@Article{, title={Adaptive Neuro Fuzzy Inference Controller for Full Vehicle Nonlinear Active Suspension Systems}, author={A. Aldair and W. J. Wang}, journal={Iraqi Journal for Electrical And Electronic Engineering المجلة العراقية للهندسة الكهربائية والالكترونية}, volume={6}, number={2}, pages={97-106}, year={2010}, abstract={The main objective of designed the controllerfor a vehicle suspension system is to reduce the discomfortsensed by passengers which arises from road roughnessand to increase the ride handling associated with thepitching and rolling movements. This necessitates a veryfast and accurate controller to meet as much controlobjectives, as possible. Therefore, this paper deals with anartificial intelligence Neuro-Fuzzy (NF) technique todesign a robust controller to meet the control objectives.The advantage of this controller is that it can handle thenonlinearities faster than other conventional controllers.The approach of the proposed controller is to minimizethe vibrations on each corner of vehicle by supplyingcontrol forces to suspension system when travelling onrough road. The other purpose for using the NF controllerfor vehicle model is to reduce the body inclinations thatare made during intensive manoeuvres including brakingand cornering. A full vehicle nonlinear active suspensionsystem is introduced and tested. The robustness of theproposed controller is being assessed by comparing withan optimal Fractional Order PIλDμ (FOPID) controller.The results show that the intelligent NF controller hasimproved the dynamic response measured by decreasingthe cost function.

} }