Loading…
A robust quadratic stabilization synthesis for uncertain systems based on T-S fuzzy model
The problem of quadratic stability for a class of uncertain nonlinear systems using Takagi-Sugeno fuzzy model is solved and certain relaxed conditions are derived. Firstly, a new robust quadratic stability condition via designing state feedback controller for T-S fuzzy system with uncertainties is d...
Saved in:
Main Authors: | , , , |
---|---|
Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | |
container_end_page | 302 |
container_issue | |
container_start_page | 297 |
container_title | |
container_volume | |
creator | Stankovski, M. Stojanovski, G. Nadzinski, G. Zhaona Chen |
description | The problem of quadratic stability for a class of uncertain nonlinear systems using Takagi-Sugeno fuzzy model is solved and certain relaxed conditions are derived. Firstly, a new robust quadratic stability condition via designing state feedback controller for T-S fuzzy system with uncertainties is derived. This condition is represented in the form of LMI and it is shown to be less conservative than similar known relaxed quadratic stabilization conditions in recent literature. Secondly, a dynamic output feedback control design for complex nonlinear systems represented by T-S fuzzy model is derived. These new techniques consider the interactions among all fuzzy subsystems. Finally, the applicability and validity of the proposed approach are demonstrated by means control design and simulation results for an illustrative example. |
doi_str_mv | 10.1109/IS.2012.6335233 |
format | conference_proceeding |
fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_6335233</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6335233</ieee_id><sourcerecordid>6335233</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-2f78ba116f9500a150c62e38d59c55e99ca66005668e09b924c4f9540625bfba3</originalsourceid><addsrcrecordid>eNo1kD1PwzAYhM2XRFs6M7D4DyS8tmM7HquKQqVKDM3CVNmJLYzyAbEzJL-eVJTpdPecbjiEHgmkhIB63h9TCoSmgjFOGbtCayVzkgnJKJWSX6MFURlJCFXZDVr-A5HfzoCfgZD0Hi1D-AKgDEi-QB8b3HdmCBH_DLrqdfQlDlEbX_tpNl2Lw9jGTxt8wK7r8dCWto_an_MQbROw0cFWeC4WyRG7YZpG3HSVrR_QndN1sOuLrlCxeym2b8nh_XW_3RwSryAm1MncaEKEUxxAEw6loJblFVcl51apUgsBwIXILSijaFZmczUDQblxRrMVevqb9dba03fvG92Pp8tD7BfVLlWl</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>A robust quadratic stabilization synthesis for uncertain systems based on T-S fuzzy model</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Stankovski, M. ; Stojanovski, G. ; Nadzinski, G. ; Zhaona Chen</creator><creatorcontrib>Stankovski, M. ; Stojanovski, G. ; Nadzinski, G. ; Zhaona Chen</creatorcontrib><description>The problem of quadratic stability for a class of uncertain nonlinear systems using Takagi-Sugeno fuzzy model is solved and certain relaxed conditions are derived. Firstly, a new robust quadratic stability condition via designing state feedback controller for T-S fuzzy system with uncertainties is derived. This condition is represented in the form of LMI and it is shown to be less conservative than similar known relaxed quadratic stabilization conditions in recent literature. Secondly, a dynamic output feedback control design for complex nonlinear systems represented by T-S fuzzy model is derived. These new techniques consider the interactions among all fuzzy subsystems. Finally, the applicability and validity of the proposed approach are demonstrated by means control design and simulation results for an illustrative example.</description><identifier>ISSN: 1541-1672</identifier><identifier>ISBN: 1467322768</identifier><identifier>ISBN: 9781467322768</identifier><identifier>EISSN: 1941-1294</identifier><identifier>EISBN: 9781467322775</identifier><identifier>EISBN: 9781467322782</identifier><identifier>EISBN: 1467322776</identifier><identifier>EISBN: 1467322784</identifier><identifier>DOI: 10.1109/IS.2012.6335233</identifier><language>eng</language><publisher>IEEE</publisher><subject>Fuzzy control ; Fuzzy system models ; nonlinear plants ; Nonlinear systems ; Output feedback ; quadratic stability ; Robustness ; Stability analysis ; uncertainties ; Uncertainty</subject><ispartof>2012 6th IEEE International Conference Intelligent Systems, 2012, p.297-302</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6335233$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54796,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6335233$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Stankovski, M.</creatorcontrib><creatorcontrib>Stojanovski, G.</creatorcontrib><creatorcontrib>Nadzinski, G.</creatorcontrib><creatorcontrib>Zhaona Chen</creatorcontrib><title>A robust quadratic stabilization synthesis for uncertain systems based on T-S fuzzy model</title><title>2012 6th IEEE International Conference Intelligent Systems</title><addtitle>IS</addtitle><description>The problem of quadratic stability for a class of uncertain nonlinear systems using Takagi-Sugeno fuzzy model is solved and certain relaxed conditions are derived. Firstly, a new robust quadratic stability condition via designing state feedback controller for T-S fuzzy system with uncertainties is derived. This condition is represented in the form of LMI and it is shown to be less conservative than similar known relaxed quadratic stabilization conditions in recent literature. Secondly, a dynamic output feedback control design for complex nonlinear systems represented by T-S fuzzy model is derived. These new techniques consider the interactions among all fuzzy subsystems. Finally, the applicability and validity of the proposed approach are demonstrated by means control design and simulation results for an illustrative example.