太原理工大学学报2012，Vol.43Issue(2)：158-162,5.
粒子群算法优化神经网络的异步电机转速估计
Asynchronous Motor Speed Estimation Methods Based on Neural Network Optimized by PSO
邹敢 1李涛 1肖仁鑫1
作者信息
- 1. 昆明理工大学机电工程学院,昆明650093
- 折叠
摘要
Abstract
In vector-controlled system of asynchronous motor, detection for speed is essential, and the detection precision affects the system greatly. In this paper, the features of common schemes for sensorless estimation of motor speed were discussed and a method to estimate motor speed by neural network was propested in which particle swarm optimization(PSO) was used to optimize initial weights and thresholds of the neural network. Furthermore, a vector-controlled system of asynchronous motor was designed by Matlab/Simulink. The simulation results show that the method estimated motor speed, exhibiting good dynamic performance and strong robustness to the variation of motor parameters.关键词
BP神经网络/粒子群算法/矢量控制/电机转速估计Key words
neural network/particle swarm optimization(PSO)/ vector control/motor speed estimation分类
信息技术与安全科学引用本文复制引用
邹敢,李涛,肖仁鑫..粒子群算法优化神经网络的异步电机转速估计[J].太原理工大学学报,2012,43(2):158-162,5.
