增广吸引域快速预测控制算法

EFFICIENT MPC ALGORITHM WITH LARGER ATTRACTION REGION

针对具有输入约束的离散时间线性系统,提出一种增广吸引域的快速模型预测控制(MPC)算法.首先,通过增广状态空间模型离线计算MPC增广吸引域.其次,设计了MPC线搜索优化算法求解在线优化问题.该算法具有提前终止能力和保证性能指标迭代单调递减.同时,给出了MPC线搜索算法的局部收敛性和闭环系统渐近稳定性结论.最后,通过仿真验证本文算法的有效性.

An efficient MPC algorithm with larger attraction region is presented for discrete-time linear systems subject to input constraints. Firstly, the larger at- traction regions of MPC are computated by augment state-space models. Then, the line-search optimization algorithm within the MPC framework is designed to solve on-line optimization problem. This algorithm guarantees the early termination and monotonically decrease properties of the cost performances. Meanwhile, the local con- vergence of the line-search optimization algorithm in MPC and asymptotic stability of close-loop systems are proved. Finally, a numerical simulation shows the effectiveness of the algorithm.