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Artificial neural network based controller for permanent magnet DC motor drives

Conference ·
OSTI ID:415565
; ;  [1]
  1. Memorial Univ. of Newfoundland, St. John`s, Newfoundland (Canada). Faculty of Engineering and Applied Science
This paper introduces a novel approach of designing a controller using multi-layer feed-forward neural network (FFNN) for the speed control of a permanent magnet (PM) dc motor. Artificial neural network (ANN) controller with its massive parallel properties and learning capabilities offers a promising way to solving the problem of system non-linearity, parameter variations and unexpected load excursions associated with a PM dc motor drive system. Self-tuning technique of the controller in real time is achieved through an improved on-line back-propagation training algorithm based on an output error propagation. The proposed ANN controller is implemented with a PM dc motor drive system in the laboratory. The laboratory test results validate the efficacy of the based controller for a high performance PM dc motor drive.
OSTI ID:
415565
Report Number(s):
CONF-9510203--
Country of Publication:
United States
Language:
English

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