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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.
Aiming at a class of high-order nonlinear parameterized systems, a new self-adaptive repetitive learning control method is proposed by using the piece-wise integral scheme. Combining with feedback linearization, this method can process parameters in a fast A kind of adaptive control strategy is designed by introducing the differential-differential hybrid parameter adaptive law, so that the generalized tracking error converges to zero asymptotically in the sense of error squared norm. By constructing Lyapunov functional, A sufficient condition for the convergence of closed-loop system is given. The simulation results show the feasibility of this method.