Fuzzy pid control for indoor CO2 concentration

In this research work, a fuzzy PID controller is proposed to realize C02-based DCV, rather than traditional PID controller frequently applied in building controls. On the basis of DCV, the fresh air flow rate is calculated through the C02 mass balance equation to meet the indoor C02 concentration re...

Full description

Saved in:
Bibliographic Details
Main Author: Sun, Xuan
Other Authors: Cai Wenjian
Format: Theses and Dissertations
Language:English
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/10356/66288
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-66288
record_format dspace
spelling sg-ntu-dr.10356-662882023-07-04T15:41:26Z Fuzzy pid control for indoor CO2 concentration Sun, Xuan Cai Wenjian School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering In this research work, a fuzzy PID controller is proposed to realize C02-based DCV, rather than traditional PID controller frequently applied in building controls. On the basis of DCV, the fresh air flow rate is calculated through the C02 mass balance equation to meet the indoor C02 concentration requirements. Fuzzy PID strategy initially uses classic PID control with three parameters tuned by experience. During the process of system operating, those parameters are tuned by three fuzzy modules according to the practical environment around. To get specific results, simulation models of PID, pure fuzzy and fuzzy PID controller are built in Simulink. The response graphics show that fuzzy PID has faster response speed than PID and much smaller steady-state error than pure fuzzy. Besides, it achieves best energy savings performance among them. Therefore, fuzzy PID controller can achieve acceptable C02 level with minimum energy consumption. In addition, this thesis also introduces using single chip to achieve the controlling procedures of AHU start and stop. Master of Science (Computer Control and Automation) 2016-03-23T04:20:20Z 2016-03-23T04:20:20Z 2016 Thesis http://hdl.handle.net/10356/66288 en 71 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Sun, Xuan
Fuzzy pid control for indoor CO2 concentration
description In this research work, a fuzzy PID controller is proposed to realize C02-based DCV, rather than traditional PID controller frequently applied in building controls. On the basis of DCV, the fresh air flow rate is calculated through the C02 mass balance equation to meet the indoor C02 concentration requirements. Fuzzy PID strategy initially uses classic PID control with three parameters tuned by experience. During the process of system operating, those parameters are tuned by three fuzzy modules according to the practical environment around. To get specific results, simulation models of PID, pure fuzzy and fuzzy PID controller are built in Simulink. The response graphics show that fuzzy PID has faster response speed than PID and much smaller steady-state error than pure fuzzy. Besides, it achieves best energy savings performance among them. Therefore, fuzzy PID controller can achieve acceptable C02 level with minimum energy consumption. In addition, this thesis also introduces using single chip to achieve the controlling procedures of AHU start and stop.
author2 Cai Wenjian
author_facet Cai Wenjian
Sun, Xuan
format Theses and Dissertations
author Sun, Xuan
author_sort Sun, Xuan
title Fuzzy pid control for indoor CO2 concentration
title_short Fuzzy pid control for indoor CO2 concentration
title_full Fuzzy pid control for indoor CO2 concentration
title_fullStr Fuzzy pid control for indoor CO2 concentration
title_full_unstemmed Fuzzy pid control for indoor CO2 concentration
title_sort fuzzy pid control for indoor co2 concentration
publishDate 2016
url http://hdl.handle.net/10356/66288
_version_ 1772828185966149632