FUZZY-NEURAL MODEL PREDICTIVE CONTROL OF A BUILDING HEATING SYSTEM

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.