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In this paper, an adaptive fuzzy controller is synthesized to improve the anti–lock braking system (ABS) performance in the presence of suspension systemeffects. The ABS performance in generating the maximum braking force is mainly affected by the tire normal force applied the suspension system. In thisstudy, an optimization is carried out to obtain the optimal value of longitudinal slip reference value corresponding to the suspension normal force andvehicle speed. The slip optimal value is then imported as the reference input of the fuzzy controller. In this manner, the fuzzy controller is adapted to the tirenormal force, suspension deflection and vehicle speed. Therefore, this controller is aimed at tracking the slip optimal value which is updated by on–line data from suspension system and braking system states. In this study, two quarter car models are used to simulate the ABS and suspension systems behavior.The first being a quarter car suspension model with two degrees of freedom which describes the sprung and unsprung mass vertical dynamic and the latter a quarter car braking model with two degrees of freedom which describe the braking dynamics (vehicle longitudinal dynamic). Simulation of this study is derived during hard braking on a poor quality white noise road. The stopping distance is compared in the cases of fuzzy and adaptive fuzzy ABS control situations while a passive suspension is employed. The results show that the adaptive fuzzy control strategy can be helpful to increase the ABS controller performance so that it decreases the stopping distance in the semi–real situation.<\div>

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