PID design by convex-concave optimization
This paper describes how PID controllers can be designed by optimizing performance subject to robustness constraints. The optimization problem is solved using convex-concave programming. The method admits general process descriptions in terms of frequency response data and it can cope with many diff...
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creator | Hast, M. Astrom, K. J. Bernhardsson, B. Boyd, S. |
description | This paper describes how PID controllers can be designed by optimizing performance subject to robustness constraints. The optimization problem is solved using convex-concave programming. The method admits general process descriptions in terms of frequency response data and it can cope with many different constraints. Examples are presented and some pitfalls in optimization are discussed. |
doi_str_mv | 10.23919/ECC.2013.6669312 |
format | Conference Proceeding |
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J. ; Bernhardsson, B. ; Boyd, S.</creator><creatorcontrib>Hast, M. ; Astrom, K. J. ; Bernhardsson, B. ; Boyd, S.</creatorcontrib><description>This paper describes how PID controllers can be designed by optimizing performance subject to robustness constraints. The optimization problem is solved using convex-concave programming. The method admits general process descriptions in terms of frequency response data and it can cope with many different constraints. 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J.</creatorcontrib><creatorcontrib>Bernhardsson, B.</creatorcontrib><creatorcontrib>Boyd, S.</creatorcontrib><title>PID design by convex-concave optimization</title><title>2013 European Control Conference (ECC)</title><addtitle>ECC</addtitle><description>This paper describes how PID controllers can be designed by optimizing performance subject to robustness constraints. The optimization problem is solved using convex-concave programming. The method admits general process descriptions in terms of frequency response data and it can cope with many different constraints. Examples are presented and some pitfalls in optimization are discussed.</description><subject>Optimization</subject><subject>PD control</subject><subject>Process control</subject><subject>Robustness</subject><subject>Sensitivity</subject><subject>Transfer functions</subject><subject>Uncertainty</subject><isbn>9783033039629</isbn><isbn>3033039626</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj0FLw0AQRteDoNT8APGSq4fE2ZlkN3uUWG2hoIf2XGa3s7Jik9KEYv31Biw8eIcHH3xK3WsokZx2T_O2LRE0lcYYRxqvVOZsQ0ATzqC7UdkwfAGAtlabur5Vjx_Ll3wnQ_rscn_OQ9-d5KeYFPgkeX8Y0z798pj67k5dR_4eJLt4pjav83W7KFbvb8v2eVUERBoLTzXE0Eis2AdGsizC6BsTo0WstTVTjYTsRVccGgqwY7AkDFTVhmimHv53k4hsD8e05-N5ezlEfz5nQEQ</recordid><startdate>201307</startdate><enddate>201307</enddate><creator>Hast, M.</creator><creator>Astrom, K. 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J.</creatorcontrib><creatorcontrib>Bernhardsson, B.</creatorcontrib><creatorcontrib>Boyd, S.</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>Hast, M.</au><au>Astrom, K. J.</au><au>Bernhardsson, B.</au><au>Boyd, S.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>PID design by convex-concave optimization</atitle><btitle>2013 European Control Conference (ECC)</btitle><stitle>ECC</stitle><date>2013-07</date><risdate>2013</risdate><spage>4460</spage><epage>4465</epage><pages>4460-4465</pages><eisbn>9783033039629</eisbn><eisbn>3033039626</eisbn><abstract>This paper describes how PID controllers can be designed by optimizing performance subject to robustness constraints. The optimization problem is solved using convex-concave programming. The method admits general process descriptions in terms of frequency response data and it can cope with many different constraints. Examples are presented and some pitfalls in optimization are discussed.</abstract><pub>EUCA</pub><doi>10.23919/ECC.2013.6669312</doi><tpages>6</tpages></addata></record> |
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subjects | Optimization PD control Process control Robustness Sensitivity Transfer functions Uncertainty |
title | PID design by convex-concave optimization |
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