Iterative Learning Control for a Class of Nonlinear Systems
一类非线性系统的迭代学习控制

The iterative learning control (ILC) is considered for a class of nonlinear systems, for which the dynamic nonlinearity grows up not faster than a polynomial as the state diverges and the observation equation is corrupted by noise. The control sequence cannot directly feed to the system but first has to pass through a nonlinear function such as the dead-zone, pre-load, and saturation etc. The iterative learning control sequence is recursively defined, and its boundedness and optimal tracking property are proved in the paper.