Research of iterative learning control system based on neural network

Convergence rate is the core problem for iterative learning control. The paper presents a new design method of iterative control system based on neural network. Fixed learning gain will make the learning speed slower and the iterative times more. Neural network can reduce the huge computing burden and fasten the convergent rate of right value largely compared with least square method. So the algorithm that the parameters of controller are optimized by NN is adopted in this paper. This method not only improves disturbance and robustness of the controlled system, but also fully exerts the intellectualized virtue of ILC without precise model. The optimized control method is applied to nonlinear system. The simulation result is given.