Model set identification for H∞ robust control of Hydraulic Flight Motion Simulator
A model set identification approach is presented for H infin robust control design of Hydraulic Flight Motion Simulator servo system, which suffers from various uncertainties, such as parameter uncertainty, high frequency unmodelled dynamic uncertainty, and so on. The identification approach consist...
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creator | Ben-Yong Wang Yan-Liang Dong Ke-Ding Zhao |
description | A model set identification approach is presented for H infin robust control design of Hydraulic Flight Motion Simulator servo system, which suffers from various uncertainties, such as parameter uncertainty, high frequency unmodelled dynamic uncertainty, and so on. The identification approach consists of two steps. To be exact, the first step is nominal model parameter identification, and then model uncertainty estimation. The nominal model parameter identification is based on the grey-box method. The model uncertainty estimation is implemented with model error modeling. Both nominal model and uncertainty bound are indispensable to H infin robust control design. Compared to the usual modeling method with math derivation and simulation, the proposed identification approach provides more accurate nominal model and uncertainty bound, and is more suitable for H infin robust control design of Hydraulic Flight Motion Simulator servo system. The identification procedure is illustrated with the Hydraulic Flight Motion Simulator inner gimbal servo system. |
doi_str_mv | 10.1109/ICMLC.2009.5212206 |
format | Conference Proceeding |
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The identification approach consists of two steps. To be exact, the first step is nominal model parameter identification, and then model uncertainty estimation. The nominal model parameter identification is based on the grey-box method. The model uncertainty estimation is implemented with model error modeling. Both nominal model and uncertainty bound are indispensable to H infin robust control design. Compared to the usual modeling method with math derivation and simulation, the proposed identification approach provides more accurate nominal model and uncertainty bound, and is more suitable for H infin robust control design of Hydraulic Flight Motion Simulator servo system. 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The identification approach consists of two steps. To be exact, the first step is nominal model parameter identification, and then model uncertainty estimation. The nominal model parameter identification is based on the grey-box method. The model uncertainty estimation is implemented with model error modeling. Both nominal model and uncertainty bound are indispensable to H infin robust control design. Compared to the usual modeling method with math derivation and simulation, the proposed identification approach provides more accurate nominal model and uncertainty bound, and is more suitable for H infin robust control design of Hydraulic Flight Motion Simulator servo system. The identification procedure is illustrated with the Hydraulic Flight Motion Simulator inner gimbal servo system.</description><subject>Aerospace simulation</subject><subject>Control system synthesis</subject><subject>Cybernetics</subject><subject>Grey-box method</subject><subject>Hydraulic Flight Motion Simulator</subject><subject>Machine learning</subject><subject>Model error modeling</subject><subject>Model set identification</subject><subject>Model uncertainty</subject><subject>Nominal model</subject><subject>Parameter estimation</subject><subject>Robust control</subject><subject>Sampling methods</subject><subject>Servomechanisms</subject><subject>Uncertainty</subject><subject>Valves</subject><issn>2160-133X</issn><isbn>1424437024</isbn><isbn>9781424437023</isbn><isbn>9781424437030</isbn><isbn>1424437032</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNp9j0FOwzAURD-CSrSQC8DmX6DB_naSeh1RBYmsaCV2lUkcMHJjZDuL3oBTcDhOQoXKltmMRk9vMQA3nOWcM3X3ULePdU6MqbwgTsTKM8hUteKSpBQVE-wcFn-D5AXMiZdsyYV4nsHi6K0U56qgS8hifGfHyIKqUsxh2_reOIwmoe3NmOxgO52sH3HwAZvvzy8M_mWKCTs_puAd-gGbQx_05GyHa2df3xK2_ld5svvJ6eTDNcwG7aLJTn0Ft-v7Td0srTFm9xHsXofD7nRF_E9_AE_2SFQ</recordid><startdate>200907</startdate><enddate>200907</enddate><creator>Ben-Yong Wang</creator><creator>Yan-Liang Dong</creator><creator>Ke-Ding Zhao</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200907</creationdate><title>Model set identification for H∞ robust control of Hydraulic Flight Motion Simulator</title><author>Ben-Yong Wang ; Yan-Liang Dong ; Ke-Ding Zhao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_52122063</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Aerospace simulation</topic><topic>Control system synthesis</topic><topic>Cybernetics</topic><topic>Grey-box method</topic><topic>Hydraulic Flight Motion Simulator</topic><topic>Machine learning</topic><topic>Model error modeling</topic><topic>Model set identification</topic><topic>Model uncertainty</topic><topic>Nominal model</topic><topic>Parameter estimation</topic><topic>Robust control</topic><topic>Sampling methods</topic><topic>Servomechanisms</topic><topic>Uncertainty</topic><topic>Valves</topic><toplevel>online_resources</toplevel><creatorcontrib>Ben-Yong Wang</creatorcontrib><creatorcontrib>Yan-Liang Dong</creatorcontrib><creatorcontrib>Ke-Ding Zhao</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ben-Yong Wang</au><au>Yan-Liang Dong</au><au>Ke-Ding Zhao</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Model set identification for H∞ robust control of Hydraulic Flight Motion Simulator</atitle><btitle>2009 International Conference on Machine Learning and Cybernetics</btitle><stitle>ICMLC</stitle><date>2009-07</date><risdate>2009</risdate><volume>4</volume><spage>2118</spage><epage>2122</epage><pages>2118-2122</pages><issn>2160-133X</issn><isbn>1424437024</isbn><isbn>9781424437023</isbn><eisbn>9781424437030</eisbn><eisbn>1424437032</eisbn><abstract>A model set identification approach is presented for H infin robust control design of Hydraulic Flight Motion Simulator servo system, which suffers from various uncertainties, such as parameter uncertainty, high frequency unmodelled dynamic uncertainty, and so on. The identification approach consists of two steps. To be exact, the first step is nominal model parameter identification, and then model uncertainty estimation. The nominal model parameter identification is based on the grey-box method. The model uncertainty estimation is implemented with model error modeling. Both nominal model and uncertainty bound are indispensable to H infin robust control design. Compared to the usual modeling method with math derivation and simulation, the proposed identification approach provides more accurate nominal model and uncertainty bound, and is more suitable for H infin robust control design of Hydraulic Flight Motion Simulator servo system. The identification procedure is illustrated with the Hydraulic Flight Motion Simulator inner gimbal servo system.</abstract><pub>IEEE</pub><doi>10.1109/ICMLC.2009.5212206</doi></addata></record> |
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ispartof | 2009 International Conference on Machine Learning and Cybernetics, 2009, Vol.4, p.2118-2122 |
issn | 2160-133X |
language | eng |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Aerospace simulation Control system synthesis Cybernetics Grey-box method Hydraulic Flight Motion Simulator Machine learning Model error modeling Model set identification Model uncertainty Nominal model Parameter estimation Robust control Sampling methods Servomechanisms Uncertainty Valves |
title | Model set identification for H∞ robust control of Hydraulic Flight Motion Simulator |
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