An Adaptive Predictor-Based Control Approach for Tracking Control of a Hydraulic Actuator System

Electro-hydraulic actuators offer advantages over traditional hydraulic actuators, particularly for high-precision force or position control, but their nonlinear dynamics complicate modelling and control. This study proposes a predictor-integrated adaptive controller to address these challenges. By combining a proportional-integral-derivative controller with a sliding surface, the system tracks desired trajectories, while a parameter optimization rule minimizes errors. Additionally, a smart grey prediction model with dynamic step size adjusts parameters and generates control signals to reduce noise and disturbances. Simulations show improved accuracy and control performance, with a root mean square error reduction of over 50% compared to traditional control algorithms. This adaptive approach ensures precise control in varying conditions, making it suitable for aerospace, automotive, and robotics applications.