MODELING OF THE BUILDING THERMAL BEHAVIOUR USING NONLINEAR SYSTEM IDENTIFICATION

Abstract

Model-based predictive control is a very modern powerful control strategy that uses a model of the plant to predict its future behaviour and has been in focus of researchers in the area of buildings energy management. The aim of this paper is to develop and analyze NARX (Nonlinear AutoRegressive with eXogenous inputs) structure for the modeling of the building thermal behavior. A database was generated using simulation in EnergyPlus software. The NARX identification model was designed using the MATLAB System Identification Toolbox. The input variables analyzed in this paper are: outdoor temperature, heating or cooling power, and direct solar radiation. Simulation results demonstrate that the proposed nonlinear structure can be effective identification tool for development of nonlinear buildings predictive control.