Fault-Tolerant Control for Six-Phase PMSM Drive System via Intelligent Complementary Sliding-Mode Control Using TSKFNN-AMF

An intelligent complementary sliding-mode control (CSMC) (ICSMC) is proposed in this paper 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 is briefly introduced. Moreover, a CSMC is designed to stabilize the fault-tolerant control of the six-phase PMSM drive system. Furthermore, 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 Takagi-Sugeno-Kang-type fuzzy neural network with asymmetric membership function (TSKFNN-AMF) estimator with accurate approximation capability is employed to estimate the lumped uncertainty. In addition, the adaptive learning algorithms for the online training of the TSKFNN-AMF are derived using the Lyapunov theorem to guarantee the closed-loop stability. Additionally, to enhance the control performance of the proposed intelligent fault-tolerant control, a 32-b 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 demonstrate the validity of the proposed fault-tolerant control for the six-phase PMSM drive system via ICSMC.