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中文摘要：
针对一类参数未知的周期非线性时滞系统的输出跟踪控制问题，设计了一种周期自适应迭代学习跟踪控制算法，该方法利用信号置换的思想重组系统，并在假设未知时变参数和参考输出的周期具有已知最小公倍数的情况下，将时滞以及其他不确定的时变项合并为一个周期性的辅助时变参数新变量，进而用周期自适应算法来估计该辅助量。通过构造一个Lyapunov—Krasovskii型复合能量函数，分析了系统的收敛性，证明了经过多次重复迭代学习，所有闭环信号有界且输出跟踪误差收敛，最后通过构造数值实例进行了仿真验证。理论分析和仿真结果表明，该算法简单有效，对于非线性时滞系统的跟踪问题具有很好的控制效果。
英文摘要：
A cyclical adaptive iterative learning control algorithm is proposed for the output tracking control matter of a periodic time- delay nonlinear systems with unknown time-varying parameters, By using the signal replacement theory on the assumption that the un- known time-varying parameters and the expected output have a lowest common multiple which is known, combine the delay and other unknown time-varying parameters into a new auxiliary parameter which is periodic and time-varying, and then use the periodic adaptive algorithm to estimate the parameters. A lyapunov-Krasovskii type composite energy function is constructed to analysis the convergence of the system, and prove that all the closed-loop signals are bounded and the tracking error is convergent after repeating the iterative learn- ing. Finally by an example is designed to simulate. Theoretical analysis and simulation results show that the algorithm is simple and ef- fective , and has a very good control effect for nonlinear systems with time delay tracking problem.
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