Nonlinear stabilizing control based on particle swarm optimization with controlled mutation
In this paper, a new approach based on Particle Swarm Optimization (PSO) and Lyapunov method is presented to construct nonlinear stabilizing controller using a neural network. The procedure to learn the value of neural network is formulated as min-max problem. And the problem is solved by the co-evo...
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| creator | Ishigame, A. |
| description | In this paper, a new approach based on Particle Swarm Optimization (PSO) and Lyapunov method is presented to construct nonlinear stabilizing controller using a neural network. The procedure to learn the value of neural network is formulated as min-max problem. And the problem is solved by the co-evolutionary PSO with a controlled mutation that is newly proposed. The PSO is able to generate an optimal set of parameters for neural controller. Then, the proposed neural controller can be satisfied the Lyapunov stability condition and is validated through numerical simulations of stabilizing control problem. |
| doi_str_mv | 10.1109/ISIC.2007.4450962 |
| format | Conference Proceeding |
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Then, the proposed neural controller can be satisfied the Lyapunov stability condition and is validated through numerical simulations of stabilizing control problem.</description><subject>Control systems</subject><subject>Convergence</subject><subject>Cost function</subject><subject>Genetic mutations</subject><subject>Lyapunov method</subject><subject>Multi-layer neural network</subject><subject>Neural networks</subject><subject>Nonlinear control systems</subject><subject>Optimization methods</subject><subject>Particle swarm optimization</subject><issn>2158-9860</issn><issn>2158-9879</issn><isbn>9781424404407</isbn><isbn>1424404401</isbn><isbn>9781424404414</isbn><isbn>142440441X</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2007</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVkEtLAzEcxOMLrLUfQLzkC2z9J5vnURarC0UP9eahZHcTjeyLJFLsp3fRKniaw29mYAahKwJLQkDflJuyWFIAuWSMgxb0CC20VIRRxoAxwo7RjBKuMq2kPvnHQJ7-MQHn6CLGdwAKhMEMvTwOfet7awKOyVS-9Xvfv-J66FMYWlyZaBs89Hg0Ifm6tTjuTOjwMCbf-b1JfmI7n95-E-1k7z7SN7hEZ8600S4OOkeb1d1z8ZCtn-7L4nadeQ0pU9W0RhNTM0dBOTmJAUEtcF7nwuR1rQTNnbNCGcGddA3wRlJgleYNo_kcXf-0emvtdgy-M-Fze3gp_wJzmVjF</recordid><startdate>200710</startdate><enddate>200710</enddate><creator>Ishigame, A.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>200710</creationdate><title>Nonlinear stabilizing control based on particle swarm optimization with controlled mutation</title><author>Ishigame, A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-8b96291ac4f208f74f2a062e055c36a3cc8623ffe68a65f7fd05d7204b95d423</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Control systems</topic><topic>Convergence</topic><topic>Cost function</topic><topic>Genetic mutations</topic><topic>Lyapunov method</topic><topic>Multi-layer neural network</topic><topic>Neural networks</topic><topic>Nonlinear control systems</topic><topic>Optimization methods</topic><topic>Particle swarm optimization</topic><toplevel>online_resources</toplevel><creatorcontrib>Ishigame, A.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ishigame, A.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Nonlinear stabilizing control based on particle swarm optimization with controlled mutation</atitle><btitle>2007 IEEE 22nd International Symposium on Intelligent Control</btitle><stitle>ISIC</stitle><date>2007-10</date><risdate>2007</risdate><spage>652</spage><epage>657</epage><pages>652-657</pages><issn>2158-9860</issn><eissn>2158-9879</eissn><isbn>9781424404407</isbn><isbn>1424404401</isbn><eisbn>9781424404414</eisbn><eisbn>142440441X</eisbn><abstract>In this paper, a new approach based on Particle Swarm Optimization (PSO) and Lyapunov method is presented to construct nonlinear stabilizing controller using a neural network. 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| identifier | ISSN: 2158-9860 |
| ispartof | 2007 IEEE 22nd International Symposium on Intelligent Control, 2007, p.652-657 |
| issn | 2158-9860 2158-9879 |
| language | eng |
| recordid | cdi_ieee_primary_4450962 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Control systems Convergence Cost function Genetic mutations Lyapunov method Multi-layer neural network Neural networks Nonlinear control systems Optimization methods Particle swarm optimization |
| title | Nonlinear stabilizing control based on particle swarm optimization with controlled mutation |
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