一类高阶非线性系统的混合自适应重复学习控制  

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

作　　者：孙云平[1] 李俊民[1] 王元亮[1] 

机构地区：[1]西安电子科技大学理学院,西安710071

出　　处：《系统工程理论与实践》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)

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.

关 键 词：混合型参数 非线性系统 自适应控制 重复学习控制 LYAPUNOV函数 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]