A Novel ACI Motor Vector Method based on T-S-FCMAC Neural Network Predictive Control Algorithm

摘要：

In this paper,a novel predictive control algorithm based on T-S-FCMAC neural network is presented for three phase ACI motor control.On the basis of the principle of vector control,T-S-FCMAC neural network is adopted to build predictive model for motor speed and stator torque current,and predictive control algorithm is put forward to design the regulator with golden selection for motor speed.The presented algorithm reduces the error between flux calculation and decouple part so that it improves greatly the performance of system.The simulation shows its effective.

关键词： Takagi-Sugeno model. Fuzzy cerebellar model articulation controller (FCMAC).Model predictive control.Vector control.Golden selection method

作者: Lou Haichuan Dai Wenzhan Lei Meizhen

作者单位: Department of Automatic Control Zhejiang Sci-Tech University Hangzhou ,Zhejiang ,P.R.C.

会议类型: 国际会议

会议名称: 2008 IEEE International Conference on Onformation and Automation(IEEE 信息与自动化国际会议)

会议地点: 张家界

会议语种:英文

页码: 232-237

在线出版日期: 2008-06-20（万方平台首次上网日期，不代表论文的发表时间）