Identification of uncertain nonlinear systems for robust fuzzy control

In this paper, we consider fuzzy identification of uncertain nonlinear systems in Takagi–Sugeno (T–S) form for the purpose of robust fuzzy control design. The uncertain nonlinear system is represented using a fuzzy function having constant matrices and time varying uncertain matrices that describe t...

Full description

Saved in:

Bibliographic Details
Published in:	ISA transactions Vol. 49; no. 1; pp. 27 - 38
Main Authors:	Senthilkumar, D., Mahanta, Chitralekha
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier Ltd 2010 Elsevier
Subjects:	Algorithms Applied sciences Artificial Intelligence Computer science; control theory; systems Control system analysis Control system synthesis Control theory. Systems Data Interpretation, Statistical Electronics Exact sciences and technology Fuzzy Logic Interval fuzzy model Linear programming Modelling and identification Nonlinear Dynamics Parametric uncertainties Takagi–Sugeno (T–S) fuzzy model Uncertainty Linear programming Takagi–Sugeno (T–S) fuzzy model Interval fuzzy model Parametric uncertainties Robust stability Non linear control Control synthesis Non linear system Modeling Robust control Fuzzy logic Fuzzy control Time varying system Uncertain system Robustness System identification Time constant Takagi-Sugeno (T-S) fuzzy model
ISSN:	0019-0578, 1879-2022, 1879-2022
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	In this paper, we consider fuzzy identification of uncertain nonlinear systems in Takagi–Sugeno (T–S) form for the purpose of robust fuzzy control design. The uncertain nonlinear system is represented using a fuzzy function having constant matrices and time varying uncertain matrices that describe the nominal model and the uncertainty in the nonlinear system respectively. The suggested method is based on linear programming approach and it comprises the identification of the nominal model and the bounds of the uncertain matrices and then expressing the uncertain matrices into uncertain norm bounded matrices accompanied by constant matrices. It has been observed that our method yields less conservative results than the other existing method proposed by S˘krjanc et al. (2005) [11,12]. With the obtained fuzzy model, we showed the robust stability condition which provides a basis for different robust fuzzy control design. Finally, different simulation examples are presented for identification and control of uncertain nonlinear systems to illustrate the utility of our proposed identification method for robust fuzzy control.
AbstractList	In this paper, we consider fuzzy identification of uncertain nonlinear systems in Takagi-Sugeno (T-S) form for the purpose of robust fuzzy control design. The uncertain nonlinear system is represented using a fuzzy function having constant matrices and time varying uncertain matrices that describe the nominal model and the uncertainty in the nonlinear system respectively. The suggested method is based on linear programming approach and it comprises the identification of the nominal model and the bounds of the uncertain matrices and then expressing the uncertain matrices into uncertain norm bounded matrices accompanied by constant matrices. It has been observed that our method yields less conservative results than the other existing method proposed by Skrjanc et al. (2005). With the obtained fuzzy model, we showed the robust stability condition which provides a basis for different robust fuzzy control design. Finally, different simulation examples are presented for identification and control of uncertain nonlinear systems to illustrate the utility of our proposed identification method for robust fuzzy control. In this paper, we consider fuzzy identification of uncertain nonlinear systems in Takagi-Sugeno (T-S) form for the purpose of robust fuzzy control design. The uncertain nonlinear system is represented using a fuzzy function having constant matrices and time varying uncertain matrices that describe the nominal model and the uncertainty in the nonlinear system respectively. The suggested method is based on linear programming approach and it comprises the identification of the nominal model and the bounds of the uncertain matrices and then expressing the uncertain matrices into uncertain norm bounded matrices accompanied by constant matrices. It has been observed that our method yields less conservative results than the other existing method proposed by Skrjanc et al. (2005). With the obtained fuzzy model, we showed the robust stability condition which provides a basis for different robust fuzzy control design. Finally, different simulation examples are presented for identification and control of uncertain nonlinear systems to illustrate the utility of our proposed identification method for robust fuzzy control.In this paper, we consider fuzzy identification of uncertain nonlinear systems in Takagi-Sugeno (T-S) form for the purpose of robust fuzzy control design. The uncertain nonlinear system is represented using a fuzzy function having constant matrices and time varying uncertain matrices that describe the nominal model and the uncertainty in the nonlinear system respectively. The suggested method is based on linear programming approach and it comprises the identification of the nominal model and the bounds of the uncertain matrices and then expressing the uncertain matrices into uncertain norm bounded matrices accompanied by constant matrices. It has been observed that our method yields less conservative results than the other existing method proposed by Skrjanc et al. (2005). With the obtained fuzzy model, we showed the robust stability condition which provides a basis for different robust fuzzy control design. Finally, different simulation examples are presented for identification and control of uncertain nonlinear systems to illustrate the utility of our proposed identification method for robust fuzzy control. In this paper, we consider fuzzy identification of uncertain nonlinear systems in Takagi–Sugeno (T–S) form for the purpose of robust fuzzy control design. The uncertain nonlinear system is represented using a fuzzy function having constant matrices and time varying uncertain matrices that describe the nominal model and the uncertainty in the nonlinear system respectively. The suggested method is based on linear programming approach and it comprises the identification of the nominal model and the bounds of the uncertain matrices and then expressing the uncertain matrices into uncertain norm bounded matrices accompanied by constant matrices. It has been observed that our method yields less conservative results than the other existing method proposed by S˘krjanc et al. (2005) [11,12]. With the obtained fuzzy model, we showed the robust stability condition which provides a basis for different robust fuzzy control design. Finally, different simulation examples are presented for identification and control of uncertain nonlinear systems to illustrate the utility of our proposed identification method for robust fuzzy control.
