An efficient algorithm is proposed for computing the solution to the constrained finite time optimal control （CFTOC） problem for discrete-time piecewise affine （PWA） systems with a quadratic performance index. The...An efficient algorithm is proposed for computing the solution to the constrained finite time optimal control （CFTOC） problem for discrete-time piecewise affine （PWA） systems with a quadratic performance index. The maximal positively invariant terminal set, which is feasible and invariant with respect to a feedback control law, is computed as terminal target set and an associated Lyapunov function is chosen as terminal cost. The combination of these two components guarantees constraint satisfaction and closed-loop stability for all time. The proposed algorithm combines a dynamic programming strategy with a multi-parametric quadratic programming solver and basic polyhedral manipulation. A numerical example shows that a larger stabilizable set of states can be obtained by the proposed algorithm than precious work.展开更多
显式模型预测控制(explicit model predictive control,EMPC)避免了传统的模型预测控制中最为繁琐的反复在线优化过程.显式模型预测控制系统分为离线计算获得每个分区上控制律和在线查找控制律这两个不同阶段.离线计算阶段通过多参数二...显式模型预测控制(explicit model predictive control,EMPC)避免了传统的模型预测控制中最为繁琐的反复在线优化过程.显式模型预测控制系统分为离线计算获得每个分区上控制律和在线查找控制律这两个不同阶段.离线计算阶段通过多参数二次规划(multi-parametric quadratic program,mp-QP)对系统状态空间进行凸划分,并计算得到系统在每个状态分区上的分段仿射(piece-wise affine,PWA)控制律;在线计算阶段通过查表确定系统当前状态所在的分区(即进行点定位运算)从而直接得到相应的控制律.研究工作在于如何快速确定系统当前状态所在的分区,属于在线计算过程范畴.文章在离线计算所得的状态分区数据基础上,根据可达域的思想,设计可达分区点定位算法使在线计算时搜索范围大幅减少,从而显著降低在线计算所需时间,提高EMPC系统的实时性.通过两个仿真实验将可达分区算法与直接查找法相互对比,证明可达分区算法的优势.作为一个应用例子,将文章显式模型预测控制可达分区点定位算法用于直流无刷电机显式模型预测控制,表明所用方法的有效性.展开更多
基金supported by the National Natural Science Foundation of China (60702033)Natural Science Foundation of Zhe-jiang Province (Y107440)
文摘An efficient algorithm is proposed for computing the solution to the constrained finite time optimal control （CFTOC） problem for discrete-time piecewise affine （PWA） systems with a quadratic performance index. The maximal positively invariant terminal set, which is feasible and invariant with respect to a feedback control law, is computed as terminal target set and an associated Lyapunov function is chosen as terminal cost. The combination of these two components guarantees constraint satisfaction and closed-loop stability for all time. The proposed algorithm combines a dynamic programming strategy with a multi-parametric quadratic programming solver and basic polyhedral manipulation. A numerical example shows that a larger stabilizable set of states can be obtained by the proposed algorithm than precious work.
