DocumentCode :
288698
Title :
Novel adaptive artificial neural networks based speed regulators for PMDC motor drives
Author :
Soliman, Hussein F. ; Sharaf, A.M. ; Mansour, M.M. ; Kandil, S.A. ; El-Shafii, M.H.
Author_Institution :
Dept. of Electr. Eng., New Brunswick Univ., Fredericton, NB, Canada
Volume :
4
fYear :
1994
fDate :
27 Jun-2 Jul 1994
Firstpage :
2550
Abstract :
This paper presents a new adaptive controller for PMDC motor drive using a flexible artificial neural network (ANN) structure. When the ANN regulator is used to control the motor drive directly, the only output available is the speed/position error of the controlled motor. The actual output error of the ANN network is usually unknown. This paper presents a simple and robust training algorithm, which enable the ANN based speed controller to be trained online using the speed and current motor outputs errors. The ANN based speed regulator employs an effective online tuning mechanism based on the actual drive output error; it only requires the knowledge of the speed reference trajectory, past speed error and current deviation variables
Keywords :
DC motor drives; adaptive control; intelligent control; learning (artificial intelligence); neurocontrollers; permanent magnet motors; position control; real-time systems; velocity control; adaptive controller; drive output error; neural networks; online tuning mechanism; permanent magnet DC motor drives; speed reference trajectory; speed regulators; speed/position error; training algorithm; Adaptive systems; Artificial intelligence; Artificial neural networks; Control systems; DC motors; Error correction; Fuzzy logic; Motor drives; Regulators; Traction motors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
Type :
conf
DOI :
10.1109/ICNN.1994.374622
Filename :
374622
Link To Document :
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