Command filter‐based event‐triggered adaptive neural network control for uncertain nonlinear time‐delay systems
Summary In this article, the problem of command filter‐based adaptive event‐triggered neural network control is considered for a class of uncertain nonlinear systems with time delay. Lyapunov‐Krasovskii functionals and command filtered technology are utilized to address the problem of unknown time‐v...
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| Veröffentlicht in: | International journal of robust and nonlinear control 2020-11, Vol.30 (16), p.6363-6382 |
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| container_end_page | 6382 |
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| container_issue | 16 |
| container_start_page | 6363 |
| container_title | International journal of robust and nonlinear control |
| container_volume | 30 |
| creator | Li, Baomin Xia, Jianwei Sun, Wei Park, Ju H. Sun, Zong‐Yao |
| description | Summary
In this article, the problem of command filter‐based adaptive event‐triggered neural network control is considered for a class of uncertain nonlinear systems with time delay. Lyapunov‐Krasovskii functionals and command filtered technology are utilized to address the problem of unknown time‐varying delays and explosion of complexity, respectively. Furthermore, by fusing the event‐triggered mechanism, an adaptive tracking controller is designed. The proposed controller not only ensures that the system output eventually follows the desired reference signal in the sufficiently small neighborhood of zero but also reduces the communication resources from the controller to the actuator. Finally, the effectiveness of the proposed control method is verified by a simulation example. |
| doi_str_mv | 10.1002/rnc.5111 |
| format | Article |
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In this article, the problem of command filter‐based adaptive event‐triggered neural network control is considered for a class of uncertain nonlinear systems with time delay. Lyapunov‐Krasovskii functionals and command filtered technology are utilized to address the problem of unknown time‐varying delays and explosion of complexity, respectively. Furthermore, by fusing the event‐triggered mechanism, an adaptive tracking controller is designed. The proposed controller not only ensures that the system output eventually follows the desired reference signal in the sufficiently small neighborhood of zero but also reduces the communication resources from the controller to the actuator. Finally, the effectiveness of the proposed control method is verified by a simulation example.</description><identifier>ISSN: 1049-8923</identifier><identifier>EISSN: 1099-1239</identifier><identifier>DOI: 10.1002/rnc.5111</identifier><language>eng</language><publisher>Bognor Regis: Wiley Subscription Services, Inc</publisher><subject>Actuators ; Adaptive control ; Adaptive filters ; command filtered backstepping ; Computer simulation ; Control methods ; Control systems design ; Controllers ; Network control ; neural network control ; Neural networks ; Nonlinear control ; Nonlinear systems ; time delay ; Time delay systems ; Time lag ; Tracking control</subject><ispartof>International journal of robust and nonlinear control, 2020-11, Vol.30 (16), p.6363-6382</ispartof><rights>2020 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3301-5b28118fbb0a104ec18de624f4e98c5c04a206eaba5f364c65f71523d539aa1d3</citedby><cites>FETCH-LOGICAL-c3301-5b28118fbb0a104ec18de624f4e98c5c04a206eaba5f364c65f71523d539aa1d3</cites><orcidid>0000-0002-2102-9588 ; 0000-0002-0218-2333 ; 0000-0002-5330-9349</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Frnc.5111$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Frnc.5111$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids></links><search><creatorcontrib>Li, Baomin</creatorcontrib><creatorcontrib>Xia, Jianwei</creatorcontrib><creatorcontrib>Sun, Wei</creatorcontrib><creatorcontrib>Park, Ju H.</creatorcontrib><creatorcontrib>Sun, Zong‐Yao</creatorcontrib><title>Command filter‐based event‐triggered adaptive neural network control for uncertain nonlinear time‐delay systems</title><title>International journal of robust and nonlinear control</title><description>Summary
In this article, the problem of command filter‐based adaptive event‐triggered neural network control is considered for a class of uncertain nonlinear systems with time delay. Lyapunov‐Krasovskii functionals and command filtered technology are utilized to address the problem of unknown time‐varying delays and explosion of complexity, respectively. Furthermore, by fusing the event‐triggered mechanism, an adaptive tracking controller is designed. The proposed controller not only ensures that the system output eventually follows the desired reference signal in the sufficiently small neighborhood of zero but also reduces the communication resources from the controller to the actuator. Finally, the effectiveness of the proposed control method is verified by a simulation example.