Fuzzy-neural model predictive control of a building heating system

Margarita Terziyska; Yancho Todorov; Michail Petrov

doi:10.3182/20061002-4-BG-4905.00012

Fuzzy-neural model predictive control of a building heating system

Margarita Terziyska, Yancho Todorov, Michail Petrov

Not published at VTT

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-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 language	English
Title of host publication	1st IFAC Workshop on Energy Saving Control in Plants and Buildings
Publisher	Elsevier
Pages	69-74
ISBN (Print)	978-3-902661-19-7
DOIs	https://doi.org/10.3182/20061002-4-BG-4905.00012
Publication status	Published - 1 Dec 2006
MoE publication type	A4 Article in a conference publication
Event	International IFAC Workshop on Energy Saving Control in Plants and Buildings, ESC 2006 - Bansko, Bulgaria Duration: 2 Oct 2006 → 5 Oct 2006

Publication series

Series	IFAC Proceedings Volumes
Number	19
Volume	39
ISSN	1474-6670

Conference

Conference	International IFAC Workshop on Energy Saving Control in Plants and Buildings, ESC 2006
Country	Bulgaria
City	Bansko
Period	2/10/06 → 5/10/06

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Keywords

Fuzzy control
Heating systems
Predictive control

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

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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.",

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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. Elsevier, IFAC Proceedings Volumes, no. 19, vol. 39, pp. 69-74, International IFAC Workshop on Energy Saving Control in Plants and Buildings, ESC 2006, Bansko, Bulgaria, 2/10/06. https://doi.org/10.3182/20061002-4-BG-4905.00012

Fuzzy-neural model predictive control of a building heating system. / Terziyska, Margarita; Todorov, Yancho; Petrov, Michail.

1st IFAC Workshop on Energy Saving Control in Plants and Buildings. Elsevier, 2006. p. 69-74 (IFAC Proceedings Volumes; No. 19, Vol. 39).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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N2 - 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.

AB - 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.

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Access to Document

10.3182/20061002-4-BG-4905.00012

Link to publication in Scopus