Experimental study of a model predictive control system for active chilled beam (ACB) air-conditioning system

Active chilled beams (ACB) are gaining popularity worldwide as a potentially energy-efficient air-conditioning technology for buildings. However, the control of ACB system is challenging, as it needs to handle multiple cooling coils and the relatively slow response to cooling load dynamics. This paper reports the implementation of a model predictive control (MPC) system for an ACB system, which employs a linear white-box building model for building energy and indoor condition predictions. A multiple-objectives function is employed in the MPC controller to optimize the energy efficiency in air-conditioning system and indoor thermal comfort while fulfilling the constraints of indoor comfort range (−0.5