Partial, noisy and qualitative models for adaptive critic based neurocontrol
The roles of plant models in adaptive critic methods for approximate dynamic programming are considered, with primary focus given to the dynamic heuristic programming (DHP) methodology. For complete system identification, partial, approximate, and qualitative models of plant dynamics are considered....
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Tagungsbericht |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 2275 vol.4 |
|---|---|
| container_issue | |
| container_start_page | 2271 |
| container_title | |
| container_volume | 4 |
| creator | Shannon, T.T. |
| description | The roles of plant models in adaptive critic methods for approximate dynamic programming are considered, with primary focus given to the dynamic heuristic programming (DHP) methodology. For complete system identification, partial, approximate, and qualitative models of plant dynamics are considered. Such models are found to be sufficient for successful controller design. As classification is in general easier than regression, the results for qualitative models suggest an avenue for simplifying ongoing system identification in adaptive control applications. |
| doi_str_mv | 10.1109/IJCNN.1999.833416 |
| format | Conference Proceeding |
| fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_833416</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>833416</ieee_id><sourcerecordid>833416</sourcerecordid><originalsourceid>FETCH-ieee_primary_8334163</originalsourceid><addsrcrecordid>eNp9jksKwjAUAIMf8HsAXeUAtr40pm3WoqiIuHBfnm2ESGw0iYK3V9S1q4GZzRAyYhAzBnK63sx3u5hJKeOc8xlLG6TLhMgjLiFpkh5kOXAhEpm23gFkHmUiSzuk5_0ZIIVsJrtku0cXNJoJra32T4p1RW93NDpg0A9FL7ZSxtOTdRQrvH5c6XTQJT2iVxWt1d3Z0tbBWTMg7RMar4Y_9sl4uTjMV5FWShVXpy_onsV3lv-NL2t2QKM</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Partial, noisy and qualitative models for adaptive critic based neurocontrol</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Shannon, T.T.</creator><creatorcontrib>Shannon, T.T.</creatorcontrib><description>The roles of plant models in adaptive critic methods for approximate dynamic programming are considered, with primary focus given to the dynamic heuristic programming (DHP) methodology. For complete system identification, partial, approximate, and qualitative models of plant dynamics are considered. Such models are found to be sufficient for successful controller design. As classification is in general easier than regression, the results for qualitative models suggest an avenue for simplifying ongoing system identification in adaptive control applications.</description><identifier>ISSN: 1098-7576</identifier><identifier>ISBN: 0780355296</identifier><identifier>ISBN: 9780780355293</identifier><identifier>EISSN: 1558-3902</identifier><identifier>DOI: 10.1109/IJCNN.1999.833416</identifier><language>eng</language><publisher>IEEE</publisher><subject>Adaptive control ; Control systems ; Costs ; Dynamic programming ; Functional programming ; Optimal control ; Programmable control ; State estimation ; System identification ; Utility programs</subject><ispartof>IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 1999, Vol.4, p.2271-2275 vol.4</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/833416$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,4050,4051,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/833416$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Shannon, T.T.</creatorcontrib><title>Partial, noisy and qualitative models for adaptive critic based neurocontrol</title><title>IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339)</title><addtitle>IJCNN</addtitle><description>The roles of plant models in adaptive critic methods for approximate dynamic programming are considered, with primary focus given to the dynamic heuristic programming (DHP) methodology. For complete system identification, partial, approximate, and qualitative models of plant dynamics are considered. Such models are found to be sufficient for successful controller design. As classification is in general easier than regression, the results for qualitative models suggest an avenue for simplifying ongoing system identification in adaptive control applications.</description><subject>Adaptive control</subject><subject>Control systems</subject><subject>Costs</subject><subject>Dynamic programming</subject><subject>Functional programming</subject><subject>Optimal control</subject><subject>Programmable control</subject><subject>State estimation</subject><subject>System identification</subject><subject>Utility programs</subject><issn>1098-7576</issn><issn>1558-3902</issn><isbn>0780355296</isbn><isbn>9780780355293</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1999</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNp9jksKwjAUAIMf8HsAXeUAtr40pm3WoqiIuHBfnm2ESGw0iYK3V9S1q4GZzRAyYhAzBnK63sx3u5hJKeOc8xlLG6TLhMgjLiFpkh5kOXAhEpm23gFkHmUiSzuk5_0ZIIVsJrtku0cXNJoJra32T4p1RW93NDpg0A9FL7ZSxtOTdRQrvH5c6XTQJT2iVxWt1d3Z0tbBWTMg7RMar4Y_9sl4uTjMV5FWShVXpy_onsV3lv-NL2t2QKM</recordid><startdate>1999</startdate><enddate>1999</enddate><creator>Shannon, T.T.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>1999</creationdate><title>Partial, noisy and qualitative models for adaptive critic based neurocontrol</title><author>Shannon, T.T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_8334163</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1999</creationdate><topic>Adaptive control</topic><topic>Control systems</topic><topic>Costs</topic><topic>Dynamic programming</topic><topic>Functional programming</topic><topic>Optimal control</topic><topic>Programmable control</topic><topic>State estimation</topic><topic>System identification</topic><topic>Utility programs</topic><toplevel>online_resources</toplevel><creatorcontrib>Shannon, T.T.</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>Shannon, T.T.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Partial, noisy and qualitative models for adaptive critic based neurocontrol</atitle><btitle>IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339)</btitle><stitle>IJCNN</stitle><date>1999</date><risdate>1999</risdate><volume>4</volume><spage>2271</spage><epage>2275 vol.4</epage><pages>2271-2275 vol.4</pages><issn>1098-7576</issn><eissn>1558-3902</eissn><isbn>0780355296</isbn><isbn>9780780355293</isbn><abstract>The roles of plant models in adaptive critic methods for approximate dynamic programming are considered, with primary focus given to the dynamic heuristic programming (DHP) methodology. For complete system identification, partial, approximate, and qualitative models of plant dynamics are considered. Such models are found to be sufficient for successful controller design. As classification is in general easier than regression, the results for qualitative models suggest an avenue for simplifying ongoing system identification in adaptive control applications.</abstract><pub>IEEE</pub><doi>10.1109/IJCNN.1999.833416</doi></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 1098-7576 |
| ispartof | IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 1999, Vol.4, p.2271-2275 vol.4 |
| issn | 1098-7576 1558-3902 |
| language | eng |
| recordid | cdi_ieee_primary_833416 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Adaptive control Control systems Costs Dynamic programming Functional programming Optimal control Programmable control State estimation System identification Utility programs |
| title | Partial, noisy and qualitative models for adaptive critic based neurocontrol |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T18%3A11%3A22IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Partial,%20noisy%20and%20qualitative%20models%20for%20adaptive%20critic%20based%20neurocontrol&rft.btitle=IJCNN'99.%20International%20Joint%20Conference%20on%20Neural%20Networks.%20Proceedings%20(Cat.%20No.99CH36339)&rft.au=Shannon,%20T.T.&rft.date=1999&rft.volume=4&rft.spage=2271&rft.epage=2275%20vol.4&rft.pages=2271-2275%20vol.4&rft.issn=1098-7576&rft.eissn=1558-3902&rft.isbn=0780355296&rft.isbn_list=9780780355293&rft_id=info:doi/10.1109/IJCNN.1999.833416&rft_dat=%3Cieee_6IE%3E833416%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=833416&rfr_iscdi=true |