Title :
Fuzzy logic and neural net current control on a salient pole permanent magnet synchronous machine
Author :
De Kgnet, Antonius Henricus Maria ; Seixas, Paulo Fernando ; Rodrigues, Thelma Virginia
Author_Institution :
USIMINAS-PUC, Minas, Brazil
Abstract :
In this paper a digital fuzzy logic controller (FLC) is developed to control the sinusoidal currents of a salient pole permanent magnet synchronous machine. This fuzzy controller presents a good performance even at higher speeds, where the e.f.c.m. normally introduces a considerable steady state error in other digital current controllers. After tuning the FLC is replaced by a neural net, trained by the Levenberg-Marquardt method, with considerable reduction in processing time. Simulated and experimental results are presented for the FLC, the neural and a PI controller for performance comparison
Keywords :
control system synthesis; controllers; electric current control; fuzzy control; learning (artificial intelligence); machine control; neurocontrollers; permanent magnet motors; power engineering computing; synchronous motors; Levenberg-Marquardt method; PI controller; digital fuzzy logic controller; fuzzy controller; neural net current control; salient pole permanent magnet synchronous machine; sinusoidal currents control; trained neural net; Current control; Digital control; Fuzzy control; Fuzzy logic; Fuzzy sets; Input variables; Neural networks; Permanent magnet machines; Shape control; Voltage control;
Conference_Titel :
Electric Machines and Drives Conference Record, 1997. IEEE International
Conference_Location :
Milwaukee, WI
Print_ISBN :
0-7803-3946-0
DOI :
10.1109/IEMDC.1997.604173