Research on resonant power supply for plasma cleaning based on adaptive genetic optimization PID

Xue Jiaxiang, Wang Yitong, Ding Duhan, Zhou Gang
{"title":"Research on resonant power supply for plasma cleaning based on adaptive genetic optimization PID","authors":"Xue Jiaxiang, Wang Yitong, Ding Duhan, Zhou Gang","doi":"10.1109/IHMSC55436.2022.00015","DOIUrl":null,"url":null,"abstract":"In view of the large disturbance and non-linearity of the existing plasma discharge power supply system, an adaptive genetic optimization PID control algorithm is proposed to replace the original PID control algorithm. According to the three indexes of overshoot, regulation time and steady-state accuracy, the evaluation function is formulated. Considering the convergence performance and operation speed of the system, the dynamic crossover and mutation probabilities are formulated. Finally, the simulation program is built and the step response curves of the closed-loop transfer function before and after optimization are compared. The results show that the overshoot of the system decreases from 7.14% to 1.55%, and the regulation time decreases from 337.7μs to 5.17μs.","PeriodicalId":447862,"journal":{"name":"2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)","volume":"56 7","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IHMSC55436.2022.00015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

In view of the large disturbance and non-linearity of the existing plasma discharge power supply system, an adaptive genetic optimization PID control algorithm is proposed to replace the original PID control algorithm. According to the three indexes of overshoot, regulation time and steady-state accuracy, the evaluation function is formulated. Considering the convergence performance and operation speed of the system, the dynamic crossover and mutation probabilities are formulated. Finally, the simulation program is built and the step response curves of the closed-loop transfer function before and after optimization are compared. The results show that the overshoot of the system decreases from 7.14% to 1.55%, and the regulation time decreases from 337.7μs to 5.17μs.
基于自适应遗传优化PID的等离子清洗谐振电源研究
针对现有等离子体放电供电系统扰动大、非线性大的特点,提出了一种自适应遗传优化PID控制算法来取代原有的PID控制算法。根据超调量、调节时间和稳态精度三个指标,建立了评价函数。考虑到系统的收敛性能和运行速度,给出了系统的动态交叉和突变概率。最后,建立仿真程序,比较优化前后闭环传递函数的阶跃响应曲线。结果表明,系统超调量由7.14%降至1.55%,调节时间由337.7μs降至5.17μs。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信