Abstract: In order to overcome the weakness of explicitly calculating the manipulated input according to the first-order differential equation about the controlled plant in the common model control(CMC) scheme,we propose a common model control method based on neural networks,which can embed the process model into the controller by the inverted control method with neural network.It can guarantee the(realizability) of the common model control scheme based on neural networks.The reference trajectory is a classic second-order curve.As the radial basis function is much superior in control system,the neural network in the control scheme is the radial basis function neural network(RBFNN).The parameters of CMC based on neural network have very explicit physics meaning and it is very easy to tune for the controller.The simulation results show the effectiveness of the nonlinear common model controller based on RBFNN.