Adaptive Disturbance Rejection Generalized Predictive Control of Photoelectric Turntable Servo System

In order to enhance the tracking accuracy and disturbance rejection capability in the speed loop of an optoelectronic tracking servo control system, a parameter self-adjusting disturbance rejection generalized predictive control method (STGPC) based on a continuous-time model is proposed in this paper. First, a dynamic model of the servo turntable system is established, and a linear extended state observer (LESO) is designed to perform real-time estimation of internal and external disturbances in the system. Second, a generalized predictive control law incorporating the predictive model, performance metrics, and rolling optimization is systematically derived, where the reference trajectory is generated by a tracking differentiator and the system state is provided in real time by the LESO. Furthermore, a gradient descent method is innovatively introduced to achieve adaptive adjustment in the predictive time domain, and the stability of the closed-loop system is rigorously proven based on Lyapunov theory. Finally, simulation experiments were conducted to verify the tracking performance, disturbance rejection performance, and time-domain parameter self-adjustment effects of the control method. Simulation results show that compared with PID control and traditional linear generalized predictive control (LGPC), the proposed STGPC method reduces speed tracking residuals by 73.79% and 51.04%, respectively, enhances disturbance suppression capability for speed vibration disturbances by 50.55% and 47.55%, respectively, and enhances compensation capability for friction torque disturbances by 68.03% and 59.33%, respectively. The system demonstrates outstanding velocity tracking accuracy and disturbance rejection while exhibiting good robustness against system parameter perturbations.