Precise Position Control in Air-bearing PMLSM System Using An Improved Anticipatory Fractional-Order Iterative Learning Control
The periodic motion of a permanent magnet linear synchronous motor (PMLSM) used in industrial applications requires considerable acceleration and deceleration at the start-stop stage, resulting in significant peak position errors. Moreover, thrust fluctuation due to the cogging effect, end effect, a...
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| Veröffentlicht in: | IEEE transactions on industrial electronics (1982) 2024-06, Vol.71 (6), p.1-10 |
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| creator | Wang, Mingyi Kang, Kai Zhang, Chengming Li, Liyi |
| description | The periodic motion of a permanent magnet linear synchronous motor (PMLSM) used in industrial applications requires considerable acceleration and deceleration at the start-stop stage, resulting in significant peak position errors. Moreover, thrust fluctuation due to the cogging effect, end effect, armature reaction, asymmetry of winding parameters, and time-varying electrical parameters will degrade the position-tracking precision at constant velocity. Thus, to avoid these impacts on position control accuracy, this paper proposes an improved anticipatory fractional-order iterative learning control (AFOILC), named the anticipatory lead fractional-order ILC (ALFOILC). ALFOILC is superior to the anticipatory \rm {D}^\alpha-type ILC (ADFOILC) regarding amplitude and phase compensation. Thus, ALFOILC increases the learnable band further. Moreover, this work analyzes the design, approximation, discretization, and tuning strategy for the decoupling parameters associated with ALFOILC. Finally, we build an experimental platform with an air-bearing PMLSM to validate the efficacy of ALFOILC through comparative experiments against ADFOILC and integer-order ILC. |
| doi_str_mv | 10.1109/TIE.2023.3290251 |
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Moreover, thrust fluctuation due to the cogging effect, end effect, armature reaction, asymmetry of winding parameters, and time-varying electrical parameters will degrade the position-tracking precision at constant velocity. Thus, to avoid these impacts on position control accuracy, this paper proposes an improved anticipatory fractional-order iterative learning control (AFOILC), named the anticipatory lead fractional-order ILC (ALFOILC). ALFOILC is superior to the anticipatory <inline-formula><tex-math notation="LaTeX">\rm {D}^\alpha</tex-math></inline-formula>-type ILC (ADFOILC) regarding amplitude and phase compensation. Thus, ALFOILC increases the learnable band further. Moreover, this work analyzes the design, approximation, discretization, and tuning strategy for the decoupling parameters associated with ALFOILC. Finally, we build an experimental platform with an air-bearing PMLSM to validate the efficacy of ALFOILC through comparative experiments against ADFOILC and integer-order ILC.</description><identifier>ISSN: 0278-0046</identifier><identifier>EISSN: 1557-9948</identifier><identifier>DOI: 10.1109/TIE.2023.3290251</identifier><identifier>CODEN: ITIED6</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Acceleration ; Convergence ; Deceleration ; Decoupling ; Feedforward systems ; Fluctuations ; Industrial applications ; iterative learning control (ILC) ; Iterative methods ; Lead ; Learning ; Parameters ; Permanent magnet linear synchronous motor (PMLSM) ; Permanent magnets ; Position control ; Position errors ; Synchronous motors ; Tracking ; Tuning ; two-degree-of-freedom (2-DOF) control</subject><ispartof>IEEE transactions on industrial electronics (1982), 2024-06, Vol.71 (6), p.1-10</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c292t-fc67d3a5d1f5766c01879c2a5ab32b66015f3ceb26c2356cdebb0cd86f4b20e3</citedby><cites>FETCH-LOGICAL-c292t-fc67d3a5d1f5766c01879c2a5ab32b66015f3ceb26c2356cdebb0cd86f4b20e3</cites><orcidid>0000-0003-4920-9481 ; 0000-0002-6382-2891 ; 0000-0002-6562-4530 ; 0000-0003-0596-9454</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10173736$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10173736$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Wang, Mingyi</creatorcontrib><creatorcontrib>Kang, Kai</creatorcontrib><creatorcontrib>Zhang, Chengming</creatorcontrib><creatorcontrib>Li, Liyi</creatorcontrib><title>Precise Position Control in Air-bearing PMLSM System Using An Improved Anticipatory Fractional-Order Iterative Learning Control</title><title>IEEE transactions on industrial electronics (1982)</title><addtitle>TIE</addtitle><description>The periodic motion of a permanent magnet linear synchronous motor (PMLSM) used in industrial applications requires considerable acceleration and deceleration at the start-stop stage, resulting in significant peak position errors. Moreover, thrust fluctuation due to the cogging effect, end effect, armature reaction, asymmetry of winding parameters, and time-varying electrical parameters will degrade the position-tracking precision at constant velocity. Thus, to avoid these impacts on position control accuracy, this paper proposes an improved anticipatory fractional-order iterative learning control (AFOILC), named the anticipatory lead fractional-order ILC (ALFOILC). ALFOILC is superior to the anticipatory <inline-formula><tex-math notation="LaTeX">\rm {D}^\alpha</tex-math></inline-formula>-type ILC (ADFOILC) regarding amplitude and phase compensation. Thus, ALFOILC increases the learnable band further. Moreover, this work analyzes the design, approximation, discretization, and tuning strategy for the decoupling parameters associated with ALFOILC. Finally, we build an experimental platform with an air-bearing PMLSM to validate the efficacy of ALFOILC through comparative experiments against ADFOILC and integer-order ILC.