多电飞机发电机系统的混合调制模型预测控制

S. Yeoh, Tao Yang, L. Tarisciotti, S. Bozhko, P. Zanchetta
{"title":"多电飞机发电机系统的混合调制模型预测控制","authors":"S. Yeoh, Tao Yang, L. Tarisciotti, S. Bozhko, P. Zanchetta","doi":"10.1109/ESARS.2015.7101477","DOIUrl":null,"url":null,"abstract":"The More Electric Aircraft (MEA) has been identified to be a major trend for future aircrafts. One of the key improvements introduced in MEA is its electrical power generation system. The generator system studied in this paper comprises of a permanent magnet machine and an active front-end rectifier. Rather than just using PI controllers to control the generation system, Model Predictive Control (MPC) is considered due to its ability to achieve fast dynamic performance and multivariable control. A variant of MPC called Modulated Model Predictive Control (MPC with intrinsic modulator) was recently introduced that showed significantly better performance than the standard MPC method. This paper presents a control scheme that utilizes Modulated Model Predictive Control for the current inner loop and PI controllers for the outer loop. The proposed control is compared with a full cascaded PI control scheme. Simulation tests are carried out to compare the two control methods and the results are presented and analysed.","PeriodicalId":287492,"journal":{"name":"2015 International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles (ESARS)","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Hybrid modulated model predictive control for the more electric aircraft generator system\",\"authors\":\"S. Yeoh, Tao Yang, L. Tarisciotti, S. Bozhko, P. Zanchetta\",\"doi\":\"10.1109/ESARS.2015.7101477\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The More Electric Aircraft (MEA) has been identified to be a major trend for future aircrafts. One of the key improvements introduced in MEA is its electrical power generation system. The generator system studied in this paper comprises of a permanent magnet machine and an active front-end rectifier. Rather than just using PI controllers to control the generation system, Model Predictive Control (MPC) is considered due to its ability to achieve fast dynamic performance and multivariable control. A variant of MPC called Modulated Model Predictive Control (MPC with intrinsic modulator) was recently introduced that showed significantly better performance than the standard MPC method. This paper presents a control scheme that utilizes Modulated Model Predictive Control for the current inner loop and PI controllers for the outer loop. The proposed control is compared with a full cascaded PI control scheme. Simulation tests are carried out to compare the two control methods and the results are presented and analysed.\",\"PeriodicalId\":287492,\"journal\":{\"name\":\"2015 International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles (ESARS)\",\"volume\":\"2013 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles (ESARS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ESARS.2015.7101477\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles (ESARS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ESARS.2015.7101477","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

电动飞机(MEA)已被确定为未来飞机的主要趋势。在MEA中引入的关键改进之一是其发电系统。本文所研究的发电机系统由一个永磁电机和一个有源前端整流器组成。模型预测控制(MPC),而不是仅仅使用PI控制器来控制发电系统,因为它能够实现快速动态性能和多变量控制。MPC的一种变体称为调制模型预测控制(MPC with intrinsic modulator),最近被引入,显示出比标准MPC方法更好的性能。本文提出了一种电流内环采用调制模型预测控制,外环采用PI控制器的控制方案。将所提出的控制与全级联PI控制方案进行了比较。通过仿真试验对两种控制方法进行了比较,并对结果进行了分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid modulated model predictive control for the more electric aircraft generator system
The More Electric Aircraft (MEA) has been identified to be a major trend for future aircrafts. One of the key improvements introduced in MEA is its electrical power generation system. The generator system studied in this paper comprises of a permanent magnet machine and an active front-end rectifier. Rather than just using PI controllers to control the generation system, Model Predictive Control (MPC) is considered due to its ability to achieve fast dynamic performance and multivariable control. A variant of MPC called Modulated Model Predictive Control (MPC with intrinsic modulator) was recently introduced that showed significantly better performance than the standard MPC method. This paper presents a control scheme that utilizes Modulated Model Predictive Control for the current inner loop and PI controllers for the outer loop. The proposed control is compared with a full cascaded PI control scheme. Simulation tests are carried out to compare the two control methods and the results are presented and analysed.
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
×
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:481959085
Book学术官方微信