Robust pole-placement for ellipsoidally uncertain systems
A technique is proposed for synthesizing pole-placement controllers capable of assigning the closed-loop poles of an family of plants inside a specified design region. The design is applicable to plants characterized by uncertain parameters that are known to lie inside an ellipsoid. Ellipsoidal para...
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| creator | Ballamudi, R.K. Crisalle, O.D. |
| description | A technique is proposed for synthesizing pole-placement controllers capable of assigning the closed-loop poles of an family of plants inside a specified design region. The design is applicable to plants characterized by uncertain parameters that are known to lie inside an ellipsoid. Ellipsoidal parametric uncertainty descriptions are particularly useful because they arise naturally in the context of parameter estimation, and hence have the advantage of being quantifiable using experimental input-output data. The control-design problem is posed as a minimax program that is shown to be convex, and that can be solved using numerical techniques with global convergence guarantees. |
| doi_str_mv | 10.1109/CDC.1995.478928 |
| format | Conference Proceeding |
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The design is applicable to plants characterized by uncertain parameters that are known to lie inside an ellipsoid. Ellipsoidal parametric uncertainty descriptions are particularly useful because they arise naturally in the context of parameter estimation, and hence have the advantage of being quantifiable using experimental input-output data. The control-design problem is posed as a minimax program that is shown to be convex, and that can be solved using numerical techniques with global convergence guarantees.</description><identifier>ISSN: 0191-2216</identifier><identifier>ISBN: 0780326857</identifier><identifier>ISBN: 9780780326859</identifier><identifier>DOI: 10.1109/CDC.1995.478928</identifier><language>eng</language><publisher>IEEE Control Systems Society</publisher><subject>Control system synthesis ; Convergence of numerical methods ; Ellipsoids ; Minimax techniques ; Optimal control ; Parameter estimation ; Robust control ; Robustness ; Uncertain systems ; Uncertainty</subject><ispartof>Proceedings of 1995 34th IEEE Conference on Decision and Control, 1995, Vol.4, p.4360-4367 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/478928$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,4050,4051,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/478928$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Ballamudi, R.K.</creatorcontrib><creatorcontrib>Crisalle, O.D.</creatorcontrib><title>Robust pole-placement for ellipsoidally uncertain systems</title><title>Proceedings of 1995 34th IEEE Conference on Decision and Control</title><addtitle>CDC</addtitle><description>A technique is proposed for synthesizing pole-placement controllers capable of assigning the closed-loop poles of an family of plants inside a specified design region. The design is applicable to plants characterized by uncertain parameters that are known to lie inside an ellipsoid. Ellipsoidal parametric uncertainty descriptions are particularly useful because they arise naturally in the context of parameter estimation, and hence have the advantage of being quantifiable using experimental input-output data. The control-design problem is posed as a minimax program that is shown to be convex, and that can be solved using numerical techniques with global convergence guarantees.</description><subject>Control system synthesis</subject><subject>Convergence of numerical methods</subject><subject>Ellipsoids</subject><subject>Minimax techniques</subject><subject>Optimal control</subject><subject>Parameter estimation</subject><subject>Robust control</subject><subject>Robustness</subject><subject>Uncertain systems</subject><subject>Uncertainty</subject><issn>0191-2216</issn><isbn>0780326857</isbn><isbn>9780780326859</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1995</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj8tKw0AUQAdUsK2uBVf5gcQ777lLiU8oCNKuyyRzAyOTB5l0kb9XqKuzOHDgMPbAoeIc8Kl-qSuOqCtlHQp3xbZgHUhhnLbXbAMceSkEN7dsm_MPADgwZsPwe2zOeSmmMVE5Jd9ST8NSdONcUEpxymMMPqW1OA8tzYuPQ5HXvFCf79hN51Om-3_u2PHt9VB_lPuv98_6eV9GbsVS2k4gkdWkdANCavLKBosYAhiyjfTBIErD4c-iB6-0kaRbrzUa0Sghd-zx0o1EdJrm2Pt5PV0u5S-MBUXo</recordid><startdate>1995</startdate><enddate>1995</enddate><creator>Ballamudi, R.K.</creator><creator>Crisalle, O.D.</creator><general>IEEE Control Systems Society</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>1995</creationdate><title>Robust pole-placement for ellipsoidally uncertain systems</title><author>Ballamudi, R.K. ; Crisalle, O.D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i172t-7f29ee75e45b0235ea47d799dd06e7b3ad6993610b029a0a4563e5ca55962b423</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1995</creationdate><topic>Control system synthesis</topic><topic>Convergence of numerical methods</topic><topic>Ellipsoids</topic><topic>Minimax techniques</topic><topic>Optimal control</topic><topic>Parameter estimation</topic><topic>Robust control</topic><topic>Robustness</topic><topic>Uncertain systems</topic><topic>Uncertainty</topic><toplevel>online_resources</toplevel><creatorcontrib>Ballamudi, R.K.</creatorcontrib><creatorcontrib>Crisalle, O.D.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ballamudi, R.K.</au><au>Crisalle, O.D.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Robust pole-placement for ellipsoidally uncertain systems</atitle><btitle>Proceedings of 1995 34th IEEE Conference on Decision and Control</btitle><stitle>CDC</stitle><date>1995</date><risdate>1995</risdate><volume>4</volume><spage>4360</spage><epage>4367 vol.4</epage><pages>4360-4367 vol.4</pages><issn>0191-2216</issn><isbn>0780326857</isbn><isbn>9780780326859</isbn><abstract>A technique is proposed for synthesizing pole-placement controllers capable of assigning the closed-loop poles of an family of plants inside a specified design region. The design is applicable to plants characterized by uncertain parameters that are known to lie inside an ellipsoid. Ellipsoidal parametric uncertainty descriptions are particularly useful because they arise naturally in the context of parameter estimation, and hence have the advantage of being quantifiable using experimental input-output data. The control-design problem is posed as a minimax program that is shown to be convex, and that can be solved using numerical techniques with global convergence guarantees.</abstract><pub>IEEE Control Systems Society</pub><doi>10.1109/CDC.1995.478928</doi></addata></record> |
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| ispartof | Proceedings of 1995 34th IEEE Conference on Decision and Control, 1995, Vol.4, p.4360-4367 vol.4 |
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| recordid | cdi_ieee_primary_478928 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Control system synthesis Convergence of numerical methods Ellipsoids Minimax techniques Optimal control Parameter estimation Robust control Robustness Uncertain systems Uncertainty |
| title | Robust pole-placement for ellipsoidally uncertain systems |
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