一类未知非线性系统的智能迭代学习控制

从自适应的角度设计迭代学习控制，将神经网络引入迭代学习控制中。学习控制与自适应控制相结合，使得对网络权值的学习和跟踪控制同时进行，克服 了经典迭代学习控制的一些缺陷。基于Lyapunov直接方法，证明了整个控制系统的稳定并实现了任意精度的跟踪。实例仿真结果说明了算法 的有效性及其所具有的优点。

Intelligent iterative learning control for a class of unknown nonlinear systems

The iterative learning control(ILC) is designed from the viewpoint of adaptive control. The neural network is introduced into ILC. The learning control is incorporated with the adaptive control, so the tracking control could be processed with the learning of weight simultaneously. Some defects of traditional ILC are avoided. Based on the Lyapunov direct method, the stability of the control system is shown and arbitrary output tracking accuracy is achieved. The effectiveness and advantage of the proposed algorithm are illustrated through a simulation example.