双转子气动系统数据驱动的无模型自适应控制

2014 IEEE 9th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2014-05-15 DOI:10.1109/SACI.2014.6840079

Raul-Cristian Roman, M. Radac, R. Precup

{"title":"双转子气动系统数据驱动的无模型自适应控制","authors":"Raul-Cristian Roman, M. Radac, R. Precup","doi":"10.1109/SACI.2014.6840079","DOIUrl":null,"url":null,"abstract":"This paper proposes data-driven Model-Free Adaptive Control (MFAC) algorithms for a Multi Input-Multi Output (MIMO) twin rotor aerodynamic systems. The azimuth and pitch position control are carried out using a MIMO control system structure with two control loops, one for each axis of motion. A set of experimental results on laboratory equipment is given to show the ability of the MFAC algorithms to control the mechanical ensemble even without decoupling and in spite of disturbances.","PeriodicalId":163447,"journal":{"name":"2014 IEEE 9th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Data-driven Model-Free Adaptive Control of twin rotor aerodynamic systems\",\"authors\":\"Raul-Cristian Roman, M. Radac, R. Precup\",\"doi\":\"10.1109/SACI.2014.6840079\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes data-driven Model-Free Adaptive Control (MFAC) algorithms for a Multi Input-Multi Output (MIMO) twin rotor aerodynamic systems. The azimuth and pitch position control are carried out using a MIMO control system structure with two control loops, one for each axis of motion. A set of experimental results on laboratory equipment is given to show the ability of the MFAC algorithms to control the mechanical ensemble even without decoupling and in spite of disturbances.\",\"PeriodicalId\":163447,\"journal\":{\"name\":\"2014 IEEE 9th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"volume\":\"92 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 9th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SACI.2014.6840079\",\"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 9th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SACI.2014.6840079","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 8

摘要

针对多输入-多输出(MIMO)双转子气动系统，提出了数据驱动的无模型自适应控制算法。方位角和俯仰位置控制采用MIMO控制系统结构进行，该控制系统具有两个控制回路，每个控制回路对应一个运动轴。在实验室设备上的一组实验结果表明，MFAC算法能够在不解耦和不受干扰的情况下控制机械集成。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Data-driven Model-Free Adaptive Control of twin rotor aerodynamic systems

This paper proposes data-driven Model-Free Adaptive Control (MFAC) algorithms for a Multi Input-Multi Output (MIMO) twin rotor aerodynamic systems. The azimuth and pitch position control are carried out using a MIMO control system structure with two control loops, one for each axis of motion. A set of experimental results on laboratory equipment is given to show the ability of the MFAC algorithms to control the mechanical ensemble even without decoupling and in spite of disturbances.

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

2014 IEEE 9th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)

自引率

0.00%

发文量