Adaptive Control for Systems With Time-Varying Parameters
This article investigates the adaptive control problem for systems with time-varying parameters using the so-called congelation of variables method. First, two scalar examples to illustrate how to deal with time-varying parameters in the feedback path and in the input path, respectively, are discuss...
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Veröffentlicht in: | IEEE transactions on automatic control 2021-05, Vol.66 (5), p.1986-2001 |
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container_end_page | 2001 |
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container_issue | 5 |
container_start_page | 1986 |
container_title | IEEE transactions on automatic control |
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creator | Chen, Kaiwen Astolfi, Alessandro |
description | This article investigates the adaptive control problem for systems with time-varying parameters using the so-called congelation of variables method. First, two scalar examples to illustrate how to deal with time-varying parameters in the feedback path and in the input path, respectively, are discussed. The control problem for an n-dimensional lower triangular system via state feedback is then discussed to show how to combine the congelation of variables method with adaptive backstepping techniques. To achieve output regulation problem via output feedback, problem which cannot be solved directly due to the coupling between the input and the time-varying perturbation, the ISS of the inverse dynamics, referred to as strong minimum-phaseness, is exploited. This allows converting such coupling into the coupling between the output and the time-varying perturbation. A set of filters, resulting in ISS state estimation error dynamics, are designed to cope with the unmeasured state variables. Finally, a controller is designed based on a small-gain-like analysis that takes all subsystems into account. Simulation results show that the proposed controller achieves asymptotic output regulation and outperforms the classical adaptive controller, in the presence of time-varying parameters that are neither known nor asymptotically constant. |
doi_str_mv | 10.1109/TAC.2020.3046141 |
format | Article |
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First, two scalar examples to illustrate how to deal with time-varying parameters in the feedback path and in the input path, respectively, are discussed. The control problem for an <inline-formula><tex-math notation="LaTeX">n</tex-math></inline-formula>-dimensional lower triangular system via state feedback is then discussed to show how to combine the congelation of variables method with adaptive backstepping techniques. To achieve output regulation problem via output feedback, problem which cannot be solved directly due to the coupling between the input and the time-varying perturbation, the ISS of the inverse dynamics, referred to as strong minimum-phaseness, is exploited. This allows converting such coupling into the coupling between the output and the time-varying perturbation. A set of filters, resulting in ISS state estimation error dynamics, are designed to cope with the unmeasured state variables. Finally, a controller is designed based on a small-gain-like analysis that takes all subsystems into account. Simulation results show that the proposed controller achieves asymptotic output regulation and outperforms the classical adaptive controller, in the presence of time-varying parameters that are neither known nor asymptotically constant.</description><identifier>ISSN: 0018-9286</identifier><identifier>EISSN: 1558-2523</identifier><identifier>DOI: 10.1109/TAC.2020.3046141</identifier><identifier>CODEN: IETAA9</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Adaptive control ; Asymptotic properties ; Backstepping ; Control systems design ; Controllers ; Convergence ; Coupling ; Couplings ; Inverse dynamics ; nonlinear systems ; Output feedback ; Parameters ; Perturbation ; Perturbation methods ; Regulation ; State estimation ; State feedback ; Subsystems ; Time-varying systems</subject><ispartof>IEEE transactions on automatic control, 2021-05, Vol.66 (5), p.1986-2001</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c333t-4f0fe66568bf92ed3b70265f0e4a1be4105aa1b1d84e9d250bf13f7e0bfc70223</citedby><cites>FETCH-LOGICAL-c333t-4f0fe66568bf92ed3b70265f0e4a1be4105aa1b1d84e9d250bf13f7e0bfc70223</cites><orcidid>0000-0001-6816-6910 ; 0000-0002-4331-454X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9300227$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27922,27923,54756</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9300227$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Chen, Kaiwen</creatorcontrib><creatorcontrib>Astolfi, Alessandro</creatorcontrib><title>Adaptive Control for Systems With Time-Varying Parameters</title><title>IEEE transactions on automatic control</title><addtitle>TAC</addtitle><description>This article investigates the adaptive control problem for systems with time-varying parameters using the so-called congelation of variables method. First, two scalar examples to illustrate how to deal with time-varying parameters in the feedback path and in the input path, respectively, are discussed. The control problem for an <inline-formula><tex-math notation="LaTeX">n</tex-math></inline-formula>-dimensional lower triangular system via state feedback is then discussed to show how to combine the congelation of variables method with adaptive backstepping techniques. To achieve output regulation problem via output feedback, problem which cannot be solved directly due to the coupling between the input and the time-varying perturbation, the ISS of the inverse dynamics, referred to as strong minimum-phaseness, is exploited. This allows converting such coupling into the coupling between the output and the time-varying perturbation. A set of filters, resulting in ISS state estimation error dynamics, are designed to cope with the unmeasured state variables. Finally, a controller is designed based on a small-gain-like analysis that takes all subsystems into account. Simulation results show that the proposed controller achieves asymptotic output regulation and outperforms the classical adaptive controller, in the presence of time-varying parameters that are neither known nor asymptotically constant.