基于细菌觅食优化算法的PID转矩电机系统性能分析

R. Precup, Andrei-Leonard Borza, M. Radac, E. Petriu
{"title":"基于细菌觅食优化算法的PID转矩电机系统性能分析","authors":"R. Precup, Andrei-Leonard Borza, M. Radac, E. Petriu","doi":"10.1109/CIVEMSA.2014.6841453","DOIUrl":null,"url":null,"abstract":"This paper deals with the optimal tuning of proportional-integral-derivative (PID) controllers for a pancake direct current (DC) torque motor system that belongs to a Diesel engine exhaust gas recirculation valve in automotive applications. The Bacterial Foraging Optimization (BFO) algorithms solve an optimization problem which targets the minimization of an objective function expressed as the weighted sum of overshoot plus the integral of squared control error, and the parameters of the PID controllers are the variables of the objective function. Our BFO algorithms are characterized by the validation of the position of bacteria only if the PID control system response is in a valid range. A digitally simulated case study which deals with the shaft angle control of a DC torque motor system is considered. The impact of four parameters of one BFO algorithm on the objective function values is discussed.","PeriodicalId":228132,"journal":{"name":"2014 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Performance analysis of torque motor systems with PID controllers tuned by Bacterial Foraging Optimization algorithms\",\"authors\":\"R. Precup, Andrei-Leonard Borza, M. Radac, E. Petriu\",\"doi\":\"10.1109/CIVEMSA.2014.6841453\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with the optimal tuning of proportional-integral-derivative (PID) controllers for a pancake direct current (DC) torque motor system that belongs to a Diesel engine exhaust gas recirculation valve in automotive applications. The Bacterial Foraging Optimization (BFO) algorithms solve an optimization problem which targets the minimization of an objective function expressed as the weighted sum of overshoot plus the integral of squared control error, and the parameters of the PID controllers are the variables of the objective function. Our BFO algorithms are characterized by the validation of the position of bacteria only if the PID control system response is in a valid range. A digitally simulated case study which deals with the shaft angle control of a DC torque motor system is considered. The impact of four parameters of one BFO algorithm on the objective function values is discussed.\",\"PeriodicalId\":228132,\"journal\":{\"name\":\"2014 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIVEMSA.2014.6841453\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIVEMSA.2014.6841453","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

本文研究了车用柴油机废气再循环阀的煎饼式直流转矩电机系统的比例-积分-导数(PID)控制器的最优整定问题。细菌觅食优化算法(Bacterial Foraging Optimization, BFO)解决的是一个以超调量加权和加控制误差平方积分为目标函数的最优化问题,PID控制器的参数为目标函数的变量。我们的BFO算法的特点是只有当PID控制系统响应在有效范围内时才能验证细菌的位置。对直流转矩电机系统的轴角控制进行了数值仿真研究。讨论了一种BFO算法的四个参数对目标函数值的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Performance analysis of torque motor systems with PID controllers tuned by Bacterial Foraging Optimization algorithms
This paper deals with the optimal tuning of proportional-integral-derivative (PID) controllers for a pancake direct current (DC) torque motor system that belongs to a Diesel engine exhaust gas recirculation valve in automotive applications. The Bacterial Foraging Optimization (BFO) algorithms solve an optimization problem which targets the minimization of an objective function expressed as the weighted sum of overshoot plus the integral of squared control error, and the parameters of the PID controllers are the variables of the objective function. Our BFO algorithms are characterized by the validation of the position of bacteria only if the PID control system response is in a valid range. A digitally simulated case study which deals with the shaft angle control of a DC torque motor system is considered. The impact of four parameters of one BFO algorithm on the objective function values is discussed.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Performance analysis of torque motor systems with PID controllers tuned by Bacterial Foraging Optimization algorithms Virtual calibration environment for a-priori estimation of measurement uncertainty ACO-based media content adaptation for e-learning environments Unsupervised machine learning via Hidden Markov Models for accurate clustering of plant stress levels based on imaged chlorophyll fluorescence profiles & their rate of change in time A security model for wireless sensor networks
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1