Neural control for a semi-active suspension of a half-vehicle model. (28th November 2005)

• Record Type: Journal Article
• Authors: Boada, M.J.L.; Boada, B.L.; Munoz, B.; Diaz, V.
• Is Part Of: International journal of vehicle autonomous systems. Volume 3:Number 2/3/4(2005)
• Page Start: 306
• Page End: 329
• Publication Date: 2005-11-28
• Subjects: continuous reinforcement learning -- half-vehicle model -- neural networks -- semi-active suspension vehicle -- ride comfort -- tyre-ground contact -- simulation -- vehicle suspension -- autonomous vehicle systems; Autonomous vehicles -- Periodicals; Motor vehicles -- Technological innovations -- Periodicals; Motor vehicles -- Electronic equipment -- Periodicals; Robots -- Control systems -- Periodicals; Intelligent transportation systems -- Periodicals; 629.20285
• Languages: English
• ISSNs: 1471-0226

Abstract

This paper presents a reinforcement learning algorithm using neural networks which allows a vehicle with semi-active suspension to improve continuously not only the ride comfort but also the tyre/ground contact. The proposed controller learns online, so that the system can adapt to changes produced in the environment. The neural controller has been studied using a half-vehicle model. Different road profiles have been tested to prove the robustness and reliability of the proposed semi-active suspension system. Simulation results show the effectiveness of our algorithm.