一类高阶非线性系统的混合自适应重复学习控制

针对含有时变和时不变未知参数的高阶非线性系统,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,该方法结合了反馈线性化,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函数,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有效性和可行性.

Adaptive Repetitive Learning Control for a Class of High Order Nonlinear Time-Varying Systems with Mixed Parameters

Combining the pointwise integral mechanism with the feedback linearization approach,a novel adaptive repetitive learning control for high-order nonlinear 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 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.A simulation example illustrates the effectiveness and the feasibility of the proposed method.