Implementation of fuzzy logic control system on rotary car parking system prototype

Rotary car parking system (RCPS) is one of the effective parking models used in the metropolitan area because the mechanical parking system is designed vertically to conserve the land usage. This paper discussed the implementation of fuzzy logic with the Sugeno Inference Model on the RCPS miniature...

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Main Authors: Ismail, Nanang, Nursalim, Iim, Saputra, Hendri Maja, Gunawan, Teddy Surya
Format: Article
Language:English
English
Published: Institute of Advanced Engineering and Science 2018
Subjects:
Online Access:http://irep.iium.edu.my/66216/
http://irep.iium.edu.my/66216/
http://irep.iium.edu.my/66216/
http://irep.iium.edu.my/66216/1/66216_Implementation%20of%20Fuzzy%20Logic.pdf
http://irep.iium.edu.my/66216/2/66216_Implementation%20of%20Fuzzy%20Logic_SCOPUS.pdf
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spelling iium-662162018-09-12T02:49:01Z http://irep.iium.edu.my/66216/ Implementation of fuzzy logic control system on rotary car parking system prototype Ismail, Nanang Nursalim, Iim Saputra, Hendri Maja Gunawan, Teddy Surya TJ212 Control engineering Rotary car parking system (RCPS) is one of the effective parking models used in the metropolitan area because the mechanical parking system is designed vertically to conserve the land usage. This paper discussed the implementation of fuzzy logic with the Sugeno Inference Model on the RCPS miniature control system. The research started with kinematics analysis and a mathematical model was derived to determine the slot position and optimal power requirements for each condition. Furthermore, the Fuzzy Inference model used was the Sugeno Model, taking into account two variables: distance and angle. These two variables were selected because in the designed miniature RCPS there will be rotational changes of rotation and rotation in turn. Variable distance was divided into four clusters, such as Zero, Near, Medium and Far. While the angle variables were divided into four clusters as well, such as Zero, Small, Medium, and Big. The test results on a miniature RCPS consisting of six parking slots showed that fuzzy based control provided better results when compared to conventional systems. Step response on the control system without fuzzy control showed the rise time value of 0.58 seconds, peak time of 0.85 seconds, settling time of 0.89, percentage overshoot of 0.20%, and steady state error of 4.14%. While the fuzzy control system provided the rise time value of 0.54 seconds, settling time of 0.83 seconds, steady state error of 2.32%, with no overshoot. Institute of Advanced Engineering and Science 2018-11 Article PeerReviewed application/pdf en http://irep.iium.edu.my/66216/1/66216_Implementation%20of%20Fuzzy%20Logic.pdf application/pdf en http://irep.iium.edu.my/66216/2/66216_Implementation%20of%20Fuzzy%20Logic_SCOPUS.pdf Ismail, Nanang and Nursalim, Iim and Saputra, Hendri Maja and Gunawan, Teddy Surya (2018) Implementation of fuzzy logic control system on rotary car parking system prototype. Indonesian Journal of Electrical Engineering and Computer Science, 12 (2). pp. 706-715. ISSN 2502-4752 https://www.iaescore.com/journals/index.php/IJEECS/article/view/14541/9401 10.11591/ijeecs.v12.i2.pp706-715
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
English
topic TJ212 Control engineering
spellingShingle TJ212 Control engineering
Ismail, Nanang
Nursalim, Iim
Saputra, Hendri Maja
Gunawan, Teddy Surya
Implementation of fuzzy logic control system on rotary car parking system prototype
description Rotary car parking system (RCPS) is one of the effective parking models used in the metropolitan area because the mechanical parking system is designed vertically to conserve the land usage. This paper discussed the implementation of fuzzy logic with the Sugeno Inference Model on the RCPS miniature control system. The research started with kinematics analysis and a mathematical model was derived to determine the slot position and optimal power requirements for each condition. Furthermore, the Fuzzy Inference model used was the Sugeno Model, taking into account two variables: distance and angle. These two variables were selected because in the designed miniature RCPS there will be rotational changes of rotation and rotation in turn. Variable distance was divided into four clusters, such as Zero, Near, Medium and Far. While the angle variables were divided into four clusters as well, such as Zero, Small, Medium, and Big. The test results on a miniature RCPS consisting of six parking slots showed that fuzzy based control provided better results when compared to conventional systems. Step response on the control system without fuzzy control showed the rise time value of 0.58 seconds, peak time of 0.85 seconds, settling time of 0.89, percentage overshoot of 0.20%, and steady state error of 4.14%. While the fuzzy control system provided the rise time value of 0.54 seconds, settling time of 0.83 seconds, steady state error of 2.32%, with no overshoot.
format Article
author Ismail, Nanang
Nursalim, Iim
Saputra, Hendri Maja
Gunawan, Teddy Surya
author_facet Ismail, Nanang
Nursalim, Iim
Saputra, Hendri Maja
Gunawan, Teddy Surya
author_sort Ismail, Nanang
title Implementation of fuzzy logic control system on rotary car parking system prototype
title_short Implementation of fuzzy logic control system on rotary car parking system prototype
title_full Implementation of fuzzy logic control system on rotary car parking system prototype
title_fullStr Implementation of fuzzy logic control system on rotary car parking system prototype
title_full_unstemmed Implementation of fuzzy logic control system on rotary car parking system prototype
title_sort implementation of fuzzy logic control system on rotary car parking system prototype
publisher Institute of Advanced Engineering and Science
publishDate 2018
url http://irep.iium.edu.my/66216/
http://irep.iium.edu.my/66216/
http://irep.iium.edu.my/66216/
http://irep.iium.edu.my/66216/1/66216_Implementation%20of%20Fuzzy%20Logic.pdf
http://irep.iium.edu.my/66216/2/66216_Implementation%20of%20Fuzzy%20Logic_SCOPUS.pdf
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last_indexed 2023-09-18T21:33:58Z
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