Title :
A novel ACI motor vector method based on T-S-FCMAC neural network predictive control algorithm.
Author :
Haichuan, Lou ; Wenzhan, Dai ; Meizhen, Lei
Author_Institution :
Dept. of Autom. Control, Zhejiang Sci-Tech Univ., Hangzhou
Abstract :
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.
Keywords :
control engineering computing; electric machine analysis computing; electric motors; fuzzy control; machine vector control; neural nets; predictive control; ACI motor vector method; Terms-Takagi-Sugeno model; fuzzy cerebellar model articulation controller; motor speed; neural network predictive control algorithm; stator torque current; Machine vector control; Motor drives; Neural networks; Prediction algorithms; Predictive control; Predictive models; Rotors; Stators; Tellurium; Torque control; Fuzzy cerebellar model articulation controller (FCMAC); Golden selection method; Model predictive control; Takagi-Sugeno model; Vector control;
Conference_Titel :
Information and Automation, 2008. ICIA 2008. International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-2183-1
Electronic_ISBN :
978-1-4244-2184-8
DOI :
10.1109/ICINFA.2008.4608002
