Evolutionary Design of Both Topologies and Parameters of a Hybrid Dynamical System

This paper investigates the issue of evolutionary design of open-ended plants for hybrid dynamical systems, i.e., both their topologies and parameters. Hybrid bond graphs (HBGs) are used to represent dynamical systems involving both continuous and discrete system dynamics. Genetic programming, with...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on evolutionary computation 2012-06, Vol.16 (3), p.391-405
Hauptverfasser: Dupuis, J., Zhun Fan, Goodman, E. D.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 405
container_issue 3
container_start_page 391
container_title IEEE transactions on evolutionary computation
container_volume 16
creator Dupuis, J.
Zhun Fan
Goodman, E. D.
description This paper investigates the issue of evolutionary design of open-ended plants for hybrid dynamical systems, i.e., both their topologies and parameters. Hybrid bond graphs (HBGs) are used to represent dynamical systems involving both continuous and discrete system dynamics. Genetic programming, with some special mechanisms incorporated, is used as a search tool to explore the open-ended design space of hybrid bond graphs. Combination of these two tools, i.e., HBGs and genetic programming, leads to an approach called HBGGP that can automatically generate viable design candidates of hybrid dynamical systems that fulfill predefined design specifications. A comprehensive investigation of a case study of DC-DC converter design demonstrates the feasibility and effectiveness of the HBGGP approach. Important characteristics of the approach are also discussed, with some future research directions pointed out.
doi_str_mv 10.1109/TEVC.2011.2159724
format Article
fullrecord <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_proquest_miscellaneous_1671266771</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6045329</ieee_id><sourcerecordid>1671266771</sourcerecordid><originalsourceid>FETCH-LOGICAL-c356t-92be58ccfdb3a4c4e5792bcbec329e671d99eafb0957e1e465cf6a773f84bc5d3</originalsourceid><addsrcrecordid>eNpdkMtKxDAUhosoeH0AcRMQwU3HnDaXZqnjeAFB0VHclTQ91UjbjElHmLc3ZQYXrhKS7_8550uSY6ATAKou5rO36SSjAJMMuJIZ20r2QDFIKc3EdrzTQqVSFu-7yX4IX5QC46D2kufZj2uXg3W99ityjcF-9MQ15MoNn2TuFq51HxYD0X1NnrTXHQ7ow0hocreqvK3J9arXnTW6JS-rMGB3mOw0ug14tDkPkteb2Xx6lz483t5PLx9Sk3MxpCqrkBfGNHWVa2YYchmfTIUmzxQKCbVSqJuKKi4RkAluGqGlzJuCVYbX-UFyvu5dePe9xDCUnQ0G21b36JahhNiRCSElRPT0H_rllr6P05VAQSqWF2KkYE0Z70Lw2JQLb7voJULlaLkcLZej5XJjOWbONs06RAWN172x4S-YCUolL0buZM1ZRPz7FpTxuG3-C3oRhac</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1017943861</pqid></control><display><type>article</type><title>Evolutionary Design of Both Topologies and Parameters of a Hybrid Dynamical System</title><source>IEEE/IET Electronic Library (IEL)</source><creator>Dupuis, J. ; Zhun Fan ; Goodman, E. D.</creator><creatorcontrib>Dupuis, J. ; Zhun Fan ; Goodman, E. D.</creatorcontrib><description>This paper investigates the issue of evolutionary design of open-ended plants for hybrid dynamical systems, i.e., both their topologies and parameters. Hybrid bond graphs (HBGs) are used to represent dynamical systems involving both continuous and discrete system dynamics. Genetic programming, with some special mechanisms incorporated, is used as a search tool to explore the open-ended design space of hybrid bond graphs. Combination of these two tools, i.e., HBGs and genetic programming, leads to an approach called HBGGP that can automatically generate viable design candidates of hybrid dynamical systems that fulfill predefined design specifications. A comprehensive investigation of a case study of DC-DC converter design demonstrates the feasibility and effectiveness of the HBGGP approach. Important characteristics of the approach are also discussed, with some future research directions pointed out.