TY - GEN
T1 - Torque disturbance observer based model predictive control for electric drives
AU - Mei, Xuezhu
AU - Lu, Xiaoquan
AU - Davari, Alireza
AU - Jarchlo, Elnaz Alizadeh
AU - Wang, Fengxiang
AU - Kennel, Ralph
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/4/19
Y1 - 2018/4/19
N2 - Model predictive control (MPC) based electric drive systems has faster dynamics and can achieve similar performance as field oriented control (FOC) and direct torque control (DTC) based systems though much smaller control frequency is applied. In this work, model inverse deadbeat based MPC is applied, which maintains the fast dynamics of the model forward finite control set MPC (FCS-MPC) and has even simpler structure. However, since it still keeps the outer speed proportional-integral (PI) controller, integration time for speed and torque response is required when load torque variations occurs. To improve system dynamics and stability by reducing response time and torque ripples against load disturbances, a torque disturbance observer (TDO) is designed. The effectiveness and good overall performance of the proposed system is verified through simulations.
AB - Model predictive control (MPC) based electric drive systems has faster dynamics and can achieve similar performance as field oriented control (FOC) and direct torque control (DTC) based systems though much smaller control frequency is applied. In this work, model inverse deadbeat based MPC is applied, which maintains the fast dynamics of the model forward finite control set MPC (FCS-MPC) and has even simpler structure. However, since it still keeps the outer speed proportional-integral (PI) controller, integration time for speed and torque response is required when load torque variations occurs. To improve system dynamics and stability by reducing response time and torque ripples against load disturbances, a torque disturbance observer (TDO) is designed. The effectiveness and good overall performance of the proposed system is verified through simulations.
KW - disturbance observer
KW - electric drives
KW - model predictive control
UR - http://www.scopus.com/inward/record.url?scp=85050348321&partnerID=8YFLogxK
U2 - 10.1109/PEDSTC.2018.8343847
DO - 10.1109/PEDSTC.2018.8343847
M3 - Conference contribution
AN - SCOPUS:85050348321
T3 - 9th Annual International Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2018
SP - 499
EP - 504
BT - 9th Annual International Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th Annual International Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2018
Y2 - 13 February 2018 through 15 February 2018
ER -