Genetic algorithm optimization of I/O scales for FLIC in servomotor control
Direct Current (DC) servomotors are widely used in robot manipulator applications. Servomotors use feedback controller to control either the speed or the position or both. This paper discusses the modeling and simulation of DC servomotor control built using MATLAB/Simulink, and the analysis of contr...
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my.utp.eprints.3132017-01-19T08:25:59Z Genetic algorithm optimization of I/O scales for FLIC in servomotor control Wahyunggoro , O. Saad ., Nordin TK Electrical engineering. Electronics Nuclear engineering Direct Current (DC) servomotors are widely used in robot manipulator applications. Servomotors use feedback controller to control either the speed or the position or both. This paper discusses the modeling and simulation of DC servomotor control built using MATLAB/Simulink, and the analysis of controller performance, namely a Fuzzy Logic parallel I Controller (FLIC) in which the I/O scale factors of Fuzzy Logic Controller (FLC) and integrator constant are optimized using Genetic Algorithm (GA). The singleton fuzzification is used as a fuzzifier: seven membership functions for both input and output of fuzzy logic controller. The center average is used as a defuzzifier. The 32-bit-50-population is used in GA. Two control modes are applied in cascade to the plant: speed control in the position control loop. Simulation results show that FLIC with GA-optimized is the best performance compared to FLIC without GA and conventionalFLC for the speed and position control of DC servomotor. © 2009 IEEE. 2009 Conference or Workshop Item NonPeerReviewed application/pdf http://eprints.utp.edu.my/313/1/paper.pdf http://www.scopus.com/inward/record.url?eid=2-s2.0-70449120934&partnerID=40&md5=8cbe9390185d05754c336d3bb93b346e Wahyunggoro , O. and Saad ., Nordin (2009) Genetic algorithm optimization of I/O scales for FLIC in servomotor control. In: 2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009, 25 July 2009 through 26 July 2009, Kuala Lumpur. http://eprints.utp.edu.my/313/ |
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TK Electrical engineering. Electronics Nuclear engineering Wahyunggoro , O. Saad ., Nordin Genetic algorithm optimization of I/O scales for FLIC in servomotor control |
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Direct Current (DC) servomotors are widely used in robot manipulator applications. Servomotors use feedback controller to control either the speed or the position or both. This paper discusses the modeling and simulation of DC servomotor control built using MATLAB/Simulink, and the analysis of controller performance, namely a Fuzzy Logic parallel I Controller (FLIC) in which the I/O scale factors of Fuzzy Logic Controller (FLC) and integrator constant are optimized using Genetic Algorithm (GA). The singleton fuzzification is used as a fuzzifier: seven membership functions for both input and output of fuzzy logic controller. The center average is used as a defuzzifier. The 32-bit-50-population is used in GA. Two control modes are applied in cascade to the plant: speed control in the position control loop. Simulation results show that FLIC with GA-optimized is the best performance compared to FLIC without GA and conventionalFLC for the speed and position control of DC servomotor. © 2009 IEEE.
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Conference or Workshop Item |
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Wahyunggoro , O. Saad ., Nordin |
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Wahyunggoro , O. Saad ., Nordin |
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Wahyunggoro , O. |
title |
Genetic algorithm optimization of I/O scales for FLIC in servomotor control
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title_short |
Genetic algorithm optimization of I/O scales for FLIC in servomotor control
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title_full |
Genetic algorithm optimization of I/O scales for FLIC in servomotor control
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title_fullStr |
Genetic algorithm optimization of I/O scales for FLIC in servomotor control
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title_full_unstemmed |
Genetic algorithm optimization of I/O scales for FLIC in servomotor control
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title_sort |
genetic algorithm optimization of i/o scales for flic in servomotor control |
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2009 |
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http://eprints.utp.edu.my/313/1/paper.pdf http://www.scopus.com/inward/record.url?eid=2-s2.0-70449120934&partnerID=40&md5=8cbe9390185d05754c336d3bb93b346e http://eprints.utp.edu.my/313/ |
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