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 honlinearly parameterized uncertain systems

作　　者：孙云平[1] 李俊民[1] 李靖[1] 

机构地区：[1]西安电子科技大学理学院,陕西西安710071

出　　处：《控制理论与应用》2009年第2期228-232,共5页Control Theory & Applications

基　　金：国家自然科学基金资助项目(60374015).

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.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.

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 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]