Author	Senthilkumar, D. Mahanta, Chitralekha
Author_xml	– sequence: 1 givenname: D. surname: Senthilkumar fullname: Senthilkumar, D. email: d.senthil@iitg.ernet.in, senthildsenthil@gmail.com – sequence: 2 givenname: Chitralekha surname: Mahanta fullname: Mahanta, Chitralekha email: chitra@iitg.ernet.in
BackLink	http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=22472780$$DView record in Pascal Francis https://www.ncbi.nlm.nih.gov/pubmed/19683234$$D View this record in MEDLINE/PubMed
BookMark	eNp9kcFq3DAQhkVISDZp36AUX0pPdkeSLVk9FEJo2kAgl_YsZHkEWrxSKsmFzdNX6W5z6CEnXb5_ZvR_l-Q0xICEvKPQUaDi07bz2ZRkOgagOpAdwHBCNnSUqmXA2CnZAFDVwiDHC3KZ8xYA2KDGc3JBlRg54_2G3N7NGIp33priY2iia9ZgMRXjQ1M3Lj6gSU3e54K73LiYmhSnNZfGrU9P-8bGUFJc3pAzZ5aMb4_vFfl5-_XHzff2_uHb3c31fWu5oqWlzlBp-CC5QADjUPWCMrCKT1IoNg1CQM-4o9PMJuQ4MjVJ1_dusqMYDONX5ONh7mOKv1bMRe98trgsJmBcs5acj4ILyiv5_kiu0w5n_Zj8zqS9_vf1Cnw4AiZbs7hkgvX5hWOsl0yOULnPB86mmHNCp60vf8uq5ftFU9DPPvRWH3zoZx8apK4-arj_L_xyx-uxL4cY1i5_e0w6W4_Vy-wT2qLn6F8f8AcIAaZC
CitedBy_id	crossref_primary_10_1016_j_knosys_2014_09_010 crossref_primary_10_1109_ACCESS_2021_3056003 crossref_primary_10_1088_1757_899X_138_1_012009 crossref_primary_10_1109_JSEN_2021_3067841 crossref_primary_10_1186_s40064_016_2632_4 crossref_primary_10_1016_j_amc_2017_10_053 crossref_primary_10_1016_j_isatra_2016_04_005 crossref_primary_10_1177_0954410017712329 crossref_primary_10_1016_j_isatra_2013_04_009 crossref_primary_10_1016_j_isatra_2015_08_012 crossref_primary_10_1016_j_isatra_2010_11_007 crossref_primary_10_3233_IFS_162191 crossref_primary_10_1109_TFUZZ_2018_2833822
Cites_doi	10.1016/S0377-0427(00)00342-3 10.1109/TSMCB.2002.1033180 10.1109/91.728456 10.1109/91.940966 10.1109/TSMCB.2005.850166 10.1016/j.fss.2004.04.013 10.1109/TSMCB.2003.818562 10.1007/BF02252616 10.1109/TFUZZ.2006.880006 10.1109/TFUZZ.2006.889931 10.1016/S0165-0114(03)00023-X 10.1109/91.618271 10.1016/j.automatica.2004.09.010 10.1007/BF02238641 10.1109/TFUZZ.2005.861602 10.1109/TFUZZ.2006.876725 10.1109/TFUZZ.2007.894983 10.1016/j.automatica.2005.11.005 10.1016/j.engappai.2007.02.011 10.1016/j.ins.2007.05.004 10.1080/10556789908805766 10.1016/S0888-613X(02)00061-0 10.1109/87.491203 10.1109/TSMCB.2005.862486 10.1109/TSMC.1985.6313399 10.1109/TFUZZ.2005.856567 10.1109/91.919253 10.1109/TSMCB.2004.842417 10.1109/TFUZZ.2002.806317 10.1109/TFUZZ.2006.876331 10.1016/j.fss.2006.09.010
ContentType	Journal Article
Copyright	2009 ISA 2015 INIST-CNRS 2009 ISA. Published by Elsevier Ltd. All rights reserved.
Copyright_xml	– notice: 2009 ISA – notice: 2015 INIST-CNRS – notice: 2009 ISA. Published by Elsevier Ltd. All rights reserved.
