Title :
A robust torque control of induction motor for electric vehicle applications using ANFIS
Author :
Vasudevan, M ; Arumugam, R.
Author_Institution :
Dept. of Electr. & Electron. Eng., Anna Univ., India
Abstract :
Motor parameter variations in electric vehicles using induction motor drive system are larger than in industrial drive system. In this paper, a robust fuzzy torque control system using ANFIS (adaptive neuro-fuzzy inference system) is presented. ANFIS provide simplicity, accuracy and good performance. The block diagram of this system and the membership functions of every fuzzy variable are also given in this paper. The simulation results show that the neuro-fuzzy torque control has better dynamic torque response than the conventional torque control. In addition, the sturdiness of the fuzzy control is proved. Estimation of stator resistance using ANFIS is also presented.
Keywords :
adaptive systems; electric machine analysis computing; electric vehicles; fuzzy control; induction motor drives; inference mechanisms; machine control; neurocontrollers; stators; torque control; ANFIS; adaptive neuro-fuzzy inference system; dynamic torque response; electric vehicles; fuzzy variable; induction motor drive system; industrial drive system; membership function; motor parameter variation; neuro-fuzzy torque control; robust fuzzy torque control system; stator resistance estimation; Adaptive systems; Electric vehicles; Electrical equipment industry; Fuzzy control; Fuzzy systems; Induction motor drives; Induction motors; Programmable control; Robust control; Torque control;
Conference_Titel :
TENCON 2004. 2004 IEEE Region 10 Conference
Print_ISBN :
0-7803-8560-8
DOI :
10.1109/TENCON.2004.1414858
