一类非线性参数化系统自适应重复学习控制

Adaptive repetitive learning control for a class of nonlinearly parameterized uncertain systems

中文关键词  非线性参数化系统  混合型参数  自适应控制  重复学习控制  Lyapunov泛函

英文关键词  nonlinearly parameterized uncertain systems  mixed parametric  adaptive control  repetitive learning control  Lyapunov functional

中文摘要

      针对一类高阶非线性参数化系统，利用分段积分机制，提出了一种新的自适应重复学习控制方法，该方法结合反馈线性化，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，通过引进微分-差分混合型参数自适应律，设计了一种自适应控制策略，使广义跟踪误差在误差平方范数意义下渐近收敛于零，通过构造Lyapunov泛函，给出了闭环系统收敛的一个充分条件。实例仿真结果说明了该方法的可行性。

英文摘要

      Combining the pointwise integral mechanism with the feedback linearization approach, a novel adaptive repetitive learning control for high-order Nonlinearly Parameterized Uncertain Systems with time-varying and time-invariant parameters is proposed. It can be applied to the time-varying parametric uncertainty systems with unknown compact set, rapid time-varying，periodic and where the prior knowledge is the periodicity only, A differential-difference mixed-type adaptive law and an adaptive repetitive learning control one are constructed to ensure the asymptotic convergence of the extended tracking error in the sense of square error norm. Also, a sufficient condition of the convergence of the method is given by constructing a Lyapunov functional。A simulation example illustrates the feasibility of the proposed method