Model Predictive Control of Servo System Based on Improved Equivalent Input Disturbance
This paper focuses on achieving robust tracking control for servo systems in the presence of mismatched disturbances and measurement noise.It proposes a model predictive control(MPC)method based on an improved equivalent input dis-turbance(EID)approach.The paper starts by designing an EID estimator based on adaptive filtering.This estimator adjusts the bandwidth parameter of the filter ac-cording to the estimated disturbance characteristics,effectively balancing disturbance estimation performance and measurement noise attenuation.Next,considering the impact of disturbance compensation residuals on servo system performance,a robust tracking controller based on MPC is developed.By combining the improved EID and MPC,the proposed method achieves high-performance servo system tracking control while maintaining robust stability of the closed-loop system.Finally,the effectiveness and superiority of the proposed method are verified through comparative simulations and experiments,demonstrating its ability to handle mismatched disturbances and noise in practical scenarios.
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