Development of a Model Based Predictive Control System for Heating Buildings

The problems concerning pollution and energy supply have forced Europe to dwindle its consumption. In this contribution, a new control method will be developed based on Model Predictive Control (MPC) to optimally drive a heating system. The goal is to develop a model predictive control for heating in buildings calculating optimal heating inputs for the heating system while assuring a standard level of comfort. The optimization covers the minimization of the difference between the desired temperature and the measured temperature, this for a specific building and a fixed time period. The purpose is to establish a physical model to simulate the real thermal behavior of a basic building. The model needs to be easily adaptable to varying life situations. We propose model predictive controllers which are based on a dynamic model of the building. By means of predictive control, a finite time interval can be optimized, keeping future time steps in mind. Different types of control techniques are discussed: the traditional MPC method and MPC based on Laguerre functions. Both are studied taking into account the constraints on the control signals for the heating system. In the calculations, disturbances as predicted heat fluxes and ambient temperature are taking into account.