</description><subject>Fuzzy control</subject><subject>Fuzzy system models</subject><subject>nonlinear plants</subject><subject>Nonlinear systems</subject><subject>Output feedback</subject><subject>quadratic stability</subject><subject>Robustness</subject><subject>Stability analysis</subject><subject>uncertainties</subject><subject>Uncertainty</subject><issn>1541-1672</issn><issn>1941-1294</issn><isbn>1467322768</isbn><isbn>9781467322768</isbn><isbn>9781467322775</isbn><isbn>9781467322782</isbn><isbn>1467322776</isbn><isbn>1467322784</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1kD1PwzAYhM2XRFs6M7D4DyS8tmM7HquKQqVKDM3CVNmJLYzyAbEzJL-eVJTpdPecbjiEHgmkhIB63h9TCoSmgjFOGbtCayVzkgnJKJWSX6MFURlJCFXZDVr-A5HfzoCfgZD0Hi1D-AKgDEi-QB8b3HdmCBH_DLrqdfQlDlEbX_tpNl2Lw9jGTxt8wK7r8dCWto_an_MQbROw0cFWeC4WyRG7YZpG3HSVrR_QndN1sOuLrlCxeym2b8nh_XW_3RwSryAm1MncaEKEUxxAEw6loJblFVcl51apUgsBwIXILSijaFZmczUDQblxRrMVevqb9dba03fvG92Pp8tD7BfVLlWl</recordid><startdate>201209</startdate><enddate>201209</enddate><creator>Stankovski, M.</creator><creator>Stojanovski, G.</creator><creator>Nadzinski, G.</creator><creator>Zhaona Chen</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201209</creationdate><title>A robust quadratic stabilization synthesis for uncertain systems based on T-S fuzzy model</title><author>Stankovski, M. ; Stojanovski, G. ; Nadzinski, G. ; Zhaona Chen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-2f78ba116f9500a150c62e38d59c55e99ca66005668e09b924c4f9540625bfba3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Fuzzy control</topic><topic>Fuzzy system models</topic><topic>nonlinear plants</topic><topic>Nonlinear systems</topic><topic>Output feedback</topic><topic>quadratic stability</topic><topic>Robustness</topic><topic>Stability analysis</topic><topic>uncertainties</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Stankovski, M.</creatorcontrib><creatorcontrib>Stojanovski, G.</creatorcontrib><creatorcontrib>Nadzinski, G.</creatorcontrib><creatorcontrib>Zhaona Chen</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/IET Electronic Library</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>Stankovski, M.</au><au>Stojanovski, G.</au><au>Nadzinski, G.</au><au>Zhaona Chen</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A robust quadratic stabilization synthesis for uncertain systems based on T-S fuzzy model</atitle><btitle>2012 6th IEEE International Conference Intelligent Systems</btitle><stitle>IS</stitle><date>2012-09</date><risdate>2012</risdate><spage>297</spage><epage>302</epage><pages>297-302</pages><issn>1541-1672</issn><eissn>1941-1294</eissn><isbn>1467322768</isbn><isbn>9781467322768</isbn><eisbn>9781467322775</eisbn><eisbn>9781467322782</eisbn><eisbn>1467322776</eisbn><eisbn>1467322784</eisbn><abstract>The problem of quadratic stability for a class of uncertain nonlinear systems using Takagi-Sugeno fuzzy model is solved and certain relaxed conditions are derived. Firstly, a new robust quadratic stability condition via designing state feedback controller for T-S fuzzy system with uncertainties is derived. This condition is represented in the form of LMI and it is shown to be less conservative than similar known relaxed quadratic stabilization conditions in recent literature. Secondly, a dynamic output feedback control design for complex nonlinear systems represented by T-S fuzzy model is derived. These new techniques consider the interactions among all fuzzy subsystems. Finally, the applicability and validity of the proposed approach are demonstrated by means control design and simulation results for an illustrative example.</abstract><pub>IEEE</pub><doi>10.1109/IS.2012.6335233</doi><tpages>6</tpages></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISSN: 1541-1672 |
ispartof | 2012 6th IEEE International Conference Intelligent Systems, 2012, p.297-302 |
issn | 1541-1672 1941-1294 |
language | eng |
recordid | cdi_ieee_primary_6335233 |
source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Fuzzy control Fuzzy system models nonlinear plants Nonlinear systems Output feedback quadratic stability Robustness Stability analysis uncertainties Uncertainty |
title | A robust quadratic stabilization synthesis for uncertain systems based on T-S fuzzy model |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T06%3A48%3A52IST&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=A%20robust%20quadratic%20stabilization%20synthesis%20for%20uncertain%20systems%20based%20on%20T-S%20fuzzy%20model&rft.btitle=2012%206th%20IEEE%20International%20Conference%20Intelligent%20Systems&rft.au=Stankovski,%20M.&rft.date=2012-09&rft.spage=297&rft.epage=302&rft.pages=297-302&rft.issn=1541-1672&rft.eissn=1941-1294&rft.isbn=1467322768&rft.isbn_list=9781467322768&rft_id=info:doi/10.1109/IS.2012.6335233&rft.eisbn=9781467322775&rft.eisbn_list=9781467322782&rft.eisbn_list=1467322776&rft.eisbn_list=1467322784&rft_dat=%3Cieee_6IE%3E6335233%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i90t-2f78ba116f9500a150c62e38d59c55e99ca66005668e09b924c4f9540625bfba3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6335233&rfr_iscdi=true |