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Energy Efficiency and Tracking Performance Evaluation for Dual-Mode Model Predictive Control of HVAC Systems

[+] Author and Article Information
Zicheng Cai

Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78705
zichengcai@utexas.edu

Asad Ul Haq

Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78705
asadulhaq@utexas.edu

Michael Cholette

Science and Engineering Faculty, Queensland University of Technology, Brisbane, QLD 4001, Australia
michael.cholette@qut.edu.au

Dragan Djurdjanovic

Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78705
dragand@me.utexas.edu

1Corresponding author.

ASME doi:10.1115/1.4040281 History: Received November 29, 2017; Revised April 07, 2018

Abstract

This paper presents evaluation of the energy consumption and tracking performance associated with the use of a recently introduced dual-mode model predictive controller (DMMPC) for control of a heating, ventilation, and air conditioning (HVAC) system. The DMMPC overcomes some key computational and stability limitations of traditional model predictive controllers (MPC) by requiring only a finite number of iterations for the underlying optimization and yet guaranteeing closed-loop stability. The study was conducted using detailed simulations of an HVAC system, which included a multi-zone air loop, a water loop, and a chiller. Energy consumption and tracking performance are computed from the simulations and evaluated in the presence of different types and magnitudes of noise and disturbances. Performance of the DMMPC is compared with a baseline PID control structure commonly used for HVAC system control, and this comparison showed clear and consistent superiority of the DMMPC.

Copyright (c) 2018 by ASME
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