SVM-DTC Control of Induction Motor based on Adaptive Fuzzy Neural Network
Wang Jie1, Ai Hong2
1. College of Electrical and Control Engineering, North China University of Technology, Beijing, 100144; 2. Automation Institute of Beijing Information Science & TechnologyUniversity, Beijing 100192
Abstract：Amethod that basing on Adaptive neuro-fuzzy network (ANFIS) in SVM-DTC Control system of Induction Motoris proposedin this paper. Making the best use of ANFIS' ability of dealing with uncertain nonlinear object and the ability of self-adaptation and self-study, this method could overcome the defects of nonlinear and multi-variable coupling in the system of asynchronous motor effectively. It can also improve the robustness and dynamic performance of the system. The simulation results show that this method could reduce the flux and the torque ripple effectively and has a good performance than traditional DTC system.
王捷, 艾红. 基于自适应模糊神经网络的异步电动机SVM-DTC控制[J]. 电气技术, 2017, 18(9): 40-45.
Wang Jie, Ai Hong. SVM-DTC Control of Induction Motor based on Adaptive Fuzzy Neural Network. Electrical Engineering, 2017, 18(9): 40-45.
2017, Vol. 18 