DBID	AAYXX CITATION IQODW CGR CUY CVF ECM EIF NPM 7X8
DOI	10.1016/j.isatra.2009.07.005
DatabaseName	CrossRef Pascal-Francis Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed MEDLINE - Academic
DatabaseTitle	CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) MEDLINE - Academic
DatabaseTitleList	MEDLINE MEDLINE - Academic
Database_xml	– sequence: 1 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering Sciences (General) Applied Sciences
EISSN	1879-2022
EndPage	38
ExternalDocumentID	19683234 22472780 10_1016_j_isatra_2009_07_005 S0019057809000561
Genre	Journal Article
GroupedDBID	--- --K --M -~X .DC .~1 0R~ 1B1 1~. 1~5 29J 4.4 457 4G. 53G 5GY 5VS 6P2 7-5 71M 8P~ 9JN AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AAXUO ABFNM ABFRF ABJNI ABMAC ABNEU ABTAH ABXDB ABYKQ ACDAQ ACFVG ACGFO ACNNM ACRLP ADBBV ADEZE ADMUD ADTZH AEBSH AECPX AEFWE AEKER AENEX AFDAS AFFNX AFKWA AFTJW AGHFR AGUBO AGYEJ AHHHB AHJVU AIEXJ AIKHN AITUG AIVDX AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ ASPBG AVWKF AXJTR AZFZN BJAXD BKOJK BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 GBLVA HVGLF HZ~ IHE J1W JJJVA KOM LY7 M41 MO0 N9A O-L O9- OAUVE OGIMB OZT P-8 P-9 P2P PC. Q38 R2- ROL RPZ SDF SDG SES SET SEW SPC SPCBC SPD SSQ SST SSZ T5K T9H TAE TN5 UHS UNMZH WUQ XPP ZMT ZY4 ~G- 9DU AATTM AAXKI AAYWO AAYXX ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD AFXIZ AGCQF AGRNS BNPGV IQODW SSH CGR CUY CVF ECM EIF NPM 7X8
ID	FETCH-LOGICAL-c391t-1fa17a35736e00afe946120c93b7692b5660423f1bd2be3e829b7f44fbc865a23
ISICitedReferencesCount	19
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000274738500004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0019-0578 1879-2022
IngestDate	Thu Oct 02 11:56:07 EDT 2025 Mon Jul 21 05:56:19 EDT 2025 Mon Jul 21 09:14:40 EDT 2025 Sat Nov 29 02:28:30 EST 2025 Tue Nov 18 22:19:51 EST 2025 Fri Feb 23 02:30:41 EST 2024
IsPeerReviewed	true
IsScholarly	true
Issue	1
Keywords	Linear programming Takagi–Sugeno (T–S) fuzzy model Interval fuzzy model Parametric uncertainties Robust stability Non linear control Control synthesis Non linear system Modeling Robust control Fuzzy logic Fuzzy control Time varying system Uncertain system Robustness System identification Time constant Takagi-Sugeno (T-S) fuzzy model
Language	English
License	https://www.elsevier.com/tdm/userlicense/1.0 CC BY 4.0 2009 ISA. Published by Elsevier Ltd. All rights reserved.
LinkModel	OpenURL
MergedId	FETCHMERGED-LOGICAL-c391t-1fa17a35736e00afe946120c93b7692b5660423f1bd2be3e829b7f44fbc865a23
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
PMID	19683234
PQID	733863613
PQPubID	23479
PageCount	12
ParticipantIDs	proquest_miscellaneous_733863613 pubmed_primary_19683234 pascalfrancis_primary_22472780 crossref_citationtrail_10_1016_j_isatra_2009_07_005 crossref_primary_10_1016_j_isatra_2009_07_005 elsevier_sciencedirect_doi_10_1016_j_isatra_2009_07_005
PublicationCentury	2000
PublicationDate	2010 2010-1-00 2010-Jan 20100101
PublicationDateYYYYMMDD	2010-01-01
PublicationDate_xml	– year: 2010 text: 2010
PublicationDecade	2010
PublicationPlace	Kidlington
PublicationPlace_xml	– name: Kidlington – name: United States
PublicationTitle	ISA transactions
PublicationTitleAlternate	ISA Trans
PublicationYear	2010
Publisher	Elsevier Ltd Elsevier
Publisher_xml	– name: Elsevier Ltd – name: Elsevier
References	Munack, Tubingen (b22) 1992; 48 Ichida, Fujii (b21) 1979; 23 Hansen, Walster (b24) 2004 Kau, Lee, Yang, Lee, Hong, Fang (b4) 2007; 158 Sun J, Grotstollen H. Averaged modelling of switching power converters: Reformulation and theoretical basis. In: Power electronics specialists conference, 1992. PESC ’92 Record., 23rd annual IEEE, vol. 2. 1992. p. 1165–72 Lam, Leung (b33) 2005; 35 Ariño, Sala (b32) 2007; 20 Lo, Lin (b6) 2007; 15 Alefeld, Mayer (b23) 2000; 121 Takagi, Sugeno (b16) 1985; 15 S˘krjanc, Blaz˘ic, Agamennoni (b13) 2005; 41 Sturm (b34) 1999; 11–12 Lian, Liou (b37) 2006; 14 Bupp RT, Bernstein DS, Coppola VT. A benchmark problem for nonlinear control design: Problem statement, experimental testbed and passive nonlinear compensation. In: Proc. 1995 American control conference. 