Adaptive Neural Network Control For Vehicle Active Suspension System with Unknown Dead-Zones

This paper presents the development of an adaptive neural network (NN) control method for non-linear quarter-vehicle model which has the characteristics of road disturbance, parameter uncertainties and unknown dead-zone. Considering the dead-zone slopes as a model uncertainty, an adaptive NN control scheme is developed depending on back stepping technique. In this paper, uncertain non-linear functions in suspension systems are estimated by NNs. Then again, the minimal learning parameters can ensure that the computation and the complexity of system are exceedingly reduced. The stability and the signals boundedness of vehicle suspension system are proved. Finally, a given simulation example shows the feasibility of the designed approach.