摘要
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.
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 timevarying, 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.
出处
《系统工程理论与实践》
EI
CSCD
北大核心
2007年第11期104-110,共7页
Systems Engineering-Theory & Practice
基金
国家自然科学基金(60374015)
