基于有限时间跟踪微分器的迭代学习控制

针对迭代学习控制（Iterative learning control，ILC）中的初始状态问题，提出了采用有限时间跟踪微分器安排过渡过程方法，根据迭代学习控制中期望轨迹已知的特点，设计了其参数有明显物理意义并且调节方便的有限时间跟踪微分器. 在此基础上，针对一类具有不确定性的非线性时变系统的迭代学习控制问题，提出了具有对不确定项进行估计的迭代学习控制算法，并应用类Lyapunov方法给出了相关定理证明. 仿真结果表明所提出的方法是有效的.

Iterative Learning Control Based on Finite Time Tracking Differentiator

For the initial state problem of iterative learning control (ILC), a method of arranging transition process is presented using finite time tracking differentiators. A finite time tracking differentiator, whose parameters are easy to adjust because of their clear physical meanings, is designed according to the feature of ILC that the desired trajectory is known beforehand. Based on this, an ILC algorithm with estimator for system uncertainty is presented for a class of nonlinear time-varying system with uncertainty. A Lyapunov-like approach is used to prove the corresponding theorems. Simulation results verify the effectiveness of the proposed methods.