Vehicle suspension vibration control using recurrent neural networks

Abstract

This paper presents an application of vibration control to a half-car model using recurrent neural networks. The robust vibration control is formulated as equality constrained optimization problem. Simulation results show that the close-loop system has good response performance in the presence of disturbances generated by an isolated bump. The study shows potential in using neural networks for the active vibration control in precision machine design.