一类时变非线性系统的混合自适应重复学习控制
首发时间:2006-07-11
摘要:针对含有时变和时不变未知参数的高阶非线性系统,结合backstepping方法,提出了一种新的自适应控制方法,该方法可以处理参数在一个未知紧集内周期性快时变的非线性系统,通过引进参数周期自适应律,设计了一种自适应控制策略,使跟踪误差在误差平方积分范数意义下渐近收敛于零,通过构造李亚普诺夫函数,给出了闭环系统收敛的一个充分条件。仿真结果说明了该方法的有效性和可行性。
关键词: 自适应重复学习控制 backstepping方法 李雅普诺夫函数 参数周期自适应律 混合型的参数非线性系统
For information in English, please click here
Adaptive repetitive learning control for a class of nonlinear time-varying systems with mixed parameters
Abstract:A novel adaptive repetitive learning control for high-order nonlinear systems with time-varying and time-invariant parameters is proposed by combining the backstepping approach. It can be applied in the time-varying parametric uncertainty systems with unknown compact set, non-vanishing, rapid time-varying, periodic and only the prior knowledge is the periodicity. A periodic mixed adaptive law and an adaptive control law are constructed to ensure the asymptotic convergence of the tracking error in the sense of square error norm. And a sufficient condition of the convergence of the method is also given. A simulation example illustrates the effectiveness of the method.
基金:
论文图表:
引用
No.7557728471152591****
同行评议
共计0人参与
勘误表
一类时变非线性系统的混合自适应重复学习控制
评论
全部评论0/1000