Huang, H.Chen, L.Hu, E.2015-08-112015-08-112015Proceedings of the ... American Control Conference. American Control Conference, 2015, vol.2015-July, pp.256-26197814799868590743-16192378-5861http://hdl.handle.net/2440/93470This paper presents a hybrid model predictive control (MPC) scheme for energy-saving control in commercial buildings. The proposed method combines a linear MPC with a neural network feedback linearisation (NNFL) method. The control model for the linear MPC is developed using a simplified physical model, while nonlinearities associated with the building system are handled by an affine recurrent neural network (ARNN) model through system feedback. The proposed MPC integrates several advanced air-conditioning control strategies, such as an economizer control, an optimal start-stop control, and a pre-cooling control. The developed MPC has been tested in the check-in hall of T-1 building, Adelaide Airport, through both simulation and field experiment. The result shows that the proposed control scheme can achieve a considerable amount of savings without violating occupants’ thermal comfort.en© 2015 AACCConference paper003003267310.1109/ACC.2015.71707450003702592000432-s2.0-84940934678196030Chen, L. [0000-0002-2269-2912]Hu, E. [0000-0002-7390-0961]