi-min-max. On the basis of the proposed dual-mode MPC approach, it can be proved that the closed-loop discrete-time singular system is input-to-state stable. Finally, the numerical simulation result shows the feasibility and the effectiveness of the proposed method.