Self-tuning Control for Air Conditioning in a Room with Varying Temperature and Imperfectly Mixed Air

This study aims to control indoor temperatures in an air-conditioned room to ensure the occupant’s thermal comfort while minimizing energy consumption. In the literature, controlled simulations of air conditioning systems usually assume that the indoor air is perfectly mixed. This assumption provides little information on spatial temperature and air flow. By contrast, this study deals with imperfectly mixed air. A computational fluid dynamics method is used to model an air-conditioned room and links this model with controllers. A self-tuning controller can monitor plant changes based on recursive estimation and adjusts control parameters to meet desired performance. Therefore, this study develops self-tuning controllers to control room temperature. Disturbances of varying temperature are exerted to investigate control performance. This paper compares the performance of a self-tuning linear quadratic controller and a self-tuning proportional-integral-derivative (PID) controller. Simulation results show that both controllers track desired temperatures well. Compared with the self-tuning PID controller, the self-tuning linear quadratic controller yields less overshoot with a slower response. The proposed method in this study is validated by experimental results.