Study on a recurrent functional link-based fuzzy neural network controller with improved particle swarm optimization
A recurrent functional link-based fuzzy neural network controller with improved particle swarm optimization is proposed to control the mover of a permanent-magnet synchronous motor (PMSM) servo drive to track periodic reference trajectories. First, a recurrent functional link-based fuzzy neural netw...
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| creator | Zhirong Guo Shunyi Xie Wei Gao |
| description | A recurrent functional link-based fuzzy neural network controller with improved particle swarm optimization is proposed to control the mover of a permanent-magnet synchronous motor (PMSM) servo drive to track periodic reference trajectories. First, a recurrent functional link-based fuzzy neural network is proposed to control the PMSM, and the connective weights of the recurrent functional link-base neural network, the mean value and standard deviation of Gaussian function are trained online by recurrent algorithm. Moreover, an improved particle swarm optimization (IPSO) is adopted in this study to adapt the learning rates to improve the learning capability and increase the speed of constringency. Finally, the control performance of the proposed method is verified by the simulated results. |
| doi_str_mv | 10.1109/ICEMI.2009.5274344 |
| format | Conference Proceeding |
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Finally, the control performance of the proposed method is verified by the simulated results.</description><identifier>ISBN: 1424438632</identifier><identifier>ISBN: 9781424438631</identifier><identifier>EISBN: 1424438640</identifier><identifier>EISBN: 9781424438648</identifier><identifier>DOI: 10.1109/ICEMI.2009.5274344</identifier><identifier>LCCN: 2009900515</identifier><language>eng</language><publisher>IEEE</publisher><subject>Error correction ; Fuzzy control ; fuzzy neural network ; Fuzzy neural networks ; Instruments ; Neural networks ; Nonlinear dynamical systems ; Particle swarm optimization ; Particle tracking ; permanent magnet synchronous motor ; recurrent function ; Recurrent neural networks ; Zirconium</subject><ispartof>2009 9th International Conference on Electronic Measurement & Instruments, 2009, p.3-1095-3-1100</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/5274344$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,777,781,786,787,2052,27906,54901</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5274344$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Zhirong Guo</creatorcontrib><creatorcontrib>Shunyi Xie</creatorcontrib><creatorcontrib>Wei Gao</creatorcontrib><title>Study on a recurrent functional link-based fuzzy neural network controller with improved particle swarm optimization</title><title>2009 9th International Conference on Electronic Measurement & Instruments</title><addtitle>ICEMI</addtitle><description>A recurrent functional link-based fuzzy neural network controller with improved particle swarm optimization is proposed to control the mover of a permanent-magnet synchronous motor (PMSM) servo drive to track periodic reference trajectories. 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Finally, the control performance of the proposed method is verified by the simulated results.</description><subject>Error correction</subject><subject>Fuzzy control</subject><subject>fuzzy neural network</subject><subject>Fuzzy neural networks</subject><subject>Instruments</subject><subject>Neural networks</subject><subject>Nonlinear dynamical systems</subject><subject>Particle swarm optimization</subject><subject>Particle tracking</subject><subject>permanent magnet synchronous motor</subject><subject>recurrent function</subject><subject>Recurrent neural networks</subject><subject>Zirconium</subject><isbn>1424438632</isbn><isbn>9781424438631</isbn><isbn>1424438640</isbn><isbn>9781424438648</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFUFFLwzAYjMhAN_cH9CV_oDNpkjZ5lDHdYOKDex9p8hXj2qSkqWP79XY48F6OO47jOIQeKVlQStTzZrl63yxyQtRC5CVnnN-gKeU550wWnNz-C5ZP0PQSVIQIKu7QvO-_yQgumBD8HqXPNNgTDh5rHMEMMYJPuB68SS543eDG-UNW6R7s6J7PJ-xhiKPvIR1DPGATfIqhaSDio0tf2LVdDD9jutMxOdMA7o86tjh0ybXurC-1D2hS66aH-ZVnaPe62i3X2fbjbbN82WZOkZSxapyoiZSUWUPqitgil9qUIJXl3ComoWJSFWBzYQutrJa1rkqqjNQlFJzN0NNfrQOAfRddq-Npf32M_QKcE2E9</recordid><startdate>200908</startdate><enddate>200908</enddate><creator>Zhirong Guo</creator><creator>Shunyi Xie</creator><creator>Wei Gao</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200908</creationdate><title>Study on a recurrent functional link-based fuzzy neural network controller with improved particle swarm optimization</title><author>Zhirong Guo ; Shunyi Xie ; Wei Gao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-3b355a08813dc0fb0d628ac7e89d44d938eb3896ed25d6a9da8fab719c8a7e643</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Error correction</topic><topic>Fuzzy control</topic><topic>fuzzy neural network</topic><topic>Fuzzy neural networks</topic><topic>Instruments</topic><topic>Neural networks</topic><topic>Nonlinear dynamical systems</topic><topic>Particle swarm optimization</topic><topic>Particle tracking</topic><topic>permanent magnet synchronous motor</topic><topic>recurrent function</topic><topic>Recurrent neural networks</topic><topic>Zirconium</topic><toplevel>online_resources</toplevel><creatorcontrib>Zhirong Guo</creatorcontrib><creatorcontrib>Shunyi Xie</creatorcontrib><creatorcontrib>Wei Gao</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>Zhirong Guo</au><au>Shunyi Xie</au><au>Wei Gao</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Study on a recurrent functional link-based fuzzy neural network controller with improved particle swarm optimization</atitle><btitle>2009 9th International Conference on Electronic Measurement & Instruments</btitle><stitle>ICEMI</stitle><date>2009-08</date><risdate>2009</risdate><spage>3-1095</spage><epage>3-1100</epage><pages>3-1095-3-1100</pages><isbn>1424438632</isbn><isbn>9781424438631</isbn><eisbn>1424438640</eisbn><eisbn>9781424438648</eisbn><abstract>A recurrent functional link-based fuzzy neural network controller with improved particle swarm optimization is proposed to control the mover of a permanent-magnet synchronous motor (PMSM) servo drive to track periodic reference trajectories. First, a recurrent functional link-based fuzzy neural network is proposed to control the PMSM, and the connective weights of the recurrent functional link-base neural network, the mean value and standard deviation of Gaussian function are trained online by recurrent algorithm. Moreover, an improved particle swarm optimization (IPSO) is adopted in this study to adapt the learning rates to improve the learning capability and increase the speed of constringency. Finally, the control performance of the proposed method is verified by the simulated results.</abstract><pub>IEEE</pub><doi>10.1109/ICEMI.2009.5274344</doi></addata></record> |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Error correction Fuzzy control fuzzy neural network Fuzzy neural networks Instruments Neural networks Nonlinear dynamical systems Particle swarm optimization Particle tracking permanent magnet synchronous motor recurrent function Recurrent neural networks Zirconium |
| title | Study on a recurrent functional link-based fuzzy neural network controller with improved particle swarm optimization |
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