Abstract: A back-propagation neural network is applied to learning control of nonlinear control systems. By training the neural networks using back-propagation algorithm, optimal state feedback control of nonlinear systems can be realized. This paper presents a novel learning control mechanism for a class of nonlinear systems, which does not depend the model of nonlinear control system. Simulation results show that the new scheme is efficient for large unknown nonlinearity.