</description><subject>Acceleration</subject><subject>Convergence</subject><subject>Deceleration</subject><subject>Decoupling</subject><subject>Feedforward systems</subject><subject>Fluctuations</subject><subject>Industrial applications</subject><subject>iterative learning control (ILC)</subject><subject>Iterative methods</subject><subject>Lead</subject><subject>Learning</subject><subject>Parameters</subject><subject>Permanent magnet linear synchronous motor (PMLSM)</subject><subject>Permanent magnets</subject><subject>Position control</subject><subject>Position errors</subject><subject>Synchronous motors</subject><subject>Tracking</subject><subject>Tuning</subject><subject>two-degree-of-freedom (2-DOF) control</subject><issn>0278-0046</issn><issn>1557-9948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkL1rwzAQxUVpoWnavUMHQWen-rBkewwhbQ0OCSSdhSyfi0JipZISyNR_vTbJ0OmO473fPR5Cz5RMKCXF26acTxhhfMJZQZigN2hEhciSokjzWzQiLMsTQlJ5jx5C2BJCU0HFCP2uPBgbAK9csNG6Ds9cF73bYdvhqfVJDdrb7huvFtV6gdfnEGGPv8Jwmna43B-8O0HT79Eae9DR-TN-99oMLL1Llr4Bj8sIXkd7Alz1uG4wX988ortW7wI8XecYbd7nm9lnUi0_ytm0SgwrWExaI7OGa9HQVmRSGkLzrDBMC11zVktJqGi5gZpJw7iQpoG6JqbJZZvWjAAfo9cLto_7c4QQ1dYdfR8wqJ5PWF5IKXoVuaiMdyF4aNXB2732Z0WJGlpWfctqaFldW-4tLxeLBYB_cprxjEv-B3IDejU</recordid><startdate>20240601</startdate><enddate>20240601</enddate><creator>Wang, Mingyi</creator><creator>Kang, Kai</creator><creator>Zhang, Chengming</creator><creator>Li, Liyi</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0003-4920-9481</orcidid><orcidid>https://orcid.org/0000-0002-6382-2891</orcidid><orcidid>https://orcid.org/0000-0002-6562-4530</orcidid><orcidid>https://orcid.org/0000-0003-0596-9454</orcidid></search><sort><creationdate>20240601</creationdate><title>Precise Position Control in Air-bearing PMLSM System Using An Improved Anticipatory Fractional-Order Iterative Learning Control</title><author>Wang, Mingyi ; Kang, Kai ; Zhang, Chengming ; Li, Liyi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c292t-fc67d3a5d1f5766c01879c2a5ab32b66015f3ceb26c2356cdebb0cd86f4b20e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Acceleration</topic><topic>Convergence</topic><topic>Deceleration</topic><topic>Decoupling</topic><topic>Feedforward systems</topic><topic>Fluctuations</topic><topic>Industrial applications</topic><topic>iterative learning control (ILC)</topic><topic>Iterative methods</topic><topic>Lead</topic><topic>Learning</topic><topic>Parameters</topic><topic>Permanent magnet linear synchronous motor (PMLSM)</topic><topic>Permanent magnets</topic><topic>Position control</topic><topic>Position errors</topic><topic>Synchronous motors</topic><topic>Tracking</topic><topic>Tuning</topic><topic>two-degree-of-freedom (2-DOF) control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Mingyi</creatorcontrib><creatorcontrib>Kang, Kai</creatorcontrib><creatorcontrib>Zhang, Chengming</creatorcontrib><creatorcontrib>Li, Liyi</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on industrial electronics (1982)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wang, Mingyi</au><au>Kang, Kai</au><au>Zhang, Chengming</au><au>Li, Liyi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Precise Position Control in Air-bearing PMLSM System Using An Improved Anticipatory Fractional-Order Iterative Learning Control</atitle><jtitle>IEEE transactions on industrial electronics (1982)</jtitle><stitle>TIE</stitle><date>2024-06-01</date><risdate>2024</risdate><volume>71</volume><issue>6</issue><spage>1</spage><epage>10</epage><pages>1-10</pages><issn>0278-0046</issn><eissn>1557-9948</eissn><coden>ITIED6</coden><abstract>The periodic motion of a permanent magnet linear synchronous motor (PMLSM) used in industrial applications requires considerable acceleration and deceleration at the start-stop stage, resulting in significant peak position errors. Moreover, thrust fluctuation due to the cogging effect, end effect, armature reaction, asymmetry of winding parameters, and time-varying electrical parameters will degrade the position-tracking precision at constant velocity. Thus, to avoid these impacts on position control accuracy, this paper proposes an improved anticipatory fractional-order iterative learning control (AFOILC), named the anticipatory lead fractional-order ILC (ALFOILC). ALFOILC is superior to the anticipatory <inline-formula><tex-math notation="LaTeX">\rm {D}^\alpha</tex-math></inline-formula>-type ILC (ADFOILC) regarding amplitude and phase compensation. Thus, ALFOILC increases the learnable band further. Moreover, this work analyzes the design, approximation, discretization, and tuning strategy for the decoupling parameters associated with ALFOILC. Finally, we build an experimental platform with an air-bearing PMLSM to validate the efficacy of ALFOILC through comparative experiments against ADFOILC and integer-order ILC.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TIE.2023.3290251</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-4920-9481</orcidid><orcidid>https://orcid.org/0000-0002-6382-2891</orcidid><orcidid>https://orcid.org/0000-0002-6562-4530</orcidid><orcidid>https://orcid.org/0000-0003-0596-9454</orcidid></addata></record> |
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| subjects | Acceleration Convergence Deceleration Decoupling Feedforward systems Fluctuations Industrial applications iterative learning control (ILC) Iterative methods Lead Learning Parameters Permanent magnet linear synchronous motor (PMLSM) Permanent magnets Position control Position errors Synchronous motors Tracking Tuning two-degree-of-freedom (2-DOF) control |
| title | Precise Position Control in Air-bearing PMLSM System Using An Improved Anticipatory Fractional-Order Iterative Learning Control |
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