一类基于时间-迭代信号的切换系统ILC策略

Iterative learning control strategy for a kind of switched systems based on time-iteration signals

针对切换系统在不同学习周期内子系统间随意切换,存在初始漂移和不确定外界干扰时其动力学行为不易控制的问题,提出了一种微分型迭代学习控制算法。借助λ-范数以及Bellman-Gronwall不等式理论,分析控制算法的学习性态。通过数值模拟验证系统有效性,结果表明:在一定条件下,切换规则在时间-迭代域内随机变化时,即使系统有初始状态漂移且受到外界不确定干扰,控制算法的学习性能良好。

A novel differential iterative learning control(ILC)algorithm is proposed to solve the problem that the dynamical behavior of a class of switched systems is difficult to be controlled when there exist arbitrary switches of the swithing system between subsytems in different learning periods,initial shift and uncertain external interference.With the help ofλ-norm and Bellman-Gronwall inequality theory,the learning performance of the control scheme was analyzed.The effectiveness of the system is verified by numerical simulation.The results show that the concerned control law works well under some given conditions,even if the systems have initial state drift and are interfered by external uncertainties when the switching rules vary randomly in the time-iteration domain.