1995. p. 4363–7 Cao, Lin (b2) 2003; 11 S˘krjanc, Blaz˘ic, Agamennoni (b12) 2005; 35 Tong, Wang, Li (b1) 2002; 30 Ying (b8) 1998; 6 Löfberg J. YALMIP: A toolbox for modeling and optimization in MATLAB. In: Proc. CACSD conf. 2004. URL Taniguchi, Tanaka, Ohtake, Wang (b9) 2001; 9 Kim, Park, Ji, Park (b17) 1997; 5 Su X, Zhang Q, Jin J. Stability analysis for interval descriptor systems: A matrix inequalities approach. In: Proc. 4th world congress on intelligent control and automation, vol. 2. 2002. p. 1007–11 Gavriliu M. Towards more efficient interval analysis: Corner forms and a remainder interval newton method. Ph.D. thesis. California Institute of Technology; 2005 Tanaka, Wang (b20) 2001 Hamzaoui, Essounbouli, Benmahammed, Zaytoon (b14) 2004; 34 Tsekouras, Sarimveis, Kavakli, Bafas (b19) 2005; 150 Nguang, Shi, Ding (b7) 2007; 15 Zhang, Zhou, Li (b28) 2007; 177 Ding, Sun, Yang (b31) 2006; 42 Wu, Cai (b3) 2006; 36 Tuan, Apkarian, Narikiyo, Yamamoto (b29) 2001; 9 S˘krjanc, Blaz˘ic, Agamennoni (b11) 2005; 13 Fantuzzi C, Rovatti R. On the approximation capabilities of the homogeneous Takagi–Sugeno model. In: Proc. FUZZ-IEEE’98, vol. 2. 1996. p. 1067–72 Lo, Lin (b27) 2006; 14 Fang, Liu, Kau, Hong, Lee (b30) 2006; 14 Abonyi, Babus˘ka, Szeifert (b18) 2002; 32 Jankovic, Fontaine, Kokotović (b39) 1996; 4 Ho, Niu (b5) 2007; 15 Lo, Lin (b10) 2004; 143 Abonyi (10.1016/j.isatra.2009.07.005_b18) 2002; 32 Ding (10.1016/j.isatra.2009.07.005_b31) 2006; 42 Ying (10.1016/j.isatra.2009.07.005_b8) 1998; 6 S˘krjanc (10.1016/j.isatra.2009.07.005_b13) 2005; 41 Fang (10.1016/j.isatra.2009.07.005_b30) 2006; 14 Ariño (10.1016/j.isatra.2009.07.005_b32) 2007; 20 Lian (10.1016/j.isatra.2009.07.005_b37) 2006; 14 Sturm (10.1016/j.isatra.2009.07.005_b34) 1999; 11–12 S˘krjanc (10.1016/j.isatra.2009.07.005_b12) 2005; 35 Lo (10.1016/j.isatra.2009.07.005_b6) 2007; 15 Hansen (10.1016/j.isatra.2009.07.005_b24) 2004 10.1016/j.isatra.2009.07.005_b38 10.1016/j.isatra.2009.07.005_b15 Tong (10.1016/j.isatra.2009.07.005_b1) 2002; 30 10.1016/j.isatra.2009.07.005_b36 Takagi (10.1016/j.isatra.2009.07.005_b16) 1985; 15 10.1016/j.isatra.2009.07.005_b35 Alefeld (10.1016/j.isatra.2009.07.005_b23) 2000; 121 Tsekouras (10.1016/j.isatra.2009.07.005_b19) 2005; 150 Wu (10.1016/j.isatra.2009.07.005_b3) 2006; 36 Taniguchi (10.1016/j.isatra.2009.07.005_b9) 2001; 9 Jankovic (10.1016/j.isatra.2009.07.005_b39) 1996; 4 Munack (10.1016/j.isatra.2009.07.005_b22) 1992; 48 S˘krjanc (10.1016/j.isatra.2009.07.005_b11) 2005; 13 Lo (10.1016/j.isatra.2009.07.005_b10) 2004; 143 Lo (10.1016/j.isatra.2009.07.005_b27) 2006; 14 Tuan (10.1016/j.isatra.2009.07.005_b29) 2001; 9 Kim (10.1016/j.isatra.2009.07.005_b17) 1997; 5 Tanaka (10.1016/j.isatra.2009.07.005_b20) 2001 Zhang (10.1016/j.isatra.2009.07.005_b28) 2007; 177 Lam (10.1016/j.isatra.2009.07.005_b33) 2005; 35 10.1016/j.isatra.2009.07.005_b26 10.1016/j.isatra.2009.07.005_b25 Ho (10.1016/j.isatra.2009.07.005_b5) 2007; 15 Kau (10.1016/j.isatra.2009.07.005_b4) 2007; 158 Cao (10.1016/j.isatra.2009.07.005_b2) 2003; 11 Ichida (10.1016/j.isatra.2009.07.005_b21) 1979; 23 Nguang (10.1016/j.isatra.2009.07.005_b7) 2007; 15 Hamzaoui (10.1016/j.isatra.2009.07.005_b14) 2004; 34
References_xml	– volume: 32 start-page: 612 year: 2002 end-page: 621 ident: b18 article-title: Modified Gath-Geva fuzzy clustering for identification of Takagi–Sugeno fuzzy models publication-title: IEEE Trans Syst Man Cybern B – volume: 9 start-page: 525 year: 2001 end-page: 538 ident: b9 article-title: Model construction, rule reduction, and robust compensation for generalized form of Takagi–Sugeno fuzzy systems publication-title: IEEE Trans Fuzzy Syst – volume: 14 start-page: 386 year: 2006 end-page: 397 ident: b30 article-title: A new LMI-based approach to relaxed quadratic stabilization of T–S fuzzy control systems publication-title: IEEE Trans Fuzzy Syst – volume: 6 start-page: 582 year: 1998 end-page: 587 ident: b8 article-title: General SISO Takagi–Sugeno fuzzy systems with linear rule consequent are universal approximators publication-title: IEEE Trans Fuzzy Syst – volume: 9 start-page: 324 year: 2001 end-page: 332 ident: b29 article-title: Parameterized linear matrix inequality techniques in fuzzy control system design publication-title: IEEE Trans Fuzzy Syst – volume: 42 start-page: 503 year: 2006 end-page: 508 ident: b31 article-title: Further studies on LMI-based relaxed stabilization conditions for nonlinear systems in Takagi–Sugenos form publication-title: Automatica – reference: Sun J, Grotstollen H. Averaged modelling of switching power converters: Reformulation and theoretical basis. In: Power electronics specialists conference, 1992. PESC ’92 Record., 23rd annual IEEE, vol. 2. 