本文针对一类时滞非线性系统提出一种采样迭代学习控制算法, 严格证明了该算法的指数收敛性.当系统满足所给出的条件时, 跟踪误差以指数速率收敛至一个与采样周期有关的误差范围内.

A sampled-data iterative learning control algorithm is proposed for a class of nonlinear continuous-time systems with state delay. A sufficient condition for the exponential convergence of the proposed control algorithm is presented. The actual output exponentially converges to a neighborhood of the desired output in the entire time span. The neighborhood is small enough if the sampling period is small enough.