| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 721192 | IFAC Proceedings Volumes | 2006 | 6 Pages |
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.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
