Parameter identification for sensorless vector-controlled induction motor system using image processor
This paper presents a mechanical sensorless vector-controlled system with parameter identification by the aid of image processor. Based on the flux observer and the model reference adaptive system method, this system includes rotor speed estimation and stator resistance identification using flux err...
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creator | Tsuji, M. Chen, S. Motoo, T. Kawabe, Y. Hamasaki, S. |
description | This paper presents a mechanical sensorless vector-controlled system with parameter identification by the aid of image processor. Based on the flux observer and the model reference adaptive system method, this system includes rotor speed estimation and stator resistance identification using flux errors. Since the mathematical model of this system is constructed in a synchronously rotating reference frame, a linear model is easily derived for analyzing the system stability, including motor operating state and parameter variations. Because identifying rotor resistance is difficult simultaneously while estimating rotor speed, we use a low-accuracy image processor to measure the mechanical axis position for calculating the rotor speed at a steady-state operation. The rotor resistance is identified by the error between the estimated speed using the estimated flux and the calculated speed using the image processor. Finally, the validity of this proposed system has been proven through experimentation |
doi_str_mv | 10.1109/ICEMS.2005.202877 |
format | Conference Proceeding |
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Based on the flux observer and the model reference adaptive system method, this system includes rotor speed estimation and stator resistance identification using flux errors. Since the mathematical model of this system is constructed in a synchronously rotating reference frame, a linear model is easily derived for analyzing the system stability, including motor operating state and parameter variations. Because identifying rotor resistance is difficult simultaneously while estimating rotor speed, we use a low-accuracy image processor to measure the mechanical axis position for calculating the rotor speed at a steady-state operation. The rotor resistance is identified by the error between the estimated speed using the estimated flux and the calculated speed using the image processor. Finally, the validity of this proposed system has been proven through experimentation</description><identifier>ISBN: 7506274078</identifier><identifier>ISBN: 9787506274074</identifier><identifier>DOI: 10.1109/ICEMS.2005.202877</identifier><language>eng</language><publisher>IEEE</publisher><subject>Adaptive systems ; Electrical resistance measurement ; Induction motors ; Mathematical model ; Mechanical variables measurement ; Observers ; Parameter estimation ; Rotors ; Stability analysis ; Stators</subject><ispartof>2005 International Conference on Electrical Machines and Systems, 2005, Vol.3, p.1828-1833 Vol. 3</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1575074$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2051,4035,4036,27904,54899</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1575074$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Tsuji, M.</creatorcontrib><creatorcontrib>Chen, S.</creatorcontrib><creatorcontrib>Motoo, T.</creatorcontrib><creatorcontrib>Kawabe, Y.</creatorcontrib><creatorcontrib>Hamasaki, S.</creatorcontrib><title>Parameter identification for sensorless vector-controlled induction motor system using image processor</title><title>2005 International Conference on Electrical Machines and Systems</title><addtitle>ICEMS</addtitle><description>This paper presents a mechanical sensorless vector-controlled system with parameter identification by the aid of image processor. Based on the flux observer and the model reference adaptive system method, this system includes rotor speed estimation and stator resistance identification using flux errors. Since the mathematical model of this system is constructed in a synchronously rotating reference frame, a linear model is easily derived for analyzing the system stability, including motor operating state and parameter variations. Because identifying rotor resistance is difficult simultaneously while estimating rotor speed, we use a low-accuracy image processor to measure the mechanical axis position for calculating the rotor speed at a steady-state operation. The rotor resistance is identified by the error between the estimated speed using the estimated flux and the calculated speed using the image processor. Finally, the validity of this proposed system has been proven through experimentation</description><subject>Adaptive systems</subject><subject>Electrical resistance measurement</subject><subject>Induction motors</subject><subject>Mathematical model</subject><subject>Mechanical variables measurement</subject><subject>Observers</subject><subject>Parameter estimation</subject><subject>Rotors</subject><subject>Stability analysis</subject><subject>Stators</subject><isbn>7506274078</isbn><isbn>9787506274074</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2005</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotkN1KAzEQhQMiqLUPIN7kBbZONptN9lKWqoWKgnpdssmkRHY3JUmFvr3x51zMuflmmHMIuWGwYgy6u02_fn5b1QCijFpJeUaupIC2lg1IdUGWKX1CEe8aLrpL4l511BNmjNRbnLN33ujsw0xdiDThnEIcMSX6hSaHWJkw5xjGES31sz2aX3QK-Qc-pYwTPSY_76mf9B7pIQZTlkO8JudOjwmX_74gHw_r9_6p2r48bvr7beWZFLlyvLFSaSXrweBgrHXKsEEPplNtiQOm5QxEw0GpEkAyACucADdAgwPUHV-Q27-7HhF3h1jeiKcdE6UC2fBvGCdXcA</recordid><startdate>2005</startdate><enddate>2005</enddate><creator>Tsuji, M.</creator><creator>Chen, S.</creator><creator>Motoo, T.</creator><creator>Kawabe, Y.</creator><creator>Hamasaki, S.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2005</creationdate><title>Parameter identification for sensorless vector-controlled induction motor system using image processor</title><author>Tsuji, M. ; Chen, S. ; Motoo, T. ; Kawabe, Y. ; Hamasaki, S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-f34d78a872bcebcddf8c1babc9862020c63105430883947100d5f50fb04eb0293</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Adaptive systems</topic><topic>Electrical resistance measurement</topic><topic>Induction motors</topic><topic>Mathematical model</topic><topic>Mechanical variables measurement</topic><topic>Observers</topic><topic>Parameter estimation</topic><topic>Rotors</topic><topic>Stability analysis</topic><topic>Stators</topic><toplevel>online_resources</toplevel><creatorcontrib>Tsuji, M.</creatorcontrib><creatorcontrib>Chen, S.</creatorcontrib><creatorcontrib>Motoo, T.</creatorcontrib><creatorcontrib>Kawabe, Y.</creatorcontrib><creatorcontrib>Hamasaki, S.</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/IET Electronic Library</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>Tsuji, M.</au><au>Chen, S.</au><au>Motoo, T.</au><au>Kawabe, Y.</au><au>Hamasaki, S.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Parameter identification for sensorless vector-controlled induction motor system using image processor</atitle><btitle>2005 International Conference on Electrical Machines and Systems</btitle><stitle>ICEMS</stitle><date>2005</date><risdate>2005</risdate><volume>3</volume><spage>1828</spage><epage>1833 Vol. 3</epage><pages>1828-1833 Vol. 3</pages><isbn>7506274078</isbn><isbn>9787506274074</isbn><abstract>This paper presents a mechanical sensorless vector-controlled system with parameter identification by the aid of image processor. Based on the flux observer and the model reference adaptive system method, this system includes rotor speed estimation and stator resistance identification using flux errors. Since the mathematical model of this system is constructed in a synchronously rotating reference frame, a linear model is easily derived for analyzing the system stability, including motor operating state and parameter variations. Because identifying rotor resistance is difficult simultaneously while estimating rotor speed, we use a low-accuracy image processor to measure the mechanical axis position for calculating the rotor speed at a steady-state operation. The rotor resistance is identified by the error between the estimated speed using the estimated flux and the calculated speed using the image processor. Finally, the validity of this proposed system has been proven through experimentation</abstract><pub>IEEE</pub><doi>10.1109/ICEMS.2005.202877</doi></addata></record> |
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subjects | Adaptive systems Electrical resistance measurement Induction motors Mathematical model Mechanical variables measurement Observers Parameter estimation Rotors Stability analysis Stators |
title | Parameter identification for sensorless vector-controlled induction motor system using image processor |
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