Adaptive fuzzy multivariable controller design based on genetic algorithm for an air handling unit
Muhammad Waqas Khan,
Mohammad Ahmad Choudhry,
Muhammad Zeeshan and
Ahsan Ali
Energy, 2015, vol. 81, issue C, 477-488
Abstract:
In HVAC (Heating, Ventilation and Air Conditioning systems, effective thermal management is required because energy and operation costs of buildings are directly influenced by how well an air-conditioning system performs. HVAC systems are typically nonlinear time varying with disturbances, where conventional PID controllers may trade-off between stability and rise time. To overcome this limitation, a Genetic Algorithm based AFLC (Adaptive Fuzzy Logic Controller design has been proposed for the multivariable control of temperature and humidity of a typical AHU (air handling unit by manipulating valve positions to adjust the water and steam flow rates. Modulating equal percentage Globe valves for chilled water and steam have been modeled according to exact flow rates of water and steam. A novel method for the adaptation of FLC (Fuzzy Logic Controller by modifying FRM (Fuzzy Rule Matrix based on GA (genetic algorithm) has been proposed. This requires re-designing the complete FLC in MATLAB/Simulink whose procedure has also been proposed. The proposed adaptive controller outperforms the existing fuzzy controller in terms of steady state error, rise time and settling time.
Keywords: HVAC; Air handling unit; Genetic algorithm; Fuzzy logic controller (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544214014352
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:81:y:2015:i:c:p:477-488
DOI: 10.1016/j.energy.2014.12.061
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().