Fuzzy-neural model predictive control of a building heating system

Margarita Terziyska, Yancho Todorov, Michail Petrov

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-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 publication1st IFAC Workshop on Energy Saving Control in Plants and Buildings
PublisherElsevier
Pages69-74
ISBN (Print)978-3-902661-19-7
DOIs
Publication statusPublished - 1 Dec 2006
MoE publication typeA4 Article in a conference publication
EventInternational IFAC Workshop on Energy Saving Control in Plants and Buildings, ESC 2006 - Bansko, Bulgaria
Duration: 2 Oct 20065 Oct 2006

Publication series

SeriesIFAC Proceedings Volumes
Number19
Volume39
ISSN1474-6670

Conference

ConferenceInternational IFAC Workshop on Energy Saving Control in Plants and Buildings, ESC 2006
CountryBulgaria
CityBansko
Period2/10/065/10/06

Keywords

  • Fuzzy control
  • Heating systems
  • Predictive control

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  • Cite this

    Terziyska, M., Todorov, Y., & Petrov, M. (2006). Fuzzy-neural model predictive control of a building heating system. In 1st IFAC Workshop on Energy Saving Control in Plants and Buildings (pp. 69-74). Elsevier. IFAC Proceedings Volumes, No. 19, Vol.. 39 https://doi.org/10.3182/20061002-4-BG-4905.00012