</description><subject>Adaptive control</subject><subject>Asymptotic properties</subject><subject>Backstepping</subject><subject>Control systems design</subject><subject>Controllers</subject><subject>Convergence</subject><subject>Coupling</subject><subject>Couplings</subject><subject>Inverse dynamics</subject><subject>nonlinear systems</subject><subject>Output feedback</subject><subject>Parameters</subject><subject>Perturbation</subject><subject>Perturbation methods</subject><subject>Regulation</subject><subject>State estimation</subject><subject>State feedback</subject><subject>Subsystems</subject><subject>Time-varying systems</subject><issn>0018-9286</issn><issn>1558-2523</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kM1Lw0AQxRdRsFbvgpeA59SZ_UpyLMEvKChY9bhsmllNaZq6uxX637ulxdObgd-bNzzGrhEmiFDdzaf1hAOHiQCpUeIJG6FSZc4VF6dsBIBlXvFSn7OLEJZp1VLiiFXT1m5i90tZPayjH1aZG3z2tguR-pB9dvE7m3c95R_W77r1V_Zqve0pkg-X7MzZVaCro47Z-8P9vH7KZy-Pz_V0li-EEDGXDhxprXTZuIpTK5oCuFYOSFpsSCIomwZsS0lVyxU0DoUrKOkikVyM2e3h7sYPP1sK0SyHrV-nSMMVFiCk5pgoOFALP4TgyZmN7_r0tEEw-4JMKsjsCzLHgpLl5mDpiOgfrwSk1EL8AV1nYDA</recordid><startdate>20210501</startdate><enddate>20210501</enddate><creator>Chen, Kaiwen</creator><creator>Astolfi, Alessandro</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-6816-6910</orcidid><orcidid>https://orcid.org/0000-0002-4331-454X</orcidid></search><sort><creationdate>20210501</creationdate><title>Adaptive Control for Systems With Time-Varying Parameters</title><author>Chen, Kaiwen ; Astolfi, Alessandro</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c333t-4f0fe66568bf92ed3b70265f0e4a1be4105aa1b1d84e9d250bf13f7e0bfc70223</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adaptive control</topic><topic>Asymptotic properties</topic><topic>Backstepping</topic><topic>Control systems design</topic><topic>Controllers</topic><topic>Convergence</topic><topic>Coupling</topic><topic>Couplings</topic><topic>Inverse dynamics</topic><topic>nonlinear systems</topic><topic>Output feedback</topic><topic>Parameters</topic><topic>Perturbation</topic><topic>Perturbation methods</topic><topic>Regulation</topic><topic>State estimation</topic><topic>State feedback</topic><topic>Subsystems</topic><topic>Time-varying systems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Kaiwen</creatorcontrib><creatorcontrib>Astolfi, Alessandro</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering 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><jtitle>IEEE transactions on automatic control</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Chen, Kaiwen</au><au>Astolfi, Alessandro</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Adaptive Control for Systems With Time-Varying Parameters</atitle><jtitle>IEEE transactions on automatic control</jtitle><stitle>TAC</stitle><date>2021-05-01</date><risdate>2021</risdate><volume>66</volume><issue>5</issue><spage>1986</spage><epage>2001</epage><pages>1986-2001</pages><issn>0018-9286</issn><eissn>1558-2523</eissn><coden>IETAA9</coden><abstract>This article investigates the adaptive control problem for systems with time-varying parameters using the so-called congelation of variables method. First, two scalar examples to illustrate how to deal with time-varying parameters in the feedback path and in the input path, respectively, are discussed. The control problem for an <inline-formula><tex-math notation="LaTeX">n</tex-math></inline-formula>-dimensional lower triangular system via state feedback is then discussed to show how to combine the congelation of variables method with adaptive backstepping techniques. To achieve output regulation problem via output feedback, problem which cannot be solved directly due to the coupling between the input and the time-varying perturbation, the ISS of the inverse dynamics, referred to as strong minimum-phaseness, is exploited. This allows converting such coupling into the coupling between the output and the time-varying perturbation. A set of filters, resulting in ISS state estimation error dynamics, are designed to cope with the unmeasured state variables. Finally, a controller is designed based on a small-gain-like analysis that takes all subsystems into account. Simulation results show that the proposed controller achieves asymptotic output regulation and outperforms the classical adaptive controller, in the presence of time-varying parameters that are neither known nor asymptotically constant.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TAC.2020.3046141</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0001-6816-6910</orcidid><orcidid>https://orcid.org/0000-0002-4331-454X</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adaptive control Asymptotic properties Backstepping Control systems design Controllers Convergence Coupling Couplings Inverse dynamics nonlinear systems Output feedback Parameters Perturbation Perturbation methods Regulation State estimation State feedback Subsystems Time-varying systems |
title | Adaptive Control for Systems With Time-Varying Parameters |
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