摘要
针对一类非参数不确定系统,提出状态受限迭代学习控制的参考信号初始修正方法,以解决任意初态下的状态受限轨迹跟踪问题.通过构造修正参考信号,利用一种新型的障碍Lyapunov函数设计迭代学习控制系统,采用鲁棒方法与学习方法相结合的策略处理非参数不确定性,经过足够多次迭代后,可实现系统状态在整个作业区间上对修正参考信号的零误差跟踪,以及在预设作业区间上对参考信号的零误差跟踪.同时,将滤波误差约束于预设的界内,并由此实现对系统状态在各次迭代运行过程中的约束.仿真结果表明了本文所提控制方法的有效性.
This paper presents a reference-signal rectifying method of iterative learning control to address the trajectory- tracking problem for a class of state-constrained uncertain sys- tems, in the presence of arbitrary initial states. For design of the iterative learning control scheme, a rectified reference signal is constructed and a new type of barrier Lyapunov function is used. In order to deal with the nonparametric uncertainties, a robust learning approach is applied. It is shown that the closed- loop systemts state follows the rectified reference signal perfectly over the entire time interval as iteration increases. In turn, the system state tracks the reference signal on the specified interval. During each iteration, the filtering-error is constrained in the pre-specified region, and the system state is thus constrained. Numerical results are presented to demonstrate the effectiveness of the learning control scheme.
出处
《自动化学报》
EI
CSCD
北大核心
2017年第8期1470-1477,共8页
Acta Automatica Sinica
基金
国家自然科学基金(61374103
61573320
61573322)
浙江省公益技术研究项目(2016C32093
2017C33155)
浙江省教育厅科研项目(Y201635861)资助~~
关键词
迭代学习控制
初值问题
非参数不确定性
障碍Lyapunov
函数
Iterative learning control, initial condition prob- lem, nonparametric uncertainties, barrier Lyapunov function