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Yu, L., Ding, J., Peng, H., Liu, Y., & Liu, Y. Sampled-Data Based Containment Control for a Class of Nonlinear Multiagent Systems With Dynamic Leaders and Control Saturation. International Journal of Network Dynamics and Intelligence. 2025. doi: https://doi.org/10.53941/ijndi.2025.100011

This article focuses on examining the sampled-data based containment control (CC) issue for nonlinear multiagent systems (MASs) with dynamic leaders and input saturation. The proposed control protocol requires that the information is exchanged and calculated only at the sampling instants with the aim of conserving communication resources, and the protocol incorporates the control saturation as well. The CC is analyzed by means of the algebraic graph theory, M-matrix theory and Halanay-type inequal- ity, etc. Some criteria are derived to ensure the MAS can realize the CC under the control protocol, and in the meantime, a CC region is also given ensuring that all the followers with their initial stacked states in it will converge ultimately to the convex hull formed by the leaders. Furthermore, the design of the control gain can be carried out by searching for feasible solutions to a group of matrix inequalities. Finally, a numerical illustration is provided to substantiate the efficacy of the theoretical findings.

References

  1. Olfati-Saber, R.; Fax, J.A.; Murray, R.M. Consensus and cooperation in networked multi-agent systems. Proc. IEEE, 2007, 95: 215−233. doi: 10.1109/JPROC.2006.887293
  2. Wu, Y.Q.; Su, H.Y.; Shi, P.; et al. Consensus of multiagent systems using aperiodic sampled-data control. IEEE Trans. Cybern., 2016, 46: 2132−2143. doi: 10.1109/TCYB.2015.2466115
  3. Miao, G.Y.; Feng, Y.Z.; Li, T. Containment control for multi-agent systems with input saturation. IMA J. Math. Control Inf., 2017, 34: 667−682. doi: 10.1093/imamci/dnv068
  4. Ye, Y.Y.; Wei, H.Y.; Lu, R.Q.; et al. Containment control for networked fractional-order systems with sampled position data. IEEE Trans. Circuits Syst. I: Regul. Pap., 2021, 68: 3881−3889. doi: 10.1109/TCSI.2021.3090953
  5. Yu, L.Y.; Peng, H.H.; Liu, Y.R.; et al. Event-driven containment control for a class of nonlinear multi-agent systems with sampled-data. Discrete Contin. Dyn. Syst., 2024, 17: 2947−2966. doi: 10.3934/dcdss.2024101
  6. Hu, J.P.; Hong, Y.G. Leader-following coordination of multi-agent systems with coupling time delays. Phys. A: Stat. Mech. Appl., 2007, 374: 853−863. doi: 10.1016/j.physa.2006.08.015
  7. Zhu, W.; Cheng, D.Z. Leader-following consensus of second-order agents with multiple time-varying delays. Automatica, 2010, 46: 1994−1999. doi: 10.1016/j.automatica.2010.08.003
  8. Cao, W.J.; Zhang, J.H.; Ren, W. Leader–follower consensus of linear multi-agent systems with unknown external disturbances. Syst. Control Lett., 2015, 82: 64−70. doi: 10.1016/j.sysconle.2015.05.007
  9. Li, H.F.; Liu, Q.R.; Feng, G.; et al. Leader–follower consensus of nonlinear time-delay multiagent systems: A time-varying gain approach. Automatica, 2021, 126: 109444. doi: 10.1016/j.automatica.2020.109444
  10. Lin, L.; Cao, J.D.; Lam, J.; et al. Leader-follower consensus over finite fields. IEEE Trans. Autom. Control, 2024, 69: 4718−4725. doi: 10.1109/TAC.2024.3354195
  11. Wu, X.Q.; Mao, B.; Wu, X.Q.; et al. Dynamic event-triggered leader-follower consensus control for MultiAgent systems. SIAM J. Control Optim., 2022, 60: 189−209. doi: 10.1137/20M1321152
  12. Yaghoubi, Z.; Taheri Javan, N.; Bahaghighat, M. Consensus tracking for a class of fractional-order non-linear multi-agent systems via an adaptive dynamic surface controller. Syst. Sci. Control Eng., 2023, 11: 2207602. doi: 10.1080/21642583.2023.2207602
  13. Zhang, T.H.; Liu, Q.X.; Liu, J.Y.; et al. Multiple-bipartite consensus for networked lagrangian systems without using neighbours’ velocity information in the directed graph. Syst. Sci. Control Eng., 2023, 11: 2210185. doi: 10.1080/21642583.2023.2210185
  14. Xiong, H.X.; Chen, G.D.; Ren, H.R.; et al. Event-based model-free adaptive consensus control for multi-agent systems under intermittent attacks. Int. J. Syst. Sci., 2024, 55: 2062−2076. doi: 10.1080/00207721.2024.2329739