1992. p. 1165–72 – volume: 15 start-page: 840 year: 2007 end-page: 851 ident: b6 article-title: Existence of similarity transformation converting BMIs to LMIs publication-title: IEEE Trans Fuzzy Syst – reference: Löfberg J. YALMIP: A toolbox for modeling and optimization in MATLAB. In: Proc. CACSD conf. 2004. URL: – reference: Su X, Zhang Q, Jin J. Stability analysis for interval descriptor systems: A matrix inequalities approach. In: Proc. 4th world congress on intelligent control and automation, vol. 2. 2002. p. 1007–11 – volume: 15 start-page: 1251 year: 2007 end-page: 1262 ident: b7 article-title: Fault detection for uncertain fuzzy systems: An LMI approach publication-title: IEEE Trans Fuzzy Syst – volume: 121 start-page: 421 year: 2000 end-page: 464 ident: b23 article-title: Interval analysis: Theory and applications publication-title: J Comput Appl Math – volume: 15 start-page: 116 year: 1985 end-page: 132 ident: b16 article-title: Fuzzy identification of systems and its applications to modeling and control publication-title: IEEE Trans Syst Man Cybern – volume: 35 start-page: 1092 year: 2005 end-page: 1095 ident: b12 article-title: Interval fuzzy modeling applied to wiener models with uncertainties publication-title: IEEE Trans Syst Man Cybern B – volume: 150 start-page: 245 year: 2005 end-page: 266 ident: b19 article-title: A hierarchical fuzzy-clustering approach to fuzzy modeling publication-title: Fuzzy Sets and Systems – volume: 4 start-page: 292 year: 1996 end-page: 297 ident: b39 article-title: TORA example: Cascade- and passivity-based control designs publication-title: IEEE Trans Control Syst Technol – volume: 48 start-page: 319 year: 1992 end-page: 336 ident: b22 article-title: On global optimization using interval arithmetic publication-title: Computing – volume: 5 start-page: 328 year: 1997 end-page: 337 ident: b17 article-title: A new approach to fuzzy modeling publication-title: IEEE Trans Fuzzy Syst – volume: 11 start-page: 57 year: 2003 end-page: 67 ident: b2 article-title: Robust stability analysis and fuzzy-scheduling control for nonlinear systems subject to actuator saturation publication-title: IEEE Trans Fuzzy Syst – volume: 36 start-page: 509 year: 2006 end-page: 519 ident: b3 article-title: Mode-independent robust stabilization for uncertain markovian jump nonlinear systems via fuzzy control publication-title: IEEE Trans Syst Man Cybern B – year: 2004 ident: b24 article-title: Global optimization using interval analysis – volume: 158 start-page: 135 year: 2007 end-page: 146 ident: b4 article-title: Robust publication-title: Fuzzy Sets Syst – volume: 177 start-page: 5118 year: 2007 end-page: 5133 ident: b28 article-title: A new approach to robust and non-fragile publication-title: Information Sciences – volume: 11–12 start-page: 625 year: 1999 end-page: 653 ident: b34 article-title: Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones publication-title: Optim Methods Softw – volume: 30 start-page: 73 year: 2002 end-page: 90 ident: b1 article-title: Fuzzy robust tracking control for uncertain nonlinear systems publication-title: Int J Approx Reason – volume: 34 start-page: 942 year: 2004 end-page: 950 ident: b14 article-title: State observer based robust adaptive fuzzy controller for nonlinear uncertain and perturbed systems publication-title: IEEE Trans Syst Man Cybern B – reference: Gavriliu M. Towards more efficient interval analysis: Corner forms and a remainder interval newton method. Ph.D. thesis. California Institute of Technology; 2005 – volume: 20 start-page: 1036 year: 2007 end-page: 1046 ident: b32 article-title: Relaxed LMI conditions for closed-loop fuzzy systems with tensor-product structure publication-title: Eng Appl Artif Intell – volume: 14 start-page: 1 year: 2006 end-page: 15 ident: b27 article-title: Robust publication-title: IEEE Trans Fuzzy Syst – reference: Bupp RT, Bernstein DS, Coppola VT. A benchmark problem for nonlinear control design: Problem statement, experimental testbed and passive nonlinear compensation. In: Proc. 1995 American control conference. 