Neural control for a semi-active suspension of a half-vehicle model Online publication date: Fri, 25-Nov-2005
by M.J.L. Boada, B.L. Boada, B. Munoz, V. Diaz
International Journal of Vehicle Autonomous Systems (IJVAS), Vol. 3, No. 2/3/4, 2005
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.
Online publication date: Fri, 25-Nov-2005
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