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 |
|---|---|
| Pages (from-to) | 69-74 |
| Journal | IFAC Proceedings Volumes |
| Volume | 39 |
| Issue number | 19 |
| DOIs | |
| 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 |
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Keywords
- Fuzzy control
- Heating systems
- Predictive control
Cite this
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Fuzzy-neural model predictive control of a building heating system. / Terziyska, Margarita; Todorov, Yancho; Petrov, Michail.
In: IFAC Proceedings Volumes, Vol. 39, No. 19, 01.12.2006, p. 69-74.Research output: Contribution to journal › Article in a proceedings journal › Scientific › peer-review
TY - JOUR
T1 - Fuzzy-neural model predictive control of a building heating system
AU - Terziyska, Margarita
AU - Todorov, Yancho
AU - Petrov, Michail
PY - 2006/12/1
Y1 - 2006/12/1
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.
KW - Fuzzy control
KW - Heating systems
KW - Predictive control
UR - http://www.scopus.com/inward/record.url?scp=67449092600&partnerID=8YFLogxK
U2 - 10.3182/20061002-4-BG-4905.00012
DO - 10.3182/20061002-4-BG-4905.00012
M3 - Article in a proceedings journal
VL - 39
SP - 69
EP - 74
JO - IFAC-PapersOnLine
JF - IFAC-PapersOnLine
SN - 2405-8971
IS - 19
ER -