Dynamic Error Improved Model-Free Adaptive Control Method for Electro-Hydraulic Servo Actuators in Active Suspensions with Time Delay and Data Disturbances

The Electro-Hydraulic Servo Actuator for Active Suspensions (ASEHSA) plays a decisive role in shaping the holistic performance of vehicle suspension systems through its dynamic response speed and control precision. However, achieving high-performance control of ASEHSA still faces challenges. On one hand, existing model-based control methods are highly sensitive to parameter uncertainties and unmodeled nonlinear hydraulic dynamics, which can easily lead to reduced robustness in practical applications. On the other hand, traditional model-free strategies have limited time-delay compensation capabilities and often struggle to balance overshoot and settling time under delayed and disturbed conditions. To resolve this challenge, this study proposes an improved model-free adaptive control method that incorporates the differentiation of the tracking error (DE-IMFAC). Within the framework of traditional model-free adaptive control (MFAC), this approach reconfigures the time-delay term from an explicit form in the control law to implicit management, substantially mitigating the influence of time delays on system control performance. At the same time, by refining the performance criterion function and integrating a tracking error differentiation term together with dynamic weighting factors, the dynamic performance and adjustment flexibility of the controller are significantly enhanced. Additionally, by leveraging the characteristic equation of discrete autonomous systems and compression mapping theory, the BIBO stability of the DE-IMFAC control system and the monotonic convergence of the tracking error are rigorously established through theoretical analysis. Simulation and experimental results demonstrate that, compared with PID and traditional MFAC methods, DE-IMFAC significantly reduces integral absolute error, overshoot, settling time, and maximum position tracking error, while improving disturbance rejection capability. This approach does not depend on an accurate mathematical model of the ASEHSA system and maintains robust dynamic performance under complex operating environments characterized by time delays and data disturbances, providing a practical solution for ASEHSA and related industrial control systems.