Adaptive Admittance Flexible Control Based on a Fuzzy Predictor for Active Suspension with Electrohydraulic Actuators

Abstract This paper presents an adaptive admittance flexible control approach for a multi-axle heavy-duty wheeled vehicle (MHWV) equipped with an electrohydraulic actuator active suspension. The proposed method aims to enable flexible interaction control between the vehicle and uneven roads, enhancing the load-bearing stability and ride comfort of the MHWV over rough terrain. To reduce the effects of nonlinearity in the hydraulic system and uncertainties in the environmental stiffness on the force-tracking performance during interaction control, an adaptive fuzzy predictor (AFP) is proposed in this study for the nonlinear identification of the hydraulic suspension systems. The predictor is employed to estimate the nonlinear relationship between the output force of the hydraulic actuator and its relative displacement during vehicle-road interactions, thus enabling multistep-ahead prediction of the actuator output force. The Levenberg-Marquardt optimization algorithm is used to produce an adaptive admittance controller with precise force-tracking performance by optimizing and adaptively adjusting the admittance controller parameters based on the output force errors and the desired force within the prediction range. Finally, the validity of the AFP is confirmed on a three-axle heavy-duty wheeled experimental prototype (THWEP). The results of the vehicle experiments indicate that the proposed method has better force-tracking performance than does the conventional constant-parameter admittance controller. Thus, the ride comfort, load-bearing stability, and ability to retain the attitude of the THWEP are enhanced.