Modeling of HVAC systems and control using intelligent control approaches

Heating, ventilation, and air conditioning (HVAC) systems refer to equipment, distribution networks, and terminals used in buildings to provide all or one of the fresh air, heating, cooling requirements, and humidity control. HVAC systems are control systems that ensure that the temperature and air quality are in desired conditions in indoor environments. It also gains more importance in applications that require sensitive environmental conditions. In this thesis study, modeling and controlling a variable flow rate two-zone HVAC system was carried out. The HVAC system was controlled using PID, LQR, and Particle Swarm Optimization (PSO) based Linear Quadratic Regulator (LQR) and PSO based Fuzzy Linear Quadratic Regulator (FLQR) methods, one of the intelligent control methods. The temperatures of two different zones were reduced to approximately 7 °C from ambient temperature. The proposed control algorithms were compared and examined using performance criteria in line with the graphical and numerical data obtained from the simulations. When the methods applied to the two-zone HVAC system are examined, the lowest temperature error performance for both zones is obtained using the PSO - FLQR method and MAE criterion (for Zone 1 and Zone 2) and these values are 0.052 oC and 0.034 oC, respectively.