Institute of Electrical and Electronics Engineers Inc.;New York, NY: IEEE
摘要:
摘要： A Takagi-Sugeno-Kang type fuzzy neural network with asymmetric membership function (TSKFNN-AMF) is proposed in this study for the fault-tolerant control of a six-phase permanent-magnet synchronous motor (PMSM) drive system. First, the dynamics of the six-phase PMSM drive system is described in detail. Then, the fault detection and operating decision method is briefly introduced. Moreover, to achieve the required control performance and to maintain the stability of a six-phase PMSM drive system under faulty condition, the TSKFNN-AMF control, which combines the advantages of a Takagi-Sugeno-Kang type fuzzy logic system and an asymmetric membership function, is developed. The network structure, online learning algorithm using a delta adaptation law, and convergence analysis of the TSKFNN-AMF are described in detail. Furthermore, to enhance the control performance of the proposed intelligent fault-tolerant control, a 32-bit floating-point digital signal processor TMS320F28335 is adopted for the implementation of the proposed fault-tolerant control system. Finally, some experimental results are illustrated to show the validity of the proposed TSKFNN-AMF fault-tolerant control for the six-phase PMSM drive system. 其他題名： TPEL 出版者： New York, NY: IEEE 出版日期： 2013-07-01 出處： IEEE transactions on power electronics, 2013-07, Vol.28 (7), p.3557-3572 資源來源： IEEE Electronic Library (IEL) 版權： 2014 INIST-CNRS 版權： Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Jul 2013 識別號： ISSN: 0885-8993 識別號： EISSN: 1941-0107 識別號： DOI: 10.1109/TPEL.2012.2224888 識別號： CODEN: ITPEE8
