Adaptive fuzzy decentralized control of robot manipulators
In this paper an adaptive fuzzy decentralized control algorithm for trajectory tracking of robot manipulators is developed. The proposed decentralized control algorithm allows the overall closed-loop system to be stabilized while making the tracking error to be uniformly ultimately bounded (UUB), wi...
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| creator | Sadati, N. Elhamifar, E. |
| description | In this paper an adaptive fuzzy decentralized control algorithm for trajectory tracking of robot manipulators is developed. The proposed decentralized control algorithm allows the overall closed-loop system to be stabilized while making the tracking error to be uniformly ultimately bounded (UUB), without having any prior knowledge of the robot manipulator dynamics. The interconnections in the dynamic equations of each subsystem are considered with unknown nonlinear bounds. The adaptive fuzzy neural networks (AFNNs) are proposed to model the unknown nonlinear dynamics of the robots and the interconnection terms. Using Lyapunov method, the stability of the overall system is investigated |
| doi_str_mv | 10.1109/ICIECA.2005.1644352 |
| format | Conference Proceeding |
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The proposed decentralized control algorithm allows the overall closed-loop system to be stabilized while making the tracking error to be uniformly ultimately bounded (UUB), without having any prior knowledge of the robot manipulator dynamics. The interconnections in the dynamic equations of each subsystem are considered with unknown nonlinear bounds. The adaptive fuzzy neural networks (AFNNs) are proposed to model the unknown nonlinear dynamics of the robots and the interconnection terms. Using Lyapunov method, the stability of the overall system is investigated</description><identifier>ISBN: 9780780394193</identifier><identifier>ISBN: 0780394194</identifier><identifier>DOI: 10.1109/ICIECA.2005.1644352</identifier><language>eng</language><publisher>IEEE</publisher><subject>Adaptive control ; Distributed control ; Error correction ; Fuzzy control ; Manipulator dynamics ; Nonlinear dynamical systems ; Nonlinear equations ; Programmable control ; Robots ; Trajectory</subject><ispartof>2005 International Conference on Industrial Electronics and Control Applications, 2005, p.6 pp.-6</ispartof><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1644352$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2051,4035,4036,27904,54899</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1644352$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Sadati, N.</creatorcontrib><creatorcontrib>Elhamifar, E.</creatorcontrib><title>Adaptive fuzzy decentralized control of robot manipulators</title><title>2005 International Conference on Industrial Electronics and Control Applications</title><addtitle>ICIECA</addtitle><description>In this paper an adaptive fuzzy decentralized control algorithm for trajectory tracking of robot manipulators is developed. The proposed decentralized control algorithm allows the overall closed-loop system to be stabilized while making the tracking error to be uniformly ultimately bounded (UUB), without having any prior knowledge of the robot manipulator dynamics. The interconnections in the dynamic equations of each subsystem are considered with unknown nonlinear bounds. The adaptive fuzzy neural networks (AFNNs) are proposed to model the unknown nonlinear dynamics of the robots and the interconnection terms. Using Lyapunov method, the stability of the overall system is investigated</description><subject>Adaptive control</subject><subject>Distributed control</subject><subject>Error correction</subject><subject>Fuzzy control</subject><subject>Manipulator dynamics</subject><subject>Nonlinear dynamical systems</subject><subject>Nonlinear equations</subject><subject>Programmable control</subject><subject>Robots</subject><subject>Trajectory</subject><isbn>9780780394193</isbn><isbn>0780394194</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2005</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj01qwzAUhAWl0JL6BNnoAnb08yRZ3RmTtoZANu06yPITqDiRsZ1CfPoYmmFgvtUwQ8iWs4JzZndN3ezrqhCMqYJrAKnEE8msKdlqaYFb-UKyafplq0ABcHgl71Xnhjn-IQ3XZbnRDj1e5tH1ccGO-rRy6mkKdExtmunZXeJw7d2cxumNPAfXT5g9ckN-Pvbf9Vd-OH42dXXII18n5MFYrhg4GVqndOlLLwS2ISBjOigflPHegdClVZ3QissVOwHeGOuwBCY3ZPvfGxHxNIzx7Mbb6fFQ3gFtPUbj</recordid><startdate>2005</startdate><enddate>2005</enddate><creator>Sadati, N.</creator><creator>Elhamifar, E.</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>Adaptive fuzzy decentralized control of robot manipulators</title><author>Sadati, N. ; Elhamifar, E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i1352-f791504a3fba568c8c22ebffe006f5cf57cca426895d26513268d24c779ae8403</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Adaptive control</topic><topic>Distributed control</topic><topic>Error correction</topic><topic>Fuzzy control</topic><topic>Manipulator dynamics</topic><topic>Nonlinear dynamical systems</topic><topic>Nonlinear equations</topic><topic>Programmable control</topic><topic>Robots</topic><topic>Trajectory</topic><toplevel>online_resources</toplevel><creatorcontrib>Sadati, N.</creatorcontrib><creatorcontrib>Elhamifar, E.</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>Sadati, N.</au><au>Elhamifar, E.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Adaptive fuzzy decentralized control of robot manipulators</atitle><btitle>2005 International Conference on Industrial Electronics and Control Applications</btitle><stitle>ICIECA</stitle><date>2005</date><risdate>2005</risdate><spage>6 pp.</spage><epage>6</epage><pages>6 pp.-6</pages><isbn>9780780394193</isbn><isbn>0780394194</isbn><abstract>In this paper an adaptive fuzzy decentralized control algorithm for trajectory tracking of robot manipulators is developed. The proposed decentralized control algorithm allows the overall closed-loop system to be stabilized while making the tracking error to be uniformly ultimately bounded (UUB), without having any prior knowledge of the robot manipulator dynamics. The interconnections in the dynamic equations of each subsystem are considered with unknown nonlinear bounds. The adaptive fuzzy neural networks (AFNNs) are proposed to model the unknown nonlinear dynamics of the robots and the interconnection terms. Using Lyapunov method, the stability of the overall system is investigated</abstract><pub>IEEE</pub><doi>10.1109/ICIECA.2005.1644352</doi><oa>free_for_read</oa></addata></record> |
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| ispartof | 2005 International Conference on Industrial Electronics and Control Applications, 2005, p.6 pp.-6 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Adaptive control Distributed control Error correction Fuzzy control Manipulator dynamics Nonlinear dynamical systems Nonlinear equations Programmable control Robots Trajectory |
| title | Adaptive fuzzy decentralized control of robot manipulators |
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