Smith-predictor-based variable-universe fuzzy position control for hydraulic active suspension

In view of the common problems of time delay, nonlinearity, multi-parameter coupling, and external disturbances in vehicle hydraulic active suspension systems, a Smith-predictor-based variable-universe fuzzy self-tuning PID position control strategy (SVUFMS-PID) is proposed. By employing a Smith predictor to effectively predict and compensate for the system delay and introducing variable-universe fuzzy control to enhance the self-tuning capability of the PID parameters, the proposed approach improves the system’s adaptability to varying operating conditions and external disturbances. First, a mathematical model of the vehicle hydraulic active suspension system is established; subsequently, a simulation model is constructed on the MATLAB/Simulink platform, and simulation experiments are conducted. The results indicate that, compared with PID, fuzzy PID, and uncompensated control methods, the proposed control strategy delivers superior performance in suppressing overshoot, shortening settling time, reducing position error, and enhancing system robustness. Even under parameter perturbations and external disturbances, the method maintains high control accuracy and system stability, providing an effective solution for achieving high-performance position control of vehicle hydraulic active suspension systems and further improving the safety, stability, and comfort of the suspension system.