基于模糊神经网络的异步电机DTC研究

针对异步电机直接转矩控制在低速时脉动大、开关频率不固定等缺陷,提出了一种基于模糊神经网络的直接转矩控制方案,该方案采用模糊神经网络调节器分别对转矩和磁链进行控制。该控制方法综合了模糊控制和神经网络的优点,原理简单、无需大量专家经验、具有优良的非线性逼近和自适应能力。最后通过仿真实验证明,采用该控制器的异步电机系统动态性能良好、低速脉动小。

Induction Motor DTC Research Based on Fuzzy Neural Network

The asynchronous motor base on direct torque control have some problems, such as ripple at low speed, switching frequency not fixed. So presents a direct torque control program based on fuzzy neural network, which uses fuzzy neural network controller control the torque and flux. The control method combines fuzzy control and neural network advantages, simple in principle, without a lot of expertise, with excellent non-linear approach and adaptive capacity. Finally, through simulation experiments show that asynchronous motor system use the controller is low-speed pulsation and have good static and dynamic performance.