开闭环PD型快速迭代学习控制方法及其在直流电动机中的应用

Fast Algorithm of Open-Closed Loop PD-Type Iterative Learning Control and Its Application in Direct Current Motor

针对一类非线性系统的学习控制问题，提出了一种开闭环PD型快速迭代学习控制方法。此学习控制方法利用了系统当前的跟踪误差信号和前次迭代控制的跟踪误差信号，以及它们的微分信号，同时采用可调比例系数，根据系统误差的变化及时地调节比例系数，从而使目标的跟踪能力得到提高。通过分析给出了此快速迭代学习算法收敛的条件，直流电动机的仿真应用说明了此学习控制方法对于非线性系统具有较强的有效性和较好的可行性。

A fast algorithm of open-closed loop PD-type iterative learning control （ILC） for a class of nonlinear system was proposed in this paper. In the algorithm, the system＇s current tracking error and previous tracking error and their differential signals were all used to update the control law meanwhile. Moreover, the control law utilized adjustable proportion parameters, which could be adjusted according to the system＇s errors Therefore, the capability of the target tracking was greatly improved. Then, the sufficient condition for the convergence of the proposed fast iterative learning algorithms was given. Finally simulation results for direct current motor showed the validity and feasibility of the proposed algorithm