Neural Stabilizing Controller Based on Co-evolutionary Predator-Prey Particle Swarm Optimization
In this paper, an approach based on particle swarm optimization (PSO) and Lyapunov method to construct neural stabilizing controller is presented. The procedure to learn the value of neural network is formulated as min-max problem. And the problem is solved by the co-evolutionary predator-prey PSO w...
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| creator | Ishigame, A. Higashitani, M. Yasuda, K. |
| description | In this paper, an approach based on particle swarm optimization (PSO) and Lyapunov method to construct neural stabilizing controller is presented. The procedure to learn the value of neural network is formulated as min-max problem. And the problem is solved by the co-evolutionary predator-prey PSO which we newly propose. The PSO is able to generate an optimal set of parameters for neural controller. And then, the proposed neural controller can be satisfied the Lyapunov stability condition. The proposed method is validated through numerical simulations with power system stabilizing control problem comparing to the conventional control method. |
| doi_str_mv | 10.1109/ICSMC.2006.384816 |
| format | Conference Proceeding |
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The proposed method is validated through numerical simulations with power system stabilizing control problem comparing to the conventional control method.</description><subject>Control system synthesis</subject><subject>Lyapunov method</subject><subject>Neural networks</subject><subject>Numerical simulation</subject><subject>Optimal control</subject><subject>Particle swarm optimization</subject><subject>Power system control</subject><subject>Power system simulation</subject><subject>Power system stability</subject><subject>Power systems</subject><issn>1062-922X</issn><issn>2577-1655</issn><isbn>1424400996</isbn><isbn>9781424400997</isbn><isbn>1424401003</isbn><isbn>9781424401000</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2006</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1T9lKAzEUjRvYVj9AfMkPpN7smUcd3KBaoQq-1UznViLpTMmkiv16p6hP92wcziXkjMOYcygu7svZQzkWAGYsnXLc7JEhV0Ip4ABynwyEtpZxo_XBvwFFYQ7JgIMRrBDi9ZgMu-4DQIDibkDeHnGTfKSz7KsQwzY077Rsm5zaGDHRK99hTdum1xh-tnGTQ9v49E2fEtY-t4n1oGc-5bCISGdfPq3odJ3DKmz9LnxCjpY-dnj6d0fk5eb6ubxjk-ntfXk5YYFbnZnhWlmBXitjVI3L2mi5268Kqb00Rf9gVS3A11ghWF5ZJ4Q0zqHSii-skCNy_tsbEHG-TmHVz5wrYZV2XP4AvWtYGA</recordid><startdate>200610</startdate><enddate>200610</enddate><creator>Ishigame, A.</creator><creator>Higashitani, M.</creator><creator>Yasuda, K.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>200610</creationdate><title>Neural Stabilizing Controller Based on Co-evolutionary Predator-Prey Particle Swarm Optimization</title><author>Ishigame, A. ; Higashitani, M. ; Yasuda, K.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-615472ea54664defd65342444935a369010bbc0adebe071b78223688e4541c723</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Control system synthesis</topic><topic>Lyapunov method</topic><topic>Neural networks</topic><topic>Numerical simulation</topic><topic>Optimal control</topic><topic>Particle swarm optimization</topic><topic>Power system control</topic><topic>Power system simulation</topic><topic>Power system stability</topic><topic>Power systems</topic><toplevel>online_resources</toplevel><creatorcontrib>Ishigame, A.</creatorcontrib><creatorcontrib>Higashitani, M.</creatorcontrib><creatorcontrib>Yasuda, K.</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><au>Higashitani, M.</au><au>Yasuda, K.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Neural Stabilizing Controller Based on Co-evolutionary Predator-Prey Particle Swarm Optimization</atitle><btitle>2006 IEEE International Conference on Systems, Man and Cybernetics</btitle><stitle>ICSMC</stitle><date>2006-10</date><risdate>2006</risdate><volume>5</volume><spage>4337</spage><epage>4342</epage><pages>4337-4342</pages><issn>1062-922X</issn><eissn>2577-1655</eissn><isbn>1424400996</isbn><isbn>9781424400997</isbn><eisbn>1424401003</eisbn><eisbn>9781424401000</eisbn><abstract>In this paper, an approach based on particle swarm optimization (PSO) and Lyapunov method to construct neural stabilizing controller is presented. The procedure to learn the value of neural network is formulated as min-max problem. And the problem is solved by the co-evolutionary predator-prey PSO which we newly propose. The PSO is able to generate an optimal set of parameters for neural controller. And then, the proposed neural controller can be satisfied the Lyapunov stability condition. The proposed method is validated through numerical simulations with power system stabilizing control problem comparing to the conventional control method.</abstract><pub>IEEE</pub><doi>10.1109/ICSMC.2006.384816</doi><tpages>6</tpages></addata></record> |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Control system synthesis Lyapunov method Neural networks Numerical simulation Optimal control Particle swarm optimization Power system control Power system simulation Power system stability Power systems |
| title | Neural Stabilizing Controller Based on Co-evolutionary Predator-Prey Particle Swarm Optimization |
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