Active Disturbance Rejection Control Based Sensorless Model Predictive Control for PMSM

Abstract

Improving tracking performance in speed controllers for permanent-magnet synchronous motor (PMSM) drive systems is critical due to internal challenges such as parameter variations, model uncertainty, and external disturbances like load changes. This paper proposes a new method that combines sensorless model predictive control (MPC) with active disturbance rejection control (ADRC), employing an extended state observer (ESO) as a key component of the ADRC. Notably, the proposed ADRC-MPC control integrates the advantages of MPC, such as good time response, high robustness against load variation, and a low effect of parameter variation in comparison to conventional control methods like field-oriented control (FOC). The ADRC-MPC reduces torque and flux ripples and also reduces torque and flux irregularities as well as current harmonics, which presents a major drawback in direct torque control (DTC). The proposed control with finite set model predictive control (FS-MPC) eliminates the PWM modulation and the complexity of continuous control set model predictive control (CCS-MPC). In the outer loop, the ADRC-MPC and the ESO present a very good solution. It presents a lower processing requirement than other controllers, especially the fuzzy logic controller (FLC), and also presents a consistent dynamic behavior across the entire operating range, contrary to the PID. The ADRC with ESO presents a promising solution to these challenges. The effectiveness of the proposed method is demonstrated through numerical simulations using MATLAB/Simulink software and experiments on a 3-kW surface-mounted PMSM drive system. both simulation and experimental results under different conditions show the effectiveness of the proposed approach.