Supervisor Fuzzy Logic Controller for HVAC System of S.J Carew Building at Memorial University

Abdo-Allah, Almahdi and Iqbal, Tariq and Pope, Kevin (2019) Supervisor Fuzzy Logic Controller for HVAC System of S.J Carew Building at Memorial University. European Journal of Electrical Engineering & Computer Science, 3 (4). ISSN 2736-5751

[img] [English] PDF - Published Version
Available under License Creative Commons Attribution Non-commercial.

Download (1MB)


One of the most important characteristics contributing to the thermal management efficiency of commercial, industrial, institutional or home environments is the optimal functioning of HVAC (heating, ventilation, air conditioning) systems. In addition to using supervisor controllers for balancing comfort level in a building, the majority of today’s HVACs employ nonlinear time variance controllers when dealing with a variety of disturbances. This paper investigates both current and potential HVAC systems at Memorial University’s S. J. Carew building, St. John’s, Newfoundland. The study investigates the viability of algorithm-based supervisor fuzzy logic controllers (SFLC) for the control of the building’s four air-handling units (AHUs) used to manage the interior environment. Along with temperature, the SFLCs also control the AHUs’ fan speeds and CO2 concentrations modifying hot water and air flow rates. This work presents models of damper positions, fan speeds and globe valves that have been built in accordance with current rates of air and hot water flow in the S. J. Carew building. Based on these specifications, a novel method of SFLC adaptation using fuzzy rules has been devised. The novel system aims to better balance the performance level of the Carew building’s HVAC system on a floor-by-floor basis. The overall results indicate better overall thermal comfort levels and enhanced cost-effectiveness when using the SFLC redesign.

Item Type: Article
Item ID: 15592
Keywords: Modeling and simulation, HVAC system, IDA-ICC program, system identification, state space model, fuzzy logic, SFLC
Department(s): Engineering and Applied Science, Faculty of
Date: 9 June 2019
Date Type: Publication
Geographic Location: Newfoundland and Labrador
Digital Object Identifier (DOI):
Related URLs:

Actions (login required)

View Item View Item


Downloads per month over the past year

View more statistics