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Proceedings Paper

Generalized model for fuzzy and neural network controllers
Author(s): Syed Ali Akbar; Ramon Parra-Loera
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Paper Abstract

A generalized model is developed for a neural and fuzzy controller. A generalized model for the implementation and performance of a fuzzy and neural network controllers scheme is presented. This new method provides a structure for combining linguistic and numerical information into a common framework. This common framework can be used to implement equivalent fuzzy or neural controllers. This method provides a unified way for implementing equivalent controllers from different sets of information as well as it provides a fair basis for comparing two different controller strategies since they use the same information for both controllers. Also, this model gives freedom to the designer to choose the most appropriate controller regardless of the type of information available. This method shows the best performance when either kind of information alone is incomplete. This method was applied to the truck control problem as a case of study.

Paper Details

Date Published: 5 July 1995
PDF: 7 pages
Proc. SPIE 2484, Signal Processing, Sensor Fusion, and Target Recognition IV, (5 July 1995); doi: 10.1117/12.213019
Show Author Affiliations
Syed Ali Akbar, New Mexico State Univ. (United States)
Ramon Parra-Loera, New Mexico State Univ. (USA) and Univ. Autonoma de Ciudad Juarez (Mexico)


Published in SPIE Proceedings Vol. 2484:
Signal Processing, Sensor Fusion, and Target Recognition IV
Ivan Kadar; Vibeke Libby, Editor(s)

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