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TECHNICAL BRIEFS

Fuzzy Neural Network Control for DC-Motor Micromaneuvering

[+] Author and Article Information
Anthony Tzes, Pei-Yuan Peng

Mechanical, Aerospace, and Manufacturing Engineering Department, Polytechnic University, Brooklyn, NY 11201

J. Dyn. Sys., Meas., Control 119(2), 312-315 (Jun 01, 1997) (4 pages) doi:10.1115/1.2801254 History: Received June 23, 1993; Revised November 17, 1995; Online December 03, 2007

Abstract

The application of a fuzzy neural network controller for compensating the effects induced by the friction in a DC-motor micromaneuvering system is considered in this article. A back-propagation neural network is employed to decrease the effects of the system nonlinearities. The input vector to the neural network controller consists of the time history of the motor angular shaft velocity within a prespecified time window. A fuzzy cell space controller supervises the overall scheme and reduces the amplitude and repetitions of control switchings. Simulation studies are presented to indicate the effectiveness of the proposed algorithm.

Copyright © 1997 by The American Society of Mechanical Engineers
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