GA-based fuzzy controller design for tunnel ventilation systems

Baeksuk Chu; Dongnam Kim; Daehie Hong; Jooyoung Park; Jin Taek Chung; Tae Hyung Kim

GA-based fuzzy controller design for tunnel ventilation systems

Baeksuk Chu, Dongnam Kim, Daehie Hong, Jooyoung Park, Jin Taek Chung, Tae Hyung Kim

Research output: Contribution to conference › Paper › peer-review

Abstract

The main purpose of tunnel ventilation system is to maintain CO pollutant concentration and VI (visibility index) under an adequate level to provide drivers with comfortable and safe driving environment. Moreover, it is necessary to minimize power consumption used to operate ventilation system. To achieve these purposes, FLC (fuzzy logic controller) has been usually utilized because complex and nonlinear system like tunnel ventilation is difficult to control with conventional quantitative methods. Membership functions of FLC consist of inputs such as pollutant level inside tunnel, pollutant emission rates from vehicles, and outputs, the number of running jet-fans. The conventional fuzzy control methods have been designed just by relying on simple experiences and using trial and error method. In this paper, FLC is optimally redesigned using GA (genetic algorithm) which is a stochastic global search method. In the process of constructing objective function of GA, maintaining pollutant concentration level under allowable limit and decreasing energy consumption are included. Finally, the simulation results performed with real data collected from the target tunnel ventilation system are shown. It is confirmed that the GA-based FLC shows more efficient performance than the conventional FLC.

Original language	English
Publication status	Published - 2005
Event	22nd International Symposium on Automation and Robotics in Construction, ISARC 2005 - Ferrara, Italy Duration: 2005 Sept 11 → 2005 Sept 14

Other

Other	22nd International Symposium on Automation and Robotics in Construction, ISARC 2005
Country/Territory	Italy
City	Ferrara
Period	05/9/11 → 05/9/14

Bibliographical note

Funding Information:
This work was performed in part of 2003 industrial-educational cooperation project, ‘Underground, Fire, and Environment Research’ supported by Korea Institute of Construction and Transportation Technology Evaluation and Planning, and partially supported by the Brain Korea 21 Project in 2006.

Keywords

FLC (fuzzy logic controller)
Real-valued GA (genetic algorithm)
Tunnel ventilation control

ASJC Scopus subject areas

Artificial Intelligence
Human-Computer Interaction
Building and Construction

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

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title = "GA-based fuzzy controller design for tunnel ventilation systems",

abstract = "The main purpose of tunnel ventilation system is to maintain CO pollutant concentration and VI (visibility index) under an adequate level to provide drivers with comfortable and safe driving environment. Moreover, it is necessary to minimize power consumption used to operate ventilation system. To achieve these purposes, FLC (fuzzy logic controller) has been usually utilized because complex and nonlinear system like tunnel ventilation is difficult to control with conventional quantitative methods. Membership functions of FLC consist of inputs such as pollutant level inside tunnel, pollutant emission rates from vehicles, and outputs, the number of running jet-fans. The conventional fuzzy control methods have been designed just by relying on simple experiences and using trial and error method. In this paper, FLC is optimally redesigned using GA (genetic algorithm) which is a stochastic global search method. In the process of constructing objective function of GA, maintaining pollutant concentration level under allowable limit and decreasing energy consumption are included. Finally, the simulation results performed with real data collected from the target tunnel ventilation system are shown. It is confirmed that the GA-based FLC shows more efficient performance than the conventional FLC.",

keywords = "FLC (fuzzy logic controller), Real-valued GA (genetic algorithm), Tunnel ventilation control",

author = "Baeksuk Chu and Dongnam Kim and Daehie Hong and Jooyoung Park and Chung, {Jin Taek} and Kim, {Tae Hyung}",

note = "Funding Information: This work was performed in part of 2003 industrial-educational cooperation project, {\textquoteleft}Underground, Fire, and Environment Research{\textquoteright} supported by Korea Institute of Construction and Transportation Technology Evaluation and Planning, and partially supported by the Brain Korea 21 Project in 2006.; 22nd International Symposium on Automation and Robotics in Construction, ISARC 2005 ; Conference date: 11-09-2005 Through 14-09-2005",

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language = "English",

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TY - CONF

T1 - GA-based fuzzy controller design for tunnel ventilation systems

AU - Chu, Baeksuk

AU - Kim, Dongnam

AU - Hong, Daehie

AU - Park, Jooyoung

AU - Chung, Jin Taek

AU - Kim, Tae Hyung

N1 - Funding Information: This work was performed in part of 2003 industrial-educational cooperation project, ‘Underground, Fire, and Environment Research’ supported by Korea Institute of Construction and Transportation Technology Evaluation and Planning, and partially supported by the Brain Korea 21 Project in 2006.

PY - 2005

Y1 - 2005

N2 - The main purpose of tunnel ventilation system is to maintain CO pollutant concentration and VI (visibility index) under an adequate level to provide drivers with comfortable and safe driving environment. Moreover, it is necessary to minimize power consumption used to operate ventilation system. To achieve these purposes, FLC (fuzzy logic controller) has been usually utilized because complex and nonlinear system like tunnel ventilation is difficult to control with conventional quantitative methods. Membership functions of FLC consist of inputs such as pollutant level inside tunnel, pollutant emission rates from vehicles, and outputs, the number of running jet-fans. The conventional fuzzy control methods have been designed just by relying on simple experiences and using trial and error method. In this paper, FLC is optimally redesigned using GA (genetic algorithm) which is a stochastic global search method. In the process of constructing objective function of GA, maintaining pollutant concentration level under allowable limit and decreasing energy consumption are included. Finally, the simulation results performed with real data collected from the target tunnel ventilation system are shown. It is confirmed that the GA-based FLC shows more efficient performance than the conventional FLC.

AB - The main purpose of tunnel ventilation system is to maintain CO pollutant concentration and VI (visibility index) under an adequate level to provide drivers with comfortable and safe driving environment. Moreover, it is necessary to minimize power consumption used to operate ventilation system. To achieve these purposes, FLC (fuzzy logic controller) has been usually utilized because complex and nonlinear system like tunnel ventilation is difficult to control with conventional quantitative methods. Membership functions of FLC consist of inputs such as pollutant level inside tunnel, pollutant emission rates from vehicles, and outputs, the number of running jet-fans. The conventional fuzzy control methods have been designed just by relying on simple experiences and using trial and error method. In this paper, FLC is optimally redesigned using GA (genetic algorithm) which is a stochastic global search method. In the process of constructing objective function of GA, maintaining pollutant concentration level under allowable limit and decreasing energy consumption are included. Finally, the simulation results performed with real data collected from the target tunnel ventilation system are shown. It is confirmed that the GA-based FLC shows more efficient performance than the conventional FLC.

KW - FLC (fuzzy logic controller)

KW - Real-valued GA (genetic algorithm)

KW - Tunnel ventilation control

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M3 - Paper

AN - SCOPUS:84862570213

T2 - 22nd International Symposium on Automation and Robotics in Construction, ISARC 2005

Y2 - 11 September 2005 through 14 September 2005

ER -

GA-based fuzzy controller design for tunnel ventilation systems

Abstract

Other

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

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