时变非线性系统迭代学习控制遗忘因子算法

针对迭代学习P型控制算法对初始偏差和输出误差扰动的敏感性问题,研究了一种带有遗忘因子的时变非线性系统的迭代学习控制方法.在有扰动的情况下,利用迭代学习过程记忆的期望轨迹,期望控制以及跟踪误差,通过有界学习增益和批次时变因子设计学习控制器,并基于算子理论给出了控制算法存在的充分必要条件及其收敛性分析,改善了系统的鲁棒性和动态特性.最后以注塑机的注射速度控制仿真验证了本文算法的有效性.

Iterative Learning Control Algorithm with Forgetting Factor for Time - varying Nonlinear Systems

As the P-type iterative learning control algorithm is sensitivity of the output error disturbance and the initial error,the iterative learning control method with forgetting factor used in time-varying nonlinear system is investigated.In the case of the disturbance,by using the memory of the desired trajectory,control and tracking error expectations in the process of iterative learning,the learning controller can be designed through the bounded of learning gain and the batches of time-varying factors,then the necessary and sufficient conditions for the existence and convergence analysis of the control algorithm is given in terms of the operator theory,and the robustness and dynamic performance of the system is improved.Finally,the simulation of the speed control of the injection molding machine proves the effectiveness of the algorithm.