Title :
Artificial intelligence applications in direct torque control
Author :
Cruz, Pedro Ponce ; Paredes, Jessica Pilar Santos
Author_Institution :
Inst. Tecnologico y de Estudios Superiores de Monterrey, Mexico
Abstract :
The purpose of this paper is to show a new direct torque control (DTC) scheme that allows to improve the performance of a sensorless induction motor (IM) speed control in terms of less stator flux and currents distortions, keeping a constant switching frequency in the inverter. It is also shown a fuzzy logic application for tuning the PI speed controller, The work proposes a complete DTC scheme using two different stator resistance estimators, one of them is a neural network (ANN) and the other one is an adaptive neuro-fuzzy methodology to build a sugeno fuzzy estimator. Experimental and simulation results have been carried out, showing the advantages of the new scheme.
Keywords :
PI control; angular velocity control; controllers; fuzzy control; fuzzy neural nets; induction motor drives; invertors; machine control; torque control; PI speed controller; adaptive neuro-fuzzy methodology; artificial intelligence application; constant switching frequency; current distortion; direct torque control; fuzzy logic application; inverter; neural network; sensorless induction motor; speed control; stator flux distortion; stator resistance estimator; Artificial intelligence; Fuzzy logic; Induction motors; Inverters; Sensorless control; Stators; Switching frequency; Torque control; Tuning; Velocity control;
Conference_Titel :
Power Electronics and Drive Systems, 2003. PEDS 2003. The Fifth International Conference on
Print_ISBN :
0-7803-7885-7
DOI :
10.1109/PEDS.2003.1283149