1995. p. 4363–7 – reference: Fantuzzi C, Rovatti R. On the approximation capabilities of the homogeneous Takagi–Sugeno model. In: Proc. FUZZ-IEEE’98, vol. 2. 1996. p. 1067–72 – volume: 15 start-page: 350 year: 2007 end-page: 358 ident: b5 article-title: Robust fuzzy design for nonlinear uncertain stochastic systems via sliding-mode control publication-title: IEEE Trans Fuzzy Syst – year: 2001 ident: b20 article-title: Fuzzy control systems design and analysis – volume: 41 start-page: 327 year: 2005 end-page: 332 ident: b13 article-title: Identification of dynamical systems with a robust interval fuzzy model publication-title: Automatica – volume: 35 start-page: 269 year: 2005 end-page: 281 ident: b33 article-title: Fuzzy combination of fuzzy and switching state-feedback controllers for nonlinear systems subject to parameter uncertainties publication-title: IEEE Trans Syst Man Cybern B – volume: 14 start-page: 628 year: 2006 end-page: 639 ident: b37 article-title: Output tracking control for fuzzy systems via output feedback design publication-title: IEEE Trans Fuzzy Syst – volume: 13 start-page: 561 year: 2005 end-page: 568 ident: b11 article-title: Interval fuzzy model identification using publication-title: IEEE Trans Fuzzy Syst – volume: 143 start-page: 189 year: 2004 end-page: 209 ident: b10 article-title: Robust publication-title: Fuzzy Sets Syst – volume: 23 start-page: 85 year: 1979 end-page: 97 ident: b21 article-title: An interval arithmetic method for global optimization publication-title: Computing – volume: 121 start-page: 421 issue: 1-2 year: 2000 ident: 10.1016/j.isatra.2009.07.005_b23 article-title: Interval analysis: Theory and applications publication-title: J Comput Appl Math doi: 10.1016/S0377-0427(00)00342-3 – volume: 32 start-page: 612 issue: 5 year: 2002 ident: 10.1016/j.isatra.2009.07.005_b18 article-title: Modified Gath-Geva fuzzy clustering for identification of Takagi–Sugeno fuzzy models publication-title: IEEE Trans Syst Man Cybern B doi: 10.1109/TSMCB.2002.1033180 – ident: 10.1016/j.isatra.2009.07.005_b38 – volume: 6 start-page: 582 issue: 4 year: 1998 ident: 10.1016/j.isatra.2009.07.005_b8 article-title: General SISO Takagi–Sugeno fuzzy systems with linear rule consequent are universal approximators publication-title: IEEE Trans Fuzzy Syst doi: 10.1109/91.728456 – volume: 9 start-page: 525 issue: 4 year: 2001 ident: 10.1016/j.isatra.2009.07.005_b9 article-title: Model construction, rule reduction, and robust compensation for generalized form of Takagi–Sugeno fuzzy systems publication-title: IEEE Trans Fuzzy Syst doi: 10.1109/91.940966 – volume: 35 start-page: 1092 issue: 5 year: 2005 ident: 10.1016/j.isatra.2009.07.005_b12 article-title: Interval fuzzy modeling applied to wiener models with uncertainties publication-title: IEEE Trans Syst Man Cybern B doi: 10.1109/TSMCB.2005.850166 – ident: 10.1016/j.isatra.2009.07.005_b15 – year: 2001 ident: 10.1016/j.isatra.2009.07.005_b20 – ident: 10.1016/j.isatra.2009.07.005_b36 – volume: 150 start-page: 245 year: 2005 ident: 10.1016/j.isatra.2009.07.005_b19 article-title: A hierarchical fuzzy-clustering approach to fuzzy modeling publication-title: Fuzzy Sets and Systems doi: 10.1016/j.fss.2004.04.013 – volume: 34 start-page: 942 issue: 2 year: 2004 ident: 10.1016/j.isatra.2009.07.005_b14 article-title: State observer based robust adaptive fuzzy controller for nonlinear uncertain and perturbed systems publication-title: IEEE Trans Syst Man Cybern B doi: 10.1109/TSMCB.2003.818562 – volume: 23 start-page: 85 issue: 1 year: 1979 ident: 10.1016/j.isatra.2009.07.005_b21 article-title: An interval arithmetic method for global optimization publication-title: Computing doi: 10.1007/BF02252616 – volume: 15 start-page: 350 issue: 3 year: 2007 ident: 10.1016/j.isatra.2009.07.005_b5 article-title: Robust fuzzy design for nonlinear uncertain stochastic systems via sliding-mode control publication-title: IEEE Trans Fuzzy Syst doi: 10.1109/TFUZZ.2006.880006 – volume: 15 start-page: 840 issue: 5 year: 2007 