Heating Ventilation and Air Conditioning (HVAC) systems include the equipment used to control the conditions and distribution of indoor air in any closed environment that requires certain variables, such as temperature, humidity, carbon dioxide (CO₂) concentration, etc. to be controlled to levels of human comfort and safety, and to levels that keep machines and other devices in special conditions to protect them or guarantee their best performance. In developed countries, HVAC energy consumption is usually between 25% and 42% of the total energy consumption. Thermal zooning and demand control ventilation have shown improvements in comfort and energy consumption savings. The aim of this thesis is to develop a mathematical model for a HVAC system that will employ an estimated state-feedback control (ESFC) algorithm which guarantee human comfort indoors and savings in terms of energy and required number of sensors. The model describes the dynamic equations for CO₂ concentration and temperature for a building of five rooms. Rooms’ temperature is controlled by adjusting the low temperature air flow coming from a cooling unit with dampers, while rooms’ CO₂ level is controlled by adjusting the percentage of fresh air allowed in the rooms. To illustrate the advantages of the developed control approach, it was compared with other control approaches based on the performance in terms of response, energy consumption, and required number of sensors. The ESFC has the best performance requiring one sensor for temperature and one for CO₂ at a point on the return where all the individual returns from the different rooms have mixed, occupancy sensors in each room are also required. In future work, the ESFC would include humidity and static pressure, also would include an extended Kalman filter to estimate the parameters of an imperfect model and to eliminate the need of occupancy sensors.

Date of publication

Spring 5-4-2021

Document Type




Persistent identifier


Committee members

Nelson Fumo, Nael Barakat, Mohammad Biswas


Master of Science in Mechanical Engineering