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, we propose a novel adaptive repetitive learning control for higher-order nonlinearly parameterized uncertain systems with time-varying and time-invariant parameters. This control can be applied to an uncertain system with time-varying parameters which are varying rapidly and periodically in an unknown compact set. A differential-difference mixed-type adaptive law and an adaptive repetitive learning control law are configured 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.