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Bipartite consensus problems of Lurie multi-agent systems over signed graphs: A contraction approach |
Xiaojiao Zhang(张晓娇)1,† and Xiang Wu(吴祥)2 |
1 School of Mathematics and Information Science, Nanchang Normal University, Nanchang 330032, China; 2 School of Mathematical Sciences, Guizhou Normal University, Guiyang 550001, China |
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Abstract This paper examines the bipartite consensus problems for the nonlinear multi-agent systems in Lurie dynamics form with cooperative and competitive communication between different agents. Based on the contraction theory, some new conditions for the nonlinear Lurie multi-agent systems reaching bipartite leaderless consensus and bipartite tracking consensus are presented. Compared with the traditional methods, this approach degrades the dimensions of the conditions, eliminates some restrictions of the system matrix, and extends the range of the nonlinear function. Finally, two numerical examples are provided to illustrate the efficiency of our results.
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Received: 10 January 2024
Revised: 29 March 2024
Accepted manuscript online: 12 April 2024
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PACS:
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02.30.Yy
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(Control theory)
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05.45.Xt
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(Synchronization; coupled oscillators)
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89.75.-k
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(Complex systems)
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Fund: Project supported by the National Natural Science Foundation of China (Grant No. 62363005), the Jiangxi Provincial Natural Science Foundation (Grant Nos. 20161BAB212032 and 20232BAB202034), and the Science and Technology Research Project of Jiangxi Provincial Department of Education (Grant Nos. GJJ202602 and GJJ202601). |
Corresponding Authors:
Xiaojiao Zhang
E-mail: xiaojiao-abc@hotmail.com
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Cite this article:
Xiaojiao Zhang(张晓娇) and Xiang Wu(吴祥) Bipartite consensus problems of Lurie multi-agent systems over signed graphs: A contraction approach 2024 Chin. Phys. B 33 070204
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[1] Olfati-Saber R and Murray R M 2004 IEEE Trans. Autom. Control 49 1520 [2] Yu W W, Chen G R, Cao M and Kurths J 2010 IEEE Trans. Syst. Man Cybern. B 40 881 [3] Li Z K, Duan Z S, Chen G R and Huang L 2010 IEEE Trans. Circuits Syst. I 57 213 [4] Wen G H, Hu G Q, Yu W W and Chen G R 2014 IEEE Trans. Circuits Syst. II 61 359 [5] Zhao Y, Duan Z S, Wen G H and Zhang Y J 2013 Syst. Control Lett. 62 22 [6] Liu X D, Liu H K, Du C K and Lu P L 2019 Int. J. Control 92 431 [7] Wasserman S and Faust K 1994 Social network analysis: Methods and applications (Cambridge: Cambridge University Press) p. 3 [8] Zhu L H, Tao X Y and Shen S L 2024 Eng. Appl. Artif. Intel. 128 107491 [9] Uchibe E and Asada M 2006 Proc. IEEE 94 1412 [10] Ke Y, Zhu L H, Wu P and Shi L 2022 Appl. Math. Comput. 435 127478 [11] Ma X R, Shen S L and Zhu L H 2023 Inform. Sci. 622 1141 [12] Zhu L H and Yuan T Y 2023 Nonlinear Dyn. 111 21707 [13] Zhang H W and Chen J 2017 Int. J. Robust Nonlin. 27 3 [14] Altafini C 2013 IEEE Trans. Autom. Control 58 935 [15] Wen G H, Wang H, Yu X H and Yu W W 2018 IEEE Trans. Circuits Syst. II 65 1204 [16] Zhang X X, Han W Y and Liu X P 2020 IET Control Theory A 14 2127 [17] Zhang X X and Wang X 2021 Int. J. Syst. Sci. 52 2255 [18] Wu J, Deng Q, Han T, Yang Q S and Zhan H 2019 Physica A 525 1360 [19] Wu J, Deng Q, Han T and Yan H C 2020 Neurocomputing 395 78 [20] Ren J, Song Q, Gao Y B, Zhao M and Lu G P 2021 Int. J. Syst. Sci. 52 277 [21] Sharifi A and Pourgholi M 2021 J. Franklin Inst. 358 9178 [22] Duan Z Y, Wei A R, Zhang X F and Mu R 2023 J. Franklin Inst. 360 4880 [23] Li J M, Yang X and Li Y Y 2023 Eng. Appl. Artif. Intel. 124 106514 [24] Zhang X X, Liu X P, Lewis F L and Wang X 2020 Physica A 545 123504 [25] Wang Q, He W L, Zino L, Tan D Y and Zhong W M 2022 Neurocomputing 488 130 [26] Shams A, Rehan M, Razaq M A and Tufail M 2022 Nonlinear Anal. Hybri. 44 101143 [27] Shams A, Rehan M and Tufail M 2022 Int. J. Control 95 1944 [28] Lui D G, Petrillo A and Santini S 2022 IFAC J. Syst. Control 22 100209 [29] Zhai S D and Li Q D 2016 J. Franklin Inst. 353 4602 [30] Liu F, Song Q, Wen G H, Lu J Q and Cao J D 2018 Int. J. Robust Nonlin. 28 6087 [31] Zhou S and Gao Y B 2021 Eur. J. Control 58 388 [32] Yang J Y, Huang J J, He X and Yang W Q 2023 ISA Trans. 135 290 [33] Liu C, Ding H and Zhou L 2020 Proceedings of the 39th Chinese Control Conference July 27-29, 2020, Shenyang, China, p. 5116 [34] Lohmiller W and Slotine J J E 1998 Automatica 34 683 [35] Slotine J J E and Wang W 2005 Cooperative control (Berlin: Springer) p. 207 [36] Wang W and Slotine J J E 2005 Biol. Cybern. 92 38 [37] Zhang X J and Cui B T 2013 Appl. Math. Comput. 223 180 |
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