Disturbance Estimation-Based Robust Model Predictive Position Tracking Control for Magnetic Levitation System

Abstract

This article presents an improved equivalent input disturbance observer-based model predictive control (IEIDO-based MPC) scheme for position tracking control of a magnetic levitation system. It overcomes the problem of the position tracking performance degradation for the magnetic levitation system in the presence of time-varying disturbances. To enhance the accuracy of estimation, an IEIDO is first proposed to estimate both the system states and the time-varying equivalent input disturbance. The estimations of IEIDO are then integrated into the MPC design for output position prediction. Afterward, an explicit analytical form of the optimal predictive controller is obtained to achieve the optimized tracking performance, as well as the fine robustness against lumped time-varying equivalent input disturbance. Rigorous stability analysis shows that the closed-loop system is stable. Simulation and experimental results demonstrate the effectiveness of the proposed method as compared with the conventional EID and Luenberger observer-based integral MPC approaches.