TY - GEN
T1 - Intelligent complementary sliding mode fault tolerant control for six-phase motor drive system using TSK type FNN
AU - Hung, Ying Chih
AU - Lin, Faa Jeng
PY - 2013
Y1 - 2013
N2 - An intelligent complementary sliding mode control (ICSMC) is proposed in this study for the fault tolerant control of a six-phase permanent magnet synchronous motor (PMSM) drive system with open phases. First, the dynamics of the six-phase PMSM drive system with a lumped uncertainty is described in detail. Then, the fault detection and operating decision method are briefly introduced. Moreover, to improve the required control performance and to maintain the stability of the six-phase PMSM drive system under faulty condition, the ICSMC is developed. In this approach, a TSK type fuzzy neural network with asymmetric membership function (TSKFNN-AMF) estimator with accurate approximation capability is employed to estimate the lumped uncertainty. Furthermore, the adaptive learning algorithms for the online training of the TSKFNN-AMF are derived using the Lyapunov theorem to guarantee the closed-loop stability. In addition, to enhance the control performance of the proposed intelligent fault tolerant control, a 32-bit floating-point digital signal processor (DSP), TMS320F28335, is adopted for the implementation of the proposed fault tolerant control system. Finally, some experimental results are illustrated to demonstrate the validity of the proposed fault tolerant control for the six-phase PMSM drive system via ICSMC.
AB - An intelligent complementary sliding mode control (ICSMC) is proposed in this study for the fault tolerant control of a six-phase permanent magnet synchronous motor (PMSM) drive system with open phases. First, the dynamics of the six-phase PMSM drive system with a lumped uncertainty is described in detail. Then, the fault detection and operating decision method are briefly introduced. Moreover, to improve the required control performance and to maintain the stability of the six-phase PMSM drive system under faulty condition, the ICSMC is developed. In this approach, a TSK type fuzzy neural network with asymmetric membership function (TSKFNN-AMF) estimator with accurate approximation capability is employed to estimate the lumped uncertainty. Furthermore, the adaptive learning algorithms for the online training of the TSKFNN-AMF are derived using the Lyapunov theorem to guarantee the closed-loop stability. In addition, to enhance the control performance of the proposed intelligent fault tolerant control, a 32-bit floating-point digital signal processor (DSP), TMS320F28335, is adopted for the implementation of the proposed fault tolerant control system. Finally, some experimental results are illustrated to demonstrate the validity of the proposed fault tolerant control for the six-phase PMSM drive system via ICSMC.
KW - asymmetric membership function
KW - fault tolerant control
KW - Six-phase permanent magnet synchronous motor
KW - sliding mode control
KW - TSK type fuzzy neural network
UR - http://www.scopus.com/inward/record.url?scp=84903557770&partnerID=8YFLogxK
U2 - 10.1109/iFuzzy.2013.6825412
DO - 10.1109/iFuzzy.2013.6825412
M3 - 會議論文篇章
AN - SCOPUS:84903557770
SN - 9781479903863
T3 - iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications
SP - 71
EP - 76
BT - iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications
PB - IEEE Computer Society
T2 - iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications
Y2 - 6 December 2013 through 8 December 2013
ER -