Model predictive control for optimizing indoor air temperature and humidity in a direct expansion air conditioning system

The direct expansion (DX) air conditioning (A/C) system has been widely used to control indoor air quality (IAQ) and maintain thermal comfort simultaneously. Generally, conventional controls for IAQ are designed by using on/off control or proportional integral (PI) control. In this paper, a model predictive control (MPC) is proposed to guarantee thermal comfort and indoor air quality. The DX A/C plant is modeled into a nonlinear system, with speed of compressor and supply fan being regarded as control inputs. To facilitate MPC design, the nonlinear model is linearized around its working point. The proposed MPC is designed based on the linearized model. Simulation results indicate that, by using the proposed MPC, the indoor air temperature and humidity could achieve their comfort levels simultaneously.