</description><subject>Actuators</subject><subject>Adaptive control</subject><subject>Adaptive filters</subject><subject>command filtered backstepping</subject><subject>Computer simulation</subject><subject>Control methods</subject><subject>Control systems design</subject><subject>Controllers</subject><subject>Network control</subject><subject>neural network control</subject><subject>Neural networks</subject><subject>Nonlinear control</subject><subject>Nonlinear systems</subject><subject>time delay</subject><subject>Time delay systems</subject><subject>Time lag</subject><subject>Tracking control</subject><issn>1049-8923</issn><issn>1099-1239</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp1kMtKxDAUhosoOI6CjxBw46Zjbu00Sxm8waAgug5pejJ0bJMxSUe68xF8Rp_EjOPW1X8uH__h_Fl2TvCMYEyvvNWzghBykE0IFiInlInDXc1FXgnKjrOTENYYpx3lk2xYuL5XtkGm7SL478-vWgVoEGzBxtRF365W4NNENWoT2y0gC4NXXZL44fwb0s5G7zpknEeD1eCjai2yznatBeVRbHtIRg10akRhDBH6cJodGdUFOPvTafZ6e_OyuM-XT3cPi-tlrhnDJC9qWhFSmbrGKj0AmlQNlJQbDqLShcZcUVyCqlVhWMl1WZg5KShrCiaUIg2bZhd734137wOEKNdu8DadlJTzis8F5vNEXe4p7V0IHozc-LZXfpQEy12oMoUqd6EmNN-jH20H47-cfH5c_PI_KGt9nA</recordid><startdate>20201110</startdate><enddate>20201110</enddate><creator>Li, Baomin</creator><creator>Xia, Jianwei</creator><creator>Sun, Wei</creator><creator>Park, Ju H.</creator><creator>Sun, Zong‐Yao</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-2102-9588</orcidid><orcidid>https://orcid.org/0000-0002-0218-2333</orcidid><orcidid>https://orcid.org/0000-0002-5330-9349</orcidid></search><sort><creationdate>20201110</creationdate><title>Command filter‐based event‐triggered adaptive neural network control for uncertain nonlinear time‐delay systems</title><author>Li, Baomin ; Xia, Jianwei ; Sun, Wei ; Park, Ju H. ; Sun, Zong‐Yao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3301-5b28118fbb0a104ec18de624f4e98c5c04a206eaba5f364c65f71523d539aa1d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Actuators</topic><topic>Adaptive control</topic><topic>Adaptive filters</topic><topic>command filtered backstepping</topic><topic>Computer simulation</topic><topic>Control methods</topic><topic>Control systems design</topic><topic>Controllers</topic><topic>Network control</topic><topic>neural network control</topic><topic>Neural networks</topic><topic>Nonlinear control</topic><topic>Nonlinear systems</topic><topic>time delay</topic><topic>Time delay systems</topic><topic>Time lag</topic><topic>Tracking control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Baomin</creatorcontrib><creatorcontrib>Xia, Jianwei</creatorcontrib><creatorcontrib>Sun, Wei</creatorcontrib><creatorcontrib>Park, Ju H.</creatorcontrib><creatorcontrib>Sun, Zong‐Yao</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>International journal of robust and nonlinear control</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Baomin</au><au>Xia, Jianwei</au><au>Sun, Wei</au><au>Park, Ju H.</au><au>Sun, Zong‐Yao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Command filter‐based event‐triggered adaptive neural network control for uncertain nonlinear time‐delay systems</atitle><jtitle>International journal of robust and nonlinear control</jtitle><date>2020-11-10</date><risdate>2020</risdate><volume>30</volume><issue>16</issue><spage>6363</spage><epage>6382</epage><pages>6363-6382</pages><issn>1049-8923</issn><eissn>1099-1239</eissn><abstract>Summary
In this article, the problem of command filter‐based adaptive event‐triggered neural network control is considered for a class of uncertain nonlinear systems with time delay. Lyapunov‐Krasovskii functionals and command filtered technology are utilized to address the problem of unknown time‐varying delays and explosion of complexity, respectively. Furthermore, by fusing the event‐triggered mechanism, an adaptive tracking controller is designed. The proposed controller not only ensures that the system output eventually follows the desired reference signal in the sufficiently small neighborhood of zero but also reduces the communication resources from the controller to the actuator. Finally, the effectiveness of the proposed control method is verified by a simulation example.</abstract><cop>Bognor Regis</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/rnc.5111</doi><tpages>20</tpages><orcidid>https://orcid.org/0000-0002-2102-9588</orcidid><orcidid>https://orcid.org/0000-0002-0218-2333</orcidid><orcidid>https://orcid.org/0000-0002-5330-9349</orcidid></addata></record> |
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| ispartof | International journal of robust and nonlinear control, 2020-11, Vol.30 (16), p.6363-6382 |
| issn | 1049-8923 1099-1239 |
| language | eng |
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| source | Wiley Journals |
| subjects | Actuators Adaptive control Adaptive filters command filtered backstepping Computer simulation Control methods Control systems design Controllers Network control neural network control Neural networks Nonlinear control Nonlinear systems time delay Time delay systems Time lag Tracking control |
| title | Command filter‐based event‐triggered adaptive neural network control for uncertain nonlinear time‐delay systems |
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