一类时变非线性系统的混合自适应重复学习控制
daptive repetitive learning control for a class of nonlinear time-varying systems with mixed parameters
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。
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.
孙云平、刘赟、李俊民
自动化基础理论自动化技术、自动化技术设备
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
daptive repetitive learning control backstepping approach Lyapunov function periodic parameter adaptive law mixed parametric nonlinear system
孙云平,刘赟,李俊民.一类时变非线性系统的混合自适应重复学习控制[EB/OL].(2006-07-11)[2025-08-16].http://www.paper.edu.cn/releasepaper/content/200607-139.点此复制
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