Active suspension design for vehicles using neural networks

This paper presents and active suspension design for vehicles using the concept of neural networks. The dynamic model is described by a system with six degrees of freedom including nonlinearities of the spring and damping forces. The application of a neural network to nonlinear systems affords some abilities to process and to learn the information in parallel, and to recognize some optional patterns. In the proposed design, the system neural network and the neural network controller are used, and the active control forces are determined by learning the vertical velocities of the vehicle body and by minimizing the output of the system neural network. The effectiveness of the proposed method is confirmed by the improved control performance, and by comparison with the method of the passive control.