Projection algorithm based adaptive iterative learning control for a class of discrete-time systems

In this paper, adaptive iterative learning control scheme is designed for a class of discrete-time uncertain systems with random initial state and unknown control gain. The system uncertainty is generated by a stable high-order internal model. The proposed controller incorporates a projection algorithm. Through rigorous analysis, the asymptotical learning convergence along the iteration axis in a finite time interval can be guaranteed, provided the desired trajectory is iteration-varying.