A Novel Online Multivariate Identification for Autotuning Speed Control in PMSM Drives
A novel online algorithm to identify the moment of inertia, viscous friction coefficient, and load torque of PMSM (Permanent Magnet Synchronous Motor) drives and a distinctive autotuning speed control scheme are presented. The proposed identification algorithm does not require motors run in a partic...
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| Veröffentlicht in: | Mathematical problems in engineering 2016-01, Vol.2016 (2016), p.1-13 |
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| container_title | Mathematical problems in engineering |
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| creator | Liu, Yi Chen, Bing Ai, Wu Chen, Ke |
| description | A novel online algorithm to identify the moment of inertia, viscous friction coefficient, and load torque of PMSM (Permanent Magnet Synchronous Motor) drives and a distinctive autotuning speed control scheme are presented. The proposed identification algorithm does not require motors run in a particular trajectory and only needs a short identification time. A Luenberger speed observer is introduced to eliminate noises which are generated by the detection of position signal and to improve the accuracy of identified parameters. Parameters of the speed controller are optimized by analyzing the mathematical model of the system and the formula of the PI controller. Compared to a standard recursive least squares method (RLSM) and traditional PI algorithm, the effectiveness of the proposed identification algorithm and autotuning speed control scheme are validated through simulations and experiments. |
| doi_str_mv | 10.1155/2016/1780710 |
| format | Article |
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The proposed identification algorithm does not require motors run in a particular trajectory and only needs a short identification time. A Luenberger speed observer is introduced to eliminate noises which are generated by the detection of position signal and to improve the accuracy of identified parameters. Parameters of the speed controller are optimized by analyzing the mathematical model of the system and the formula of the PI controller. Compared to a standard recursive least squares method (RLSM) and traditional PI algorithm, the effectiveness of the proposed identification algorithm and autotuning speed control scheme are validated through simulations and experiments.</description><identifier>ISSN: 1024-123X</identifier><identifier>EISSN: 1563-5147</identifier><identifier>DOI: 10.1155/2016/1780710</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Algorithms ; Coefficient of friction ; Control algorithms ; Controllers ; Friction ; Identification ; Inertia ; Kalman filters ; Least squares method ; Load ; Mathematical models ; Moments of inertia ; Parameter identification ; Permanent magnets ; Speed control ; Synchronous motors ; Trajectory analysis ; Trajectory control ; Velocity</subject><ispartof>Mathematical problems in engineering, 2016-01, Vol.2016 (2016), p.1-13</ispartof><rights>Copyright © 2016 Ke Chen et al.</rights><rights>Copyright © 2016 Ke Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c317t-60048ec6679427353fb3ab970f8d374f0dddd91f8406b0e2690023c98fa216353</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><contributor>Peng, Haipeng</contributor><creatorcontrib>Liu, Yi</creatorcontrib><creatorcontrib>Chen, Bing</creatorcontrib><creatorcontrib>Ai, Wu</creatorcontrib><creatorcontrib>Chen, Ke</creatorcontrib><title>A Novel Online Multivariate Identification for Autotuning Speed Control in PMSM Drives</title><title>Mathematical problems in engineering</title><description>A novel online algorithm to identify the moment of inertia, viscous friction coefficient, and load torque of PMSM (Permanent Magnet Synchronous Motor) drives and a distinctive autotuning speed control scheme are presented. The proposed identification algorithm does not require motors run in a particular trajectory and only needs a short identification time. A Luenberger speed observer is introduced to eliminate noises which are generated by the detection of position signal and to improve the accuracy of identified parameters. Parameters of the speed controller are optimized by analyzing the mathematical model of the system and the formula of the PI controller. Compared to a standard recursive least squares method (RLSM) and traditional PI algorithm, the effectiveness of the proposed identification algorithm and autotuning speed control scheme are validated through simulations and experiments.