TY - GEN
T1 - An Enhanced Active Disturbance Rejection Control of PMSM Based on ILC and Parameter Self-tuning
AU - Hua, Qiang
AU - Liu, Anming
AU - Xie, Anhuan
AU - Kong, Lingyu
AU - Zhang, Dan
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9
Y1 - 2020/9
N2 - Conventional model-based permanent magnet synchronous motor (PMSM) drivers suffer deteriorated dynamic performance from the inward and outward disturbance. A new control method is proposed to improve the robustness of PMSM drivers in transient-state operation in this paper. Ant colony optimization (ACO) is utilized to tune parameters of active disturbance rejection control (ADRC). By using ACO's self-learning ability and multiple iterative calculations, the optimal solution can be quickly calculated, thereby reducing the difficulty of ADRC parameter adjustment. Besides, the torque ripple changes periodically with the rotor position and causes speed fluctuations, which reduces the PMSM system's dynamic performance. Usually, the PI controller and iterative learning control (ILC) in parallel are used to suppress torque fluctuations. However, it is very sensitive to the system uncertainty and external interference, that is, it will be paralyzed by non-periodic interference. Therefore, the ILC-ADRC is proposed in this paper to both reduce the ripple and guarantee robustness. The simulation results demonstrate the superior robustness of the proposed ADRC to that of the traditional method in transientstate and steady-state operations.
AB - Conventional model-based permanent magnet synchronous motor (PMSM) drivers suffer deteriorated dynamic performance from the inward and outward disturbance. A new control method is proposed to improve the robustness of PMSM drivers in transient-state operation in this paper. Ant colony optimization (ACO) is utilized to tune parameters of active disturbance rejection control (ADRC). By using ACO's self-learning ability and multiple iterative calculations, the optimal solution can be quickly calculated, thereby reducing the difficulty of ADRC parameter adjustment. Besides, the torque ripple changes periodically with the rotor position and causes speed fluctuations, which reduces the PMSM system's dynamic performance. Usually, the PI controller and iterative learning control (ILC) in parallel are used to suppress torque fluctuations. However, it is very sensitive to the system uncertainty and external interference, that is, it will be paralyzed by non-periodic interference. Therefore, the ILC-ADRC is proposed in this paper to both reduce the ripple and guarantee robustness. The simulation results demonstrate the superior robustness of the proposed ADRC to that of the traditional method in transientstate and steady-state operations.
KW - ACO
KW - ADRC
KW - automatic parameter tuning
KW - ILC
KW - time delay
UR - http://www.scopus.com/inward/record.url?scp=85096840294&partnerID=8YFLogxK
U2 - 10.1109/CACRE50138.2020.9230080
DO - 10.1109/CACRE50138.2020.9230080
M3 - Conference article published in proceeding or book
AN - SCOPUS:85096840294
T3 - Proceedings - 5th International Conference on Automation, Control and Robotics Engineering, CACRE 2020
SP - 427
EP - 433
BT - Proceedings - 5th International Conference on Automation, Control and Robotics Engineering, CACRE 2020
A2 - Zhang, Fumin
A2 - Liu, Lu
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Automation, Control and Robotics Engineering, CACRE 2020
Y2 - 19 September 2020 through 20 September 2020
ER -