LAPSE:2020.0142
Published Article
LAPSE:2020.0142
Improved Genetic Algorithm Tuning Controller Design for Autonomous Hovercraft
February 3, 2020
By mimicking the biological evolution process, genetic algorithm (GA) methodology has the advantages of creating and updating new elite parameters for optimization processes, especially in controller design technique. In this paper, a GA improvement that can speed up convergence and save operation time by neglecting chromosome decoding step is proposed to find the optimized fuzzy-proportional-integral-derivative (fuzzy-PID) control parameters. Due to minimizing tracking error of the controller design criterion, the fitness function integral of square error (ISE) was employed to utilize the advantages of the modified GA. The proposed method was then applied to a novel autonomous hovercraft motion model to display the superiority to the standard GA.
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Keywords
autonomous hovercraft, fuzzy-PID control, ISE criterion, modified GA
Subject
Suggested Citation
Tran HK, Son HH, Duc PV, Trang TT, Nguyen HN. Improved Genetic Algorithm Tuning Controller Design for Autonomous Hovercraft. (2020). LAPSE:2020.0142
Author Affiliations
Tran HK: Industry 4.0 Center, National Taiwan University of Science and Technology, Taipei 10607, Taiwan; Center for Cyber-Physical System Innovation, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
Son HH: Faculty of Mechanical, Electrical, Electronic and Automotive Engineering, Nguyen Tat Thanh University, Ho Chi Minh City 700000, Vietnam
Duc PV: Faculty of Automobile Technology, Van Lang University, Ho Chi Minh city 700000, Vietnam
Trang TT: Faculty of Engineering and Technology, Van Hien University, 665-667-669 Dien Bien Phu, Ho Chi Minh city 700000, Vietnam
Nguyen HN: Modeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical & Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam [ORCID]
Son HH: Faculty of Mechanical, Electrical, Electronic and Automotive Engineering, Nguyen Tat Thanh University, Ho Chi Minh City 700000, Vietnam
Duc PV: Faculty of Automobile Technology, Van Lang University, Ho Chi Minh city 700000, Vietnam
Trang TT: Faculty of Engineering and Technology, Van Hien University, 665-667-669 Dien Bien Phu, Ho Chi Minh city 700000, Vietnam
Nguyen HN: Modeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical & Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam [ORCID]
Journal Name
Processes
Volume
8
Issue
1
Article Number
E66
Year
2020
Publication Date
2020-01-03
Published Version
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr8010066, Publication Type: Journal Article
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Published Article
LAPSE:2020.0142
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External Link
doi:10.3390/pr8010066
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Version History
[v1] (Original Submission)
Feb 3, 2020
Verified by curator on
Feb 3, 2020
This Version Number
v1
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https://psecommunity.org/LAPSE:2020.0142
Original Submitter
Calvin Tsay
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