首页> 外文会议>International Conference on Frontiers of Manufacturing and Design Science >Rotor Speed Identification of PMSM on DTC System Based on PSO and CMAC Neural Network Algorithms
【24h】

Rotor Speed Identification of PMSM on DTC System Based on PSO and CMAC Neural Network Algorithms

机译:基于PSO和CMAC神经网络算法的DTC系统的PMSM转子速度识别

获取原文

摘要

Both the PSO (particle swarm optimization) for global search algorithm and the CMAC (cerebella model articulation controller) algorithm are used in the speed loop of direct torque control system in the permanent magnet synchronous motor. Firstly, the PSO algorithm is applied to search the optimal PID parameters in the domain space, and then the CMAC neural network is adopted to learn and train of the results which derive from the output of the PSO algorithm to furthermore optimize the PID parameters which can improve stability of the system. The DTC control system based on PSO with CMAC algorithmic and the traditional DTC (direct torque control) control system are established and simulated in the MATLAB circumstance whose results were all compared. It revels that the DTC control system based on PSO with CMAC algorithmic is fast response, ideal flux, and good anti-jamming.
机译:全球搜索算法的PSO(粒子群优化)和CMAC(小脑式型铰接控制器)算法用于永磁同步电动机的直接扭矩控制系统的速度环中。首先,将PSO算法应用于在域空间中搜索最佳PID参数,然后采用CMAC神经网络学习和训练从PSO算法的输出导出的结果,进一步优化了可以的PID参数提高系统的稳定性。基于PSO的DTC控制系统具有CMAC算法和传统的DTC(直接扭矩控制)控制系统,并在MATLAB环境中模拟,其结果得到了比较。它陶醉了基于PSO的DTC控制系统具有CMAC算法的快速响应,理想的通量和良好的抗干扰。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号