ident: 10.1016/j.isatra.2009.07.005_b6 article-title: Existence of similarity transformation converting BMIs to LMIs publication-title: IEEE Trans Fuzzy Syst doi: 10.1109/TFUZZ.2006.889931 – volume: 143 start-page: 189 issue: 2 year: 2004 ident: 10.1016/j.isatra.2009.07.005_b10 article-title: Robust H∞ nonlinear modeling and control via uncertain fuzzy systems publication-title: Fuzzy Sets Syst doi: 10.1016/S0165-0114(03)00023-X – volume: 5 start-page: 328 issue: 3 year: 1997 ident: 10.1016/j.isatra.2009.07.005_b17 article-title: A new approach to fuzzy modeling publication-title: IEEE Trans Fuzzy Syst doi: 10.1109/91.618271 – volume: 41 start-page: 327 issue: 2 year: 2005 ident: 10.1016/j.isatra.2009.07.005_b13 article-title: Identification of dynamical systems with a robust interval fuzzy model publication-title: Automatica doi: 10.1016/j.automatica.2004.09.010 – volume: 48 start-page: 319 year: 1992 ident: 10.1016/j.isatra.2009.07.005_b22 article-title: On global optimization using interval arithmetic publication-title: Computing doi: 10.1007/BF02238641 – ident: 10.1016/j.isatra.2009.07.005_b26 – volume: 14 start-page: 1 issue: 1 year: 2006 ident: 10.1016/j.isatra.2009.07.005_b27 article-title: Robust H∞ control for fuzzy systems with frobenius norm-bounded uncertainties publication-title: IEEE Trans Fuzzy Syst doi: 10.1109/TFUZZ.2005.861602 – volume: 14 start-page: 628 issue: 5 year: 2006 ident: 10.1016/j.isatra.2009.07.005_b37 article-title: Output tracking control for fuzzy systems via output feedback design publication-title: IEEE Trans Fuzzy Syst doi: 10.1109/TFUZZ.2006.876725 – volume: 15 start-page: 1251 issue: 6 year: 2007 ident: 10.1016/j.isatra.2009.07.005_b7 article-title: Fault detection for uncertain fuzzy systems: An LMI approach publication-title: IEEE Trans Fuzzy Syst doi: 10.1109/TFUZZ.2007.894983 – volume: 42 start-page: 503 year: 2006 ident: 10.1016/j.isatra.2009.07.005_b31 article-title: Further studies on LMI-based relaxed stabilization conditions for nonlinear systems in Takagi–Sugenos form publication-title: Automatica doi: 10.1016/j.automatica.2005.11.005 – volume: 20 start-page: 1036 year: 2007 ident: 10.1016/j.isatra.2009.07.005_b32 article-title: Relaxed LMI conditions for closed-loop fuzzy systems with tensor-product structure publication-title: Eng Appl Artif Intell doi: 10.1016/j.engappai.2007.02.011 – volume: 177 start-page: 5118 issue: 15 year: 2007 ident: 10.1016/j.isatra.2009.07.005_b28 article-title: A new approach to robust and non-fragile H∞ control for uncertain fuzzy systems publication-title: Information Sciences doi: 10.1016/j.ins.2007.05.004 – volume: 11–12 start-page: 625 year: 1999 ident: 10.1016/j.isatra.2009.07.005_b34 article-title: Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones publication-title: Optim Methods Softw doi: 10.1080/10556789908805766 – volume: 30 start-page: 73 issue: 2 year: 2002 ident: 10.1016/j.isatra.2009.07.005_b1 article-title: Fuzzy robust tracking control for uncertain nonlinear systems publication-title: Int J Approx Reason doi: 10.1016/S0888-613X(02)00061-0 – volume: 4 start-page: 292 issue: 3 year: 1996 ident: 10.1016/j.isatra.2009.07.005_b39 article-title: TORA example: Cascade- and passivity-based control designs publication-title: IEEE Trans Control Syst Technol doi: 10.1109/87.491203 – ident: 10.1016/j.isatra.2009.07.005_b35 – year: 2004 ident: 10.1016/j.isatra.2009.07.005_b24 – volume: 36 start-page: 509 issue: 3 year: 2006 ident: 10.1016/j.isatra.2009.07.005_b3 article-title: Mode-independent robust stabilization for uncertain markovian jump nonlinear systems via fuzzy control publication-title: IEEE Trans Syst Man Cybern B doi: 10.1109/TSMCB.2005.862486 – volume: 15 start-page: 116 issue: 1 year: 1985 ident: 10.1016/j.isatra.2009.07.005_b16 article-title: Fuzzy identification of systems and its applications to modeling and control publication-title: IEEE Trans Syst Man Cybern doi: 10.1109/TSMC.1985.6313399 – volume: 13 start-page: 561 issue: 5 year: 2005 ident: 10.1016/j.isatra.2009.07.005_b11 article-title: Interval fuzzy model identification using l∞-norm publication-title: IEEE Trans Fuzzy Syst doi: 10.1109/TFUZZ.2005.856567 – volume: 9 start-page: 324 issue: 2 year: 2001 ident: 