多面体不确定线性系统具有约束满足保证的预测控制(英文)

Predictive control for polytopic uncertain linear systems with guaranteed constraints satisfaction

基于不变集理论 ,拓展了Chiscil等人提出的约束不变预测控制方法 (IC PC) ,提出了一种适用于带约束多面体不确定线性系统的预测控制的框架 .其关键在于为针对标称系统设计的在线优化问题附加适当的额外的鲁棒可行约束 .若优化问题在初始阶段可行 ,则此约束可保证在线优化问题始终可行 ,从而保证了实际系统中约束条件的始终满足 .同时提出了闭环系统鲁棒稳定的一个充分条件 ,可为成本函数的选择提供指导以保证预测控制器的鲁棒镇定 .

Based on the invariant set theory, invariance constraint predictive control (IC PC) first proposed by Chiscil et al, is extended and generalized to a framework of model predictive control for constrained linear systems with polytopic uncertainty. The crucial point is to reformulate online optimization problem corresponding to nominal model with an appropriate additional robust and feasible constraint. It is shown that in this configuration feasibility of online optimization problem as well as satisfaction of constraints for the real plant can be guaranteed in all time steps if the optimization problem is feasible at the initial stage. Moreover, a sufficient condition of robust stability is given for closed loop uncertain system, which provides a guide to the choice of cost function to guarantee robust stability.