Title :
Sensorless vector control of induction motors in fuel cell vehicle using a neuro-fuzzy speed controller and an online artificial neural network speed estimator
Author :
Jalili, Kamran ; Farhangi, Shahrokh ; Saievar-Iranizad, Esmaiel
Author_Institution :
R&D Center, Iran Khodro Co., Tehran, Iran
Abstract :
A sensorless speed control method for induction motors in a fuel cell vehicle is presented. An artificial neural network (ANN) estimates the speed, and a neuro-fuzzy controller (NFC) is used in the speed control loop to overcome the nonlinearity of the plant. A PI controller controls the motor flux and the NFC determines the required torque. The tuning of the NFC is simple and this is one of the advantages of NFCs compared with the conventional PI controllers. In addition, the nonlinear behavior of the NFC increases its robustness against variation of parameters in the plant. The speed estimation is done by a two-layer online neural network in the rotating coordinate fixed with rotor flux. The ANN estimator has a simple structure, and its parameters are adjusted online. The simulation and experimental results are given to prove the effectiveness of this approach
Keywords :
fuzzy control; induction motors; learning (artificial intelligence); machine control; multilayer perceptrons; neurocontrollers; robust control; state estimation; tuning; two-term control; velocity control; PI controller; fuel cell vehicle; induction motors; neuro-fuzzy speed controller; nonlinear behavior; nonlinearity; online artificial neural network speed estimator; robustness; sensorless vector control; tuning; two-layer online neural network; Artificial neural networks; Fuel cell vehicles; Fuzzy control; Fuzzy logic; Induction motors; Machine vector control; Robustness; Sensorless control; Torque control; Velocity control;
Conference_Titel :
Control Applications, 2001. (CCA '01). Proceedings of the 2001 IEEE International Conference on
Conference_Location :
Mexico City
Print_ISBN :
0-7803-6733-2
DOI :
10.1109/CCA.2001.973874
