Design Neural Control System for Full Vehicle Nonlinear Active Suspension with Hydraulic Actuators

Abstract

The main objective of designed the controller for a vehicle suspension system is to reduce the discomfort sensed by passengers which
arises from road roughness and to increase the ride handling associated with the pitching and rolling movements. This necessitates a very fast
and accurate controller to meet as much control objectives, as possible, this paper deals with an artificial intelligence Neural Control technique to
design a robust controller. The advantage of this controller is that it can handle the nonlinearities faster than other conventional controllers. The
approach of the proposed controller is to minimize the vibration on each corner of vehicle by generating suitable control signals. This control
signals will be used as input to the hydraulic actuators which will generate appropriate control forces to improve the vehicle performances. A full
vehicle nonlinear active suspension system with hydraulic actuators is introduced and tested. The robustness of the proposed controller is being
assessed by comparing with an optimal Fractional Order PIiDd (FOPID) controller. The results show that intelligent neural controller have
improved dynamic response measured by a decreased cost function.

Keywords: Full vehicle, Nonlinear Active Suspension System with Hydraulic Actuators, Neural Controller.