Generating a fuzzy logic system from optimized numerical models

S. Ari, H. E. Khalifa, J. F. Dannenhoffer, P. Wilcoxen, C. Isik

Research output: Chapter in Book/Entry/PoemConference contribution

1 Scopus citations

Abstract

This paper presents a novel approach to the optimization of a system using soft computing. In many instances optimum solutions to complex problems can be calculated using analytic or numeric approaches, but with significant barriers for practical use, such as computational complexity, sensitivity to parameter variations, and necessity to use many measured variables. In this study, a traditional optimization method is used to calculate off-line optimum solutions to an indoor environmental control problem at numerous operating points. These solutions are, in turn, used as exemplars to train an intelligent system such as a fuzzy logic system or a neural network, resulting in a control system whose behavior exhibits the desirable features of the family of optimum solutions. It has been shown that this methodology (named Modeled Optimized System - MOS) results in a controller for an indoor environmental system, which improves occupant satisfaction, saves energy, and can be implemented in a practical fashion.

Original languageEnglish (US)
Title of host publicationNAFIPS 2007
Subtitle of host publication2007 Annual Meeting of the North American Fuzzy Information Processing Society
Pages452-457
Number of pages6
DOIs
StatePublished - 2007
EventNAFIPS 2007: 2007 Annual Meeting of the North American Fuzzy Information Processing Society - San Diego, CA, United States
Duration: Jun 24 2007Jun 27 2007

Publication series

NameAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS

Other

OtherNAFIPS 2007: 2007 Annual Meeting of the North American Fuzzy Information Processing Society
Country/TerritoryUnited States
CitySan Diego, CA
Period6/24/076/27/07

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

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