摘  要：开关磁阻电机的转矩脉动是其应用的一个问题。该文应用小波神经网络建立对应开关磁阻电机位置信号的非线性映射，估计转子位置角度，提出利用自适应模糊神经网络学习训练开关磁阻电机转矩逆模型优化期望转矩所需的相电流，采用滑模电流控制器实现电机转矩的低脉动控制，仿真结果表明方法的有效性,能够有效地控制开关磁阻电机转矩按期望变化。
关键词：开关磁阻电机;转矩逆模型;滑模变结构控制;自适应模糊神经网络

Abstract: The torque ripple of switched reluctance motor is a crucial problem in its application. The non-linear reflection of position signal of switched reluctance motor was built up by wavelet neural networks and the rotor position angle is estimated. In addition, in this paper the method was discussed that the torque inverse model of switched reluctance motor was trained by the adaptive-neural networks to optimize the required phase current of expected torque and the low ripple torque control was realized by slide mode current controller. The simulation result proves the validity of this method to effectively control the torque changing of switched reluctance motor.
Key words: switched reluctance motor; torque inverse model; slide mode control; adaptive fuzzy neural network