Application Research of Fuzzy PID Control Optimized by Genetic Algorithm in Medium and Low Speed Maglev Train Charger

China’s railways are developing rapidly, and the charger of the auxiliary power supply system is an indispensable part of the maglev train. The existing maglev train charger usually uses the traditional PID controller to control the output of the charger which has a simple structure. To m...

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Autores principales:	Li Zhang, Liwei Zhang, Jiawei Yang, Ming Gao, Yinghua Li
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Maglev train charger fuzzy PID genetic algorithm Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/0cd33d7ff28941a8967546e030a3d21f
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spelling	oai:doaj.org-article:0cd33d7ff28941a8967546e030a3d21f2021-11-20T00:00:53ZApplication Research of Fuzzy PID Control Optimized by Genetic Algorithm in Medium and Low Speed Maglev Train Charger2169-353610.1109/ACCESS.2021.3123727https://doaj.org/article/0cd33d7ff28941a8967546e030a3d21f2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9591592/https://doaj.org/toc/2169-3536China’s railways are developing rapidly, and the charger of the auxiliary power supply system is an indispensable part of the maglev train. The existing maglev train charger usually uses the traditional PID controller to control the output of the charger which has a simple structure. To meet the requirements of the maglev train charger output performance which is getting higher and higher, it is necessary to optimize the control strategies which can achieve adaptive control of the system. In this paper, taking Qingyuan maglev train as the research object, the control principle of the charger of the maglev train is studied, and the simulation model of the charger of Qingyuan speed maglev train is built in MATLAB/Simulink. After verifying its feasibility, the paper proposes fuzzy PID control to improve the charger control method, and uses genetic algorithm to optimize fuzzy control membership function and fuzzy rules. Finally, the paper builds a fuzzy PID controller simulation model, compares the output performance of the charger under different control methods, and verifies the superiority of the new control method.Li ZhangLiwei ZhangJiawei YangMing GaoYinghua LiIEEEarticleMaglev trainchargerfuzzy PIDgenetic algorithmElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 152131-152139 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Maglev train charger fuzzy PID genetic algorithm Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Maglev train charger fuzzy PID genetic algorithm Electrical engineering. Electronics. Nuclear engineering TK1-9971 Li Zhang Liwei Zhang Jiawei Yang Ming Gao Yinghua Li Application Research of Fuzzy PID Control Optimized by Genetic Algorithm in Medium and Low Speed Maglev Train Charger
description	China’s railways are developing rapidly, and the charger of the auxiliary power supply system is an indispensable part of the maglev train. The existing maglev train charger usually uses the traditional PID controller to control the output of the charger which has a simple structure. To meet the requirements of the maglev train charger output performance which is getting higher and higher, it is necessary to optimize the control strategies which can achieve adaptive control of the system. In this paper, taking Qingyuan maglev train as the research object, the control principle of the charger of the maglev train is studied, and the simulation model of the charger of Qingyuan speed maglev train is built in MATLAB/Simulink. After verifying its feasibility, the paper proposes fuzzy PID control to improve the charger control method, and uses genetic algorithm to optimize fuzzy control membership function and fuzzy rules. Finally, the paper builds a fuzzy PID controller simulation model, compares the output performance of the charger under different control methods, and verifies the superiority of the new control method.
format	article
author	Li Zhang Liwei Zhang Jiawei Yang Ming Gao Yinghua Li
author_facet	Li Zhang Liwei Zhang Jiawei Yang Ming Gao Yinghua Li
author_sort	Li Zhang
title	Application Research of Fuzzy PID Control Optimized by Genetic Algorithm in Medium and Low Speed Maglev Train Charger
title_short	Application Research of Fuzzy PID Control Optimized by Genetic Algorithm in Medium and Low Speed Maglev Train Charger
title_full	Application Research of Fuzzy PID Control Optimized by Genetic Algorithm in Medium and Low Speed Maglev Train Charger
title_fullStr	Application Research of Fuzzy PID Control Optimized by Genetic Algorithm in Medium and Low Speed Maglev Train Charger
title_full_unstemmed	Application Research of Fuzzy PID Control Optimized by Genetic Algorithm in Medium and Low Speed Maglev Train Charger
title_sort	application research of fuzzy pid control optimized by genetic algorithm in medium and low speed maglev train charger
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/0cd33d7ff28941a8967546e030a3d21f
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_version_	1718419818431905792

Application Research of Fuzzy PID Control Optimized by Genetic Algorithm in Medium and Low Speed Maglev Train Charger

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