TY - GEN
T1 - Improved deadbeat predictive current control for open-winding permanent magnet synchronous generators
AU - Wang, Wenfeng
AU - Ma, Yue
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
PY - 2023
Y1 - 2023
N2 - In order to solve the problem of parameter mismatch in the DPCC (deadbeat predictive current control) of open-winding permanent magnet synchronous generators, this paper proposes an IDPCC (improved deadbeat predictive current control) algorithm. By designing a Longberg observer to estimate disturbance error and compensate for the reference voltage of the d, q, and 0 axes, the impact of mismatched inductance parameters on the d, q, and 0 axes is eliminated. Based on the Longberg observer, an incremental model is applied to the d and q axis current predictive control to eliminate the impact of permanent magnet flux mismatch. And a control system model of an open-winding generator was established in the Matlab/Simulink environment, verifying the effectiveness of the algorithm proposed in this paper.
AB - In order to solve the problem of parameter mismatch in the DPCC (deadbeat predictive current control) of open-winding permanent magnet synchronous generators, this paper proposes an IDPCC (improved deadbeat predictive current control) algorithm. By designing a Longberg observer to estimate disturbance error and compensate for the reference voltage of the d, q, and 0 axes, the impact of mismatched inductance parameters on the d, q, and 0 axes is eliminated. Based on the Longberg observer, an incremental model is applied to the d and q axis current predictive control to eliminate the impact of permanent magnet flux mismatch. And a control system model of an open-winding generator was established in the Matlab/Simulink environment, verifying the effectiveness of the algorithm proposed in this paper.
KW - IDPCC
KW - Incremental model
KW - Longberg observer
KW - Open-winding generator
UR - http://www.scopus.com/inward/record.url?scp=85175053972&partnerID=8YFLogxK
U2 - 10.1007/978-981-99-6882-4_65
DO - 10.1007/978-981-99-6882-4_65
M3 - Conference contribution
AN - SCOPUS:85175053972
SN - 9789819968817
T3 - Lecture Notes in Electrical Engineering
SP - 801
EP - 813
BT - Proceedings of 2023 Chinese Intelligent Systems Conference - Volume II
A2 - Jia, Yingmin
A2 - Zhang, Weicun
A2 - Fu, Yongling
A2 - Wang, Jiqiang
PB - Springer Science and Business Media Deutschland GmbH
T2 - 19th Chinese Intelligent Systems Conference, CISC 2023
Y2 - 14 October 2023 through 15 October 2023
ER -