Modeling of doubly salient permanent magnet motor based on ANFIS
Qiang Sun, Ming Cheng · 2005
In this paper, the modeling based on adaptive-network-based fuzzy inference system (ANFIS) for doubly salient permanent magnet motor is developed for the first time. In the ANFIS, the hybrid learning algorithm combining the gradient method and the least square method is improved. The result of simulation shows that the modeling is of quick convergence and high accuracy. This model offers a possibility for the on-line real-time control of doubly salient permanent magnet motor.