Study on a Recurrent Functional Link-based Fuzzy Neural Network Controller with Improved Particle Swarm Optimization

摘要：

A recurrent functional link-based fuzzy neural network controller with improved particle swarm optimization is proposed to control the mover of a permanent-magnet synchronous motor (PMSM) servo drive to track periodic reference trajectories. First,a recurrent functional link-based fuzzy neural network is proposed to control the PMSM. and the connective weights of the recurrent functional link-base neural network,the mean value and standard deviation of Gaussian function are trained online by recurrent algorithm. Moreover,an improved particle swarm optimization (IPSO) is adopted in this study to adapt the learning rates to improve the learning capability and increase the speed of constringency. Finally,the control performance of the proposed method is verified by the simulated results.

关键词： particle swarm optimization recurrent function fuzzy neural network permanent magnet synchronous motor

作者: Zhirong Guo Shunyi Xie Wei Gao

作者单位: Department of Weaponry Engineering Naval University of Engineering Wuhan,China Department of weaponr Department of Weaponry Engineering Naval University of Engineering Wuhan,China Department of weaponry Engineering Naval Bengbu Petty Officer Academy Bengbu,China

会议类型: 国际会议

会议名称: 2009 9th International Conference on Electronic Measurement & Instruments(第九届电子测量与仪器国际会议 ICEMI2009)

会议地点: 北京

会议语种:英文

页码: 3223-3228

在线出版日期: 2009-08-16（万方平台首次上网日期，不代表论文的发表时间）