NON-LINEAR PREDICTIVE CONTROLLERS FOR THERMAL COMFORT OPTIMIZATION AND ENERGY SAVING

The present work is focused on the study of indoor thermal comfort control problem in buildings equipped with heating systems. The occupants' thermal comfort sensation is addressed here by a comfort index known as PMV (Predict Mean Vote). In this context, two control algorithms are proposed by using only-one-actuator system associated to the heating system. The methods are based on the model predictive control scheme and on the improvement of the PMV index together with energy minimization. Simulation results - obtained by using the weather data file for the city of Curitiba, Brazil - for two case studies: i) variations between low and moderate occupants metabolic rates and ii) variations between moderate and high occupants metabolic rates are presented to validate the proposed methodology in terms of room air temperature, relative humidity and PMV control.