Leader-following consensus problem of heterogeneous multi-agent systems with nonlinear dynamics using fuzzy disturbance observer
This article considers the leader‐following consensus problem of heterogeneous multi‐agent systems. The proposed multi‐agent system is consisted of heterogeneous agents where each agents have their own nonlinear dynamic behavior. To overcome difficulty from heterogeneous nonlinear intrinsic dynamics...
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| Veröffentlicht in: | Complexity (New York, N.Y.) N.Y.), 2014-03, Vol.19 (4), p.20-31 |
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| container_title | Complexity (New York, N.Y.) |
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| creator | Lee, Tae H. Park, Ju H. Ji, D. H. Jung, H. Y. |
| description | This article considers the leader‐following consensus problem of heterogeneous multi‐agent systems. The proposed multi‐agent system is consisted of heterogeneous agents where each agents have their own nonlinear dynamic behavior. To overcome difficulty from heterogeneous nonlinear intrinsic dynamics of agents, a fuzzy disturbance observer is adopted. In addition, based on the Lyapunov stability theory, an adaptive control method is used to compensate the observation error caused by the difference between the unknown factor and estimated values. Two numerical examples are given to illustrate the effectiveness of the proposed method. © 2013 Wiley Periodicals, Inc. Complexity 19: 20–31, 2014 |
| doi_str_mv | 10.1002/cplx.21481 |
| format | Article |
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H.</creatorcontrib><creatorcontrib>Jung, H. Y.</creatorcontrib><title>Leader-following consensus problem of heterogeneous multi-agent systems with nonlinear dynamics using fuzzy disturbance observer</title><title>Complexity (New York, N.Y.)</title><addtitle>Complexity</addtitle><description>This article considers the leader‐following consensus problem of heterogeneous multi‐agent systems. The proposed multi‐agent system is consisted of heterogeneous agents where each agents have their own nonlinear dynamic behavior. To overcome difficulty from heterogeneous nonlinear intrinsic dynamics of agents, a fuzzy disturbance observer is adopted. In addition, based on the Lyapunov stability theory, an adaptive control method is used to compensate the observation error caused by the difference between the unknown factor and estimated values. Two numerical examples are given to illustrate the effectiveness of the proposed method. © 2013 Wiley Periodicals, Inc. Complexity 19: 20–31, 2014</description><subject>fuzzy disturbance observer</subject><subject>heterogeneous multi-agent systems</subject><subject>leader-following consensus</subject><subject>nonlinear intrinsic dynamics</subject><issn>1076-2787</issn><issn>1099-0526</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kMtOwzAQRSMEEuWx4QsssUNK8StxsoQKKFLFQwKVneW4E0hJ7GInlHTFp-NSYMnG9sjnzmhOFB0RPCQY01O9qD-GlPCMbEUDgvM8xglNt9dvkcZUZGI32vN-jjHOUyYG0ecE1AxcXNq6tsvKPCNtjQfjO48WzhY1NMiW6AVacPYZDNjw0XR1W8UqlC3yvW-h8WhZtS_IWFNXBpRDs96optIedX7dtOxWqx7NKt92rlBGA7KFB_cO7iDaKVXt4fDn3o8eLy8eRuN4cnt1PTqbxJqxnISz1CzTNKUq00LzJOOE4iLPgOdcFCVRjBfAdZLoNGEFE5xrhRWUbEY4Vwnbj443fcNWbx34Vs5t50wYKUmCOQ2eBAvUyYbSznrvoJQLVzXK9ZJguTYs14blt-EAkw28rGro_yHl6G7y9JuJN5mgAj7-Msq9ylQwkcjpzZW8v8zo9Hw0lpR9AcK7kPk</recordid><startdate>201403</startdate><enddate>201403</enddate><creator>Lee, Tae H.</creator><creator>Park, Ju H.</creator><creator>Ji, D. H.</creator><creator>Jung, H. Y.</creator><general>Blackwell Publishing Ltd</general><general>Hindawi Limited</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7XB</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>M2O</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>201403</creationdate><title>Leader-following consensus problem of heterogeneous multi-agent systems with nonlinear dynamics using fuzzy disturbance observer</title><author>Lee, Tae H. ; Park, Ju H. ; Ji, D. H. ; Jung, H. 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In addition, based on the Lyapunov stability theory, an adaptive control method is used to compensate the observation error caused by the difference between the unknown factor and estimated values. Two numerical examples are given to illustrate the effectiveness of the proposed method. © 2013 Wiley Periodicals, Inc. Complexity 19: 20–31, 2014</abstract><cop>Hoboken</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1002/cplx.21481</doi><tpages>12</tpages></addata></record> |
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| identifier | ISSN: 1076-2787 |
| ispartof | Complexity (New York, N.Y.), 2014-03, Vol.19 (4), p.20-31 |
| issn | 1076-2787 1099-0526 |
| language | eng |
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| source | Alma/SFX Local Collection |
| subjects | fuzzy disturbance observer heterogeneous multi-agent systems leader-following consensus nonlinear intrinsic dynamics |
| title | Leader-following consensus problem of heterogeneous multi-agent systems with nonlinear dynamics using fuzzy disturbance observer |
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