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Direct adaptive neural control of a quarter-car active suspension system

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3 Author(s)
Pedro, J.O. ; Sch. of Mech., Aeronaut. & Ind. Eng., Univ. of the Witwatersrand, Johannesburg, South Africa ; Dahunsi, O.A. ; Baloyi, N.

This paper presents the design and implementation of a direct adaptive neural network (DANN) based feedback linearization controller for a two degree of freedom (2DOF), quarter-car active vehicle suspension system (AVSS). The main objective is to improve ride comfort and handling quality. The constant gain PID controller (based on Ziegler-Nichols tuning method) is used to benchmark the DANN controller during a suspension travel sinusoidal set point tracking in the presence of deterministic road disturbance. The maximum sprung mass acceleration of the DANN controller was about 2.723ms-2, for the PID, it was 2.676ms-2. The tire deflection was approximately 5mm and 4mm for the DANN and the PID controllers. The performance of the DANN controller was achieved at a marginally higher cost of the control input.

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13-15 Sept. 2011