TY - JOUR
T1 - Improved Iterative Learning Direct Torque Control for Torque Ripple Minimization of Surface-Mounted Permanent Magnet Synchronous Motor Drives
AU - Mohammed, Sadeq Ali Qasem
AU - Choi, Han Ho
AU - Jung, Jin Woo
N1 - Publisher Copyright:
© 2005-2012 IEEE.
PY - 2021/11
Y1 - 2021/11
N2 - This article presents an improved iterative learning direct torque control (IL-DTC) to remarkably minimize the torque ripples for a surface-mounted permanent magnet synchronous motor (SPMSM) drive. Unlike the conventional IL-DTC, the proposed IL-DTC significantly attenuates the torque ripples by effectively suppressing the repetitive disturbances using the speed and load torque compensating terms in the improved error dynamics via the improved feedback control terms and iterative learning control terms. Further, it has a simple structure and fast dynamic response due to the direct control of the torque and flux. The stability is verified through the convergence of speed errors to zero as the iteration index goes to infinity. The comparative results via MATLAB/Simulink and a prototype SPMSM test-bed with TI-TMS320F28335-DSP demonstrate the improved control performance (e.g., less torque ripples, faster transient response, smaller overshoot/undershoot, and smaller steady-state error) over the conventional IL-DTC under critical load/speed conditions with severe model parameter uncertainties.
AB - This article presents an improved iterative learning direct torque control (IL-DTC) to remarkably minimize the torque ripples for a surface-mounted permanent magnet synchronous motor (SPMSM) drive. Unlike the conventional IL-DTC, the proposed IL-DTC significantly attenuates the torque ripples by effectively suppressing the repetitive disturbances using the speed and load torque compensating terms in the improved error dynamics via the improved feedback control terms and iterative learning control terms. Further, it has a simple structure and fast dynamic response due to the direct control of the torque and flux. The stability is verified through the convergence of speed errors to zero as the iteration index goes to infinity. The comparative results via MATLAB/Simulink and a prototype SPMSM test-bed with TI-TMS320F28335-DSP demonstrate the improved control performance (e.g., less torque ripples, faster transient response, smaller overshoot/undershoot, and smaller steady-state error) over the conventional IL-DTC under critical load/speed conditions with severe model parameter uncertainties.
KW - Direct torque control (DTC)
KW - Iterative learning control (ILC)
KW - Repetitive disturbances
KW - Surface-mounted permanent magnet synchronous motor (SPMSM)
KW - Torque ripple minimization (TRM)
UR - http://www.scopus.com/inward/record.url?scp=85100466231&partnerID=8YFLogxK
U2 - 10.1109/TII.2021.3053700
DO - 10.1109/TII.2021.3053700
M3 - Article
AN - SCOPUS:85100466231
SN - 1551-3203
VL - 17
SP - 7291
EP - 7303
JO - IEEE Transactions on Industrial Informatics
JF - IEEE Transactions on Industrial Informatics
IS - 11
M1 - 9334416
ER -