Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/93470
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Type: Conference paper
Title: A hybrid model predictive control scheme for energy and cost savings in commercial buildings: simulation and experiment
Author: Huang, H.
Chen, L.
Hu, E.
Citation: Proceedings of 2015 American Control Conference, 2015 / vol.2015-July, pp.256-261
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Issue Date: 2015
Series/Report no.: Proceedings of the American Control Conference
ISBN: 9781479986859
ISSN: 0743-1619
2378-5861
Conference Name: 2015 American Control Conference (ACC) (01 Jul 2015 - 03 Jul 2015 : Chicago, USA)
Statement of
Responsibility: 
Hao Huang, Lei Chen, and Eric Hu
Abstract: This 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.
Rights: © 2015 AACC
RMID: 0030032673
DOI: 10.1109/ACC.2015.7170745
Appears in Collections:Mechanical Engineering conference papers

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