</description><identifier>ISSN: 1089-778X</identifier><identifier>EISSN: 1941-0026</identifier><identifier>DOI: 10.1109/TEVC.2011.2159724</identifier><identifier>CODEN: ITEVF5</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Applied sciences ; Artificial intelligence ; Automated design ; bond graphs ; Computer science; control theory; systems ; Control theory. Systems ; Convertors ; Design engineering ; Dynamical systems ; Electrical engineering. Electrical power engineering ; Electrical machines ; Embryo ; Encoding ; Evolutionary ; evolutionary design ; Evolutionary design method ; Exact sciences and technology ; Genetic programming ; Genetics ; hybrid mechatronic systems ; Junctions ; Mechatronics ; Modelling and identification ; Programming ; Switches ; Topology</subject><ispartof>IEEE transactions on evolutionary computation, 2012-06, Vol.16 (3), p.391-405</ispartof><rights>2015 INIST-CNRS</rights><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Jun 2012</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c356t-92be58ccfdb3a4c4e5792bcbec329e671d99eafb0957e1e465cf6a773f84bc5d3</citedby><cites>FETCH-LOGICAL-c356t-92be58ccfdb3a4c4e5792bcbec329e671d99eafb0957e1e465cf6a773f84bc5d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6045329$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6045329$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=26007584$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Dupuis, J.</creatorcontrib><creatorcontrib>Zhun Fan</creatorcontrib><creatorcontrib>Goodman, E. D.</creatorcontrib><title>Evolutionary Design of Both Topologies and Parameters of a Hybrid Dynamical System</title><title>IEEE transactions on evolutionary computation</title><addtitle>TEVC</addtitle><description>This paper investigates the issue of evolutionary design of open-ended plants for hybrid dynamical systems, i.e., both their topologies and parameters. Hybrid bond graphs (HBGs) are used to represent dynamical systems involving both continuous and discrete system dynamics. Genetic programming, with some special mechanisms incorporated, is used as a search tool to explore the open-ended design space of hybrid bond graphs. Combination of these two tools, i.e., HBGs and genetic programming, leads to an approach called HBGGP that can automatically generate viable design candidates of hybrid dynamical systems that fulfill predefined design specifications. A comprehensive investigation of a case study of DC-DC converter design demonstrates the feasibility and effectiveness of the HBGGP approach. Important characteristics of the approach are also discussed, with some future research directions pointed out.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Automated design</subject><subject>bond graphs</subject><subject>Computer science; control theory; systems</subject><subject>Control theory. Systems</subject><subject>Convertors</subject><subject>Design engineering</subject><subject>Dynamical systems</subject><subject>Electrical engineering. Electrical power engineering</subject><subject>Electrical machines</subject><subject>Embryo</subject><subject>Encoding</subject><subject>Evolutionary</subject><subject>evolutionary design</subject><subject>Evolutionary design method</subject><subject>Exact sciences and technology</subject><subject>Genetic programming</subject><subject>Genetics</subject><subject>hybrid mechatronic systems</subject><subject>Junctions</subject><subject>Mechatronics</subject><subject>Modelling and identification</subject><subject>Programming</subject><subject>Switches</subject><subject>Topology</subject><issn>1089-778X</issn><issn>1941-0026</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkMtKxDAUhosoeH0AcRMQwU3HnDaXZqnjeAFB0VHclTQ91UjbjElHmLc3ZQYXrhKS7_8550uSY6ATAKou5rO36SSjAJMMuJIZ20r2QDFIKc3EdrzTQqVSFu-7yX4IX5QC46D2kufZj2uXg3W99ityjcF-9MQ15MoNn2TuFq51HxYD0X1NnrTXHQ7ow0hocreqvK3J9arXnTW6JS-rMGB3mOw0ug14tDkPkteb2Xx6lz483t5PLx9Sk3MxpCqrkBfGNHWVa2YYchmfTIUmzxQKCbVSqJuKKi4RkAluGqGlzJuCVYbX-UFyvu5dePe9xDCUnQ0G21b36JahhNiRCSElRPT0H_rllr6P05VAQSqWF2KkYE0Z70Lw2JQLb7voJULlaLkcLZej5XJjOWbONs06RAWN172x4S-YCUolL0buZM1ZRPz7FpTxuG3-C3oRhac</recordid><startdate>20120601</startdate><enddate>20120601</enddate><creator>Dupuis, J.</creator><creator>Zhun Fan</creator><creator>Goodman, E. D.