Fuzzy-neural model predictive control of a building heating system

Margarita Terziyska*, Yancho Todorov, Michail Petrov

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

3 Citations (Scopus)

Abstract

This paper describes the development of a Model Predictive Controller with supervision control of a building heating system. A fuzzy-neural model and optimizing procedure as a part of a nonlinear predictive controller are utilized on-line to determine the future values of control actions based on dependence between outdoor and indoor temperatures. A learning algorithm for parameters in fuzzy-neural implementation of the predictive model is additionally applied. Simulation results with a model of a single room heating system demonstrate that a better system performance can be achieved in comparison to classical PID control.

Original languageEnglish
Title of host publicationInternational IFAC Workshop on Energy Saving Control in Plants and Buildings, ESC 2006 - Preprints
PublisherElsevier
Pages69-74
Number of pages6
Volume1
EditionPART 1
ISBN (Print)9783902661197
DOIs
Publication statusPublished - 2006
MoE publication typeA4 Article in a conference publication
EventInternational IFAC Workshop on Energy Saving Control in Plants and Buildings - Bansko, Bulgaria
Duration: 2 Oct 20065 Oct 2006

Publication series

NameIFAC proceedings volumes
Number19
Volume39
ISSN (Electronic)1474-6670

Workshop

WorkshopInternational IFAC Workshop on Energy Saving Control in Plants and Buildings
Abbreviated titleESC
CountryBulgaria
CityBansko
Period02/10/200605/10/2006

Keywords

  • Fuzzy control
  • Heating systems
  • Predictive control

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