10.1016/j.isatra.2009.07.005_b29 article-title: Parameterized linear matrix inequality techniques in fuzzy control system design publication-title: IEEE Trans Fuzzy Syst doi: 10.1109/91.919253 – volume: 35 start-page: 269 issue: 2 year: 2005 ident: 10.1016/j.isatra.2009.07.005_b33 article-title: Fuzzy combination of fuzzy and switching state-feedback controllers for nonlinear systems subject to parameter uncertainties publication-title: IEEE Trans Syst Man Cybern B doi: 10.1109/TSMCB.2004.842417 – volume: 11 start-page: 57 issue: 1 year: 2003 ident: 10.1016/j.isatra.2009.07.005_b2 article-title: Robust stability analysis and fuzzy-scheduling control for nonlinear systems subject to actuator saturation publication-title: IEEE Trans Fuzzy Syst doi: 10.1109/TFUZZ.2002.806317 – volume: 14 start-page: 386 issue: 3 year: 2006 ident: 10.1016/j.isatra.2009.07.005_b30 article-title: A new LMI-based approach to relaxed quadratic stabilization of T–S fuzzy control systems publication-title: IEEE Trans Fuzzy Syst doi: 10.1109/TFUZZ.2006.876331 – volume: 158 start-page: 135 issue: 2 year: 2007 ident: 10.1016/j.isatra.2009.07.005_b4 article-title: Robust H∞ fuzzy static output feedback control of T–S fuzzy systems with parametric uncertainties publication-title: Fuzzy Sets Syst doi: 10.1016/j.fss.2006.09.010 – ident: 10.1016/j.isatra.2009.07.005_b25
SSID	ssj0002598
Score	1.9462229
Snippet	In this paper, we consider fuzzy identification of uncertain nonlinear systems in Takagi–Sugeno (T–S) form for the purpose of robust fuzzy control design. The... In this paper, we consider fuzzy identification of uncertain nonlinear systems in Takagi-Sugeno (T-S) form for the purpose of robust fuzzy control design. The...
SourceID	proquest pubmed pascalfrancis crossref elsevier
SourceType	Aggregation Database Index Database Enrichment Source Publisher
StartPage	27
SubjectTerms	Algorithms Applied sciences Artificial Intelligence Computer science; control theory; systems Control system analysis Control system synthesis Control theory. Systems Data Interpretation, Statistical Electronics Exact sciences and technology Fuzzy Logic Interval fuzzy model Linear programming Modelling and identification Nonlinear Dynamics Parametric uncertainties Takagi–Sugeno (T–S) fuzzy model Uncertainty
Title	Identification of uncertain nonlinear systems for robust fuzzy control
URI	https://dx.doi.org/10.1016/j.isatra.2009.07.005 https://www.ncbi.nlm.nih.gov/pubmed/19683234 https://www.proquest.com/docview/733863613
Volume	49
WOSCitedRecordID	wos000274738500004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1879-2022 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0002598 issn: 0019-0578 databaseCode: AIEXJ dateStart: 19950301 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3fb9MwED6xjgcQAlZ-lR-VH3gAVZGSOImTxwh1aoFViHVS3yI7scUGaqumRWN_PefYzlqmqfDAS1QlTWL1vt59Pp-_A3ibJorKRJaeiAT3Iqp8D8Nw6XGaVIpWSSwpb5pNsMkknc2yL7bbZt20E2DzeXp5mS3_q6nxHBpbb539B3O3D8UT-BmNjkc0Ox7_yvBm662yuThNBjF0mYX_wdwIY3Cn4NyIMQxWC7Gp1wO1ubr65WrXt0nr-DTXrSRcX_GWhZ8OJ9PR-POns5P8607x8Ek-yifT3Cznn-tcivz-jW8nGGyRaZPvssF523_qLU-xabrj_KeRHN3BiXWGbCusGg2XGw7b5A4umtqlFbf6oVpVMr4OUG5R_o-41VYTIgtBFpb6B3AYsjhLO3CYj4ezj21Eximejchm9G4LZVPnd_PNt1GUB0te4x9HmY4nt09JGmoyfQwP7ZyC5AYLR3BHzrvwyM4viPXedRfub4lPduHIXSDvrPb4-ydwvIseslCkRQ9p0UMsegiihxj0kAY9xKLnKZwdD6cfRp5tteGVNAvWXqB4wDiNGU2k73Mlswipr19mVLAkCwWSfl1ApQJRhUJSmYaZYCqKlCjTJOYhfQYdHIR8ASQMJfp16bNEVlElBQ8UklLBeVhFQVDJHlD36xal1aHX7VB-FK7g8KIwNtEtUrPC1wUScQ-89q6l0WHZ833mDFdYLmk4YoHI23Nnf8fO7esczHpAnOEL9MV6gY3P5WJTF4zSNKFIkHvw3ADieqxZgrGTRi_3Pf0V3DMFKjrL9xo669VGvoG75c_1eb3qwwGbpX2L79-9AbUF
linkProvider	Elsevier
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Identification+of+uncertain+nonlinear+systems+for+robust+fuzzy+control&rft.jtitle=ISA+transactions&rft.au=SENTHILKUMAR%2C+D&rft.au=MAHANTA%2C+Chitralekha&rft.date=2010&rft.pub=Elsevier&rft.issn=0019-0578&rft.volume=49&rft.issue=1&rft.spage=27&rft.epage=38&rft_id=info:doi/10.1016%2Fj.isatra.2009.07.005&rft.externalDBID=n%2Fa&rft.externalDocID=22472780
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0019-0578&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0019-0578&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0019-0578&client=summon