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>F28</scope><scope>FR3</scope></search><sort><creationdate>20120601</creationdate><title>Evolutionary Design of Both Topologies and Parameters of a Hybrid Dynamical System</title><author>Dupuis, J. ; Zhun Fan ; Goodman, E. D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c356t-92be58ccfdb3a4c4e5792bcbec329e671d99eafb0957e1e465cf6a773f84bc5d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Automated design</topic><topic>bond graphs</topic><topic>Computer science; control theory; systems</topic><topic>Control theory. Systems</topic><topic>Convertors</topic><topic>Design engineering</topic><topic>Dynamical systems</topic><topic>Electrical engineering. Electrical power engineering</topic><topic>Electrical machines</topic><topic>Embryo</topic><topic>Encoding</topic><topic>Evolutionary</topic><topic>evolutionary design</topic><topic>Evolutionary design method</topic><topic>Exact sciences and technology</topic><topic>Genetic programming</topic><topic>Genetics</topic><topic>hybrid mechatronic systems</topic><topic>Junctions</topic><topic>Mechatronics</topic><topic>Modelling and identification</topic><topic>Programming</topic><topic>Switches</topic><topic>Topology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dupuis, J.</creatorcontrib><creatorcontrib>Zhun Fan</creatorcontrib><creatorcontrib>Goodman, E. D.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998–Present</collection><collection>IEEE/IET Electronic Library (IEL)</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology 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><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE transactions on evolutionary computation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Dupuis, J.</au><au>Zhun Fan</au><au>Goodman, E. D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evolutionary Design of Both Topologies and Parameters of a Hybrid Dynamical System</atitle><jtitle>IEEE transactions on evolutionary computation</jtitle><stitle>TEVC</stitle><date>2012-06-01</date><risdate>2012</risdate><volume>16</volume><issue>3</issue><spage>391</spage><epage>405</epage><pages>391-405</pages><issn>1089-778X</issn><eissn>1941-0026</eissn><coden>ITEVF5</coden><abstract>This paper investigates the issue of evolutionary design of open-ended plants for hybrid dynamical systems, i.e., both their topologies and parameters. Hybrid bond graphs (HBGs) are used to represent dynamical systems involving both continuous and discrete system dynamics. Genetic programming, with some special mechanisms incorporated, is used as a search tool to explore the open-ended design space of hybrid bond graphs. Combination of these two tools, i.e., HBGs and genetic programming, leads to an approach called HBGGP that can automatically generate viable design candidates of hybrid dynamical systems that fulfill predefined design specifications. A comprehensive investigation of a case study of DC-DC converter design demonstrates the feasibility and effectiveness of the HBGGP approach. Important characteristics of the approach are also discussed, with some future research directions pointed out.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/TEVC.2011.2159724</doi><tpages>15</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1089-778X
ispartof IEEE transactions on evolutionary computation, 2012-06, Vol.16 (3), p.391-405
issn 1089-778X
1941-0026
language eng
recordid cdi_proquest_miscellaneous_1671266771
source IEEE/IET Electronic Library (IEL)
subjects Applied sciences
Artificial intelligence
Automated design
bond graphs
Computer science
control theory
systems
Control theory. Systems
Convertors
Design engineering
Dynamical systems
Electrical engineering. Electrical power engineering
Electrical machines
Embryo
Encoding
Evolutionary
evolutionary design
Evolutionary design method
Exact sciences and technology
Genetic programming
Genetics
hybrid mechatronic systems
Junctions
Mechatronics
Modelling and identification
Programming
Switches
Topology
title Evolutionary Design of Both Topologies and Parameters of a Hybrid Dynamical System
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-14T13%3A57%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Evolutionary%20Design%20of%20Both%20Topologies%20and%20Parameters%20of%20a%20Hybrid%20Dynamical%20System&rft.jtitle=IEEE%20transactions%20on%20evolutionary%20computation&rft.au=Dupuis,%20J.&rft.date=2012-06-01&rft.volume=16&rft.issue=3&rft.spage=391&rft.epage=405&rft.pages=391-405&rft.issn=1089-778X&rft.eissn=1941-0026&rft.coden=ITEVF5&rft_id=info:doi/10.1109/TEVC.2011.2159724&rft_dat=%3Cproquest_RIE%3E1671266771%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1017943861&rft_id=info:pmid/&rft_ieee_id=6045329&rfr_iscdi=true