</description><subject>Algorithms</subject><subject>Coefficient of friction</subject><subject>Control algorithms</subject><subject>Controllers</subject><subject>Friction</subject><subject>Identification</subject><subject>Inertia</subject><subject>Kalman filters</subject><subject>Least squares method</subject><subject>Load</subject><subject>Mathematical models</subject><subject>Moments of inertia</subject><subject>Parameter identification</subject><subject>Permanent magnets</subject><subject>Speed control</subject><subject>Synchronous motors</subject><subject>Trajectory analysis</subject><subject>Trajectory control</subject><subject>Velocity</subject><issn>1024-123X</issn><issn>1563-5147</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqF0M9LwzAUB_AgCs7pzbMEPGpdXtIm7XHMXwPnhKl4K1mbaEZNZppO_O_N6MCj7_Le4cN7jy9Cp0CuALJsRAnwEYicCCB7aAAZZ0kGqdiPM6FpApS9HaKjtl0RQiGDfIBex_jRbVSD57YxVuFZ1wSzkd7IoPC0VjYYbSoZjLNYO4_HXXChs8a-48VaqRpPnA3eNdhY_DRbzPC1NxvVHqMDLZtWnez6EL3c3jxP7pOH-d10Mn5IKgYiJJyQNFcV56JIqWAZ00sml4UgOq-ZSDWpYxWg85TwJVGUF_FxVhW5lhR49EN03u9de_fVqTaUK9d5G0-WIAQVOY1ZRHXZq8q7tvVKl2tvPqX_KYGU2-TKbXLlLrnIL3r-YWwtv81_-qzXKhql5Z-OJQrGfgEYaHWG</recordid><startdate>20160101</startdate><enddate>20160101</enddate><creator>Liu, Yi</creator><creator>Chen, Bing</creator><creator>Ai, Wu</creator><creator>Chen, Ke</creator><general>Hindawi Publishing Corporation</general><general>Hindawi Limited</general><scope>ADJCN</scope><scope>AHFXO</scope><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>CWDGH</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>KR7</scope><scope>L6V</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20160101</creationdate><title>A Novel Online Multivariate Identification for Autotuning Speed Control in PMSM Drives</title><author>Liu, Yi ; Chen, Bing ; Ai, Wu ; Chen, Ke</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c317t-60048ec6679427353fb3ab970f8d374f0dddd91f8406b0e2690023c98fa216353</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Algorithms</topic><topic>Coefficient of friction</topic><topic>Control algorithms</topic><topic>Controllers</topic><topic>Friction</topic><topic>Identification</topic><topic>Inertia</topic><topic>Kalman filters</topic><topic>Least squares method</topic><topic>Load</topic><topic>Mathematical models</topic><topic>Moments of inertia</topic><topic>Parameter identification</topic><topic>Permanent magnets</topic><topic>Speed control</topic><topic>Synchronous motors</topic><topic>Trajectory analysis</topic><topic>Trajectory control</topic><topic>Velocity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Yi</creatorcontrib><creatorcontrib>Chen, Bing</creatorcontrib><creatorcontrib>Ai, Wu</creatorcontrib><creatorcontrib>Chen, Ke</creatorcontrib><collection>الدوريات العلمية والإحصائية - e-Marefa Academic and Statistical Periodicals</collection><collection>معرفة - المحتوى العربي الأكاديمي المتكامل - e-Marefa Academic Complete</collection><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access Journals</collection><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>Middle East & Africa Database</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><jtitle>Mathematical problems in engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Yi</au><au>Chen, Bing</au><au>Ai, Wu</au><au>Chen, Ke</au><au>Peng, Haipeng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Novel Online Multivariate Identification for Autotuning Speed Control in PMSM Drives</atitle><jtitle>Mathematical problems in engineering</jtitle><date>2016-01-01</date><risdate>2016</risdate><volume>2016</volume><issue>2016</issue><spage>1</spage><epage>13</epage><pages>1-13</pages><issn>1024-123X</issn><eissn>1563-5147</eissn><abstract>A novel online algorithm to identify the moment of inertia, viscous friction coefficient, and load torque of PMSM (Permanent Magnet Synchronous Motor) drives and a distinctive autotuning speed control scheme are presented. The proposed identification algorithm does not require motors run in a particular trajectory and only needs a short identification time. A Luenberger speed observer is introduced to eliminate noises which are generated by the detection of position signal and to improve the accuracy of identified parameters. Parameters of the speed controller are optimized by analyzing the mathematical model of the system and the formula of the PI controller. Compared to a standard recursive least squares method (RLSM) and traditional PI algorithm, the effectiveness of the proposed identification algorithm and autotuning speed control scheme are validated through simulations and experiments.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Publishing Corporation</pub><doi>10.1155/2016/1780710</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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| source | EZB-FREE-00999 freely available EZB journals; Wiley Online Library (Open Access Collection); Alma/SFX Local Collection |
| subjects | Algorithms Coefficient of friction Control algorithms Controllers Friction Identification Inertia Kalman filters Least squares method Load Mathematical models Moments of inertia Parameter identification Permanent magnets Speed control Synchronous motors Trajectory analysis Trajectory control Velocity |
| title | A Novel Online Multivariate Identification for Autotuning Speed Control in PMSM Drives |
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