Intelligent learning controllers for dynamic non-linear systems using neural networks

Iterative learning learning controllers are a good choice in repetitive trajectory tracking tasks because they do not need identification of a nonlinear system which by itself is a difficult task. Starting with zero knowledge about the system, this type of learning controller takes a certain number of iterations before converging to the desired trajectory. Intelligence is incorporated in the iterative learning controllers using neural networks for a class of nonlinear systems. Our proposed method is proved to be very effective in improving the convergence of the tracking error. The proposed method is very general and applicable to most of the iterative learning controllers without modifying their simple learning structures.