Finite-Time Iterative Learning Control
有限时间迭代学习控制

This paper deals with an iterative learning control approach for uncertain time-varying systems in the presence of initial state errors. A finite time controller is included in the developed learning system, where an initial rectifying action isintroduced for the controller design. The learning system is guaranteed to achieve practical complete tracking with which the tracking error converges to zero over a pre-specified interval, and the piece of trajectory from the starting position can be planned. Both partially- and fully-saturated learning algorithms are examined, respectively. The stability and convergence of the closed-loop system are established by using Lyapunov-like method. The way to carry out the boundedness proof is based on the saturated learning algorithms.