  15. Xu, X.Y.; Liu, Y.G. Adaptive consensus with limited information for uncertain nonlinear multi-agent systems. Int. J. Syst. Sci., 2024, 55: 1820−1834. doi: 10.1080/00207721.2024.2321371
  16. Cao, Y.C.; Ren, W. Containment control with multiple stationary or dynamic leaders under a directed interaction graph. In Proceedings of the 48h IEEE Conference on Decision and Control (CDC) Held Jointly with 2009 28th Chinese Control Conference, Shanghai, China, 15–18 December 2009; IEEE: New York, 2009; pp. 3014–3019. doi: 10.1109/CDC.2009.5399946
  17. Li, P.Y.; Jabbari, F.; Sun, X.M. Containment control of multi-agent systems with input saturation and unknown leader inputs. Automatica, 2021, 130: 109677. doi: 10.1016/j.automatica.2021.109677
  18. Li, Z.K.; Ren, W.; Liu, X.D.; et al. Distributed containment control of multi-agent systems with general linear dynamics in the presence of multiple leaders. Int. J. Robust Nonlinear Control, 2013, 23: 534−547. doi: 10.1002/rnc.1847
  19. Cao, Y.C.; Ren, W.; Egerstedt, M. Distributed containment control with multiple stationary or dynamic leaders in fixed and switching directed networks. Automatica, 2012, 48: 1586−1597. doi: 10.1016/j.automatica.2012.05.071
  20. Ge, X.H.; Han, Q.L.; Ding, D.R.; et al. A survey on recent advances in distributed sampled-data cooperative control of multi-agent systems. Neurocomputing, 2018, 275: 1684−1701. doi: 10.1016/j.neucom.2017.10.008
  21. Ferrari-Trecate, G.; Egerstedt, M.; Buffa, A.; et al. Laplacian sheep: A hybrid, stop-go policy for leader-based containment control. In Proceedings of the 9th International Workshop on Hybrid Systems: Computation and Control, Santa Barbara, CA, USA, 29–31 March 2006; Springer: Berlin/Heidelberg, Germany, 2006; pp. 212–226. doi: 10.1007/11730637_18
  22. Lou, Y.C.; Hong, Y.G. Target containment control of multi-agent systems with random switching interconnection topologies Automatica 2012, 48, 879–885. doi: 10.1016/j.automatica.2012.02.032
  23. Sun, H.Y.; Han, H.G.; Sun, J.; et al. Leader-following sampled-data consensus of multiagent systems with successive packet losses and stochastic sampling. IEEE Trans. Cybern., 2024, 54: 7381−7391. doi: 10.1109/TCYB.2024.3466610
  24. Shi, Z.H.; Zou, W.C.; Guo, J. Sampled-data consensus protocol for multiagent systems subject to random intermittent actuator faults. IEEE Syst. J., 2024, 18: 1368−1379. doi: 10.1109/JSYST.2024.3377452
  25. Wen, H.; Wu, W.; Tong, S.C. Fuzzy adaptive asynchronous sampled-data consensus control for nonlinear multi-agent systems under DoS attacks. J. Control Decis. 2024. doi: 10.1080/23307706.2024.2417826
  26. Zhang, J.X.; Su, H.S. Formation-containment control for multi-agent systems with sampled data and time delays. Neurocomputing, 2021, 424: 125−131. doi: 10.1016/j.neucom.2019.11.030
  27. Wang, Y.; Liu, H.J.; Tan, H.L. An overview of filtering for sampled-data systems under communication constraints. Int. J. Network Dyn. Intell., 2023, 2: 100011. doi: 10.53941/ijndi.2023.100011
  28. Ding, L.S.; Sun, W.W. Predefined time fuzzy adaptive control of switched fractional-order nonlinear systems with input saturation. Int. J. Network Dyn. Intell., 2023, 2: 100019. doi: 10.53941/ijndi.2023.100019
  29. Tarbouriech, S.; Garcia, G.; da Silva, J.M.G., Jr.; et al. Stability and Stabilization of Linear Systems with Saturating Actuators; Springer: London, UK, 2011. doi: 10.1007/978-0-85729-941-3
  30. Yu, L.Y.; Cui, Y.; Lu, Z.Y.; et al. Sampled-based bipartite tracking consensus of nonlinear multiagents subject to input saturation. Complex Eng. Syst., 2022, 2: 6. doi: 10.20517/ces.2022.08
  31. Yang, T.; Meng, Z.Y.; Dimarogonas, D.V.; et al. Global consensus for discrete-time multi-agent systems with input saturation constraints. Automatica, 2014, 50: 499−506. doi: 10.1016/j.automatica.2013.11.008
  32. Gao, C.; Wang, Z.D.; He, X.; et al. Consensus control of linear multiagent systems under actuator imperfection: When saturation meets fault. IEEE Trans. Syst. Man Cybern. Syst., 2022, 52: 2651−2663. doi: 10.1109/TSMC.2021.3050370
  33. Taylor, A.E.; Lay, D.C. Introduction to Functional Analysis, 2nd ed.; Krieger Publishing Co., Inc.: Melbourne, USA, 1986.
  34. Haghshenas, H.; Badamchizadeh, M.A.; Baradarannia, M. Containment control of heterogeneous linear multi-agent systems. Automatica, 2015, 54: 210−216. doi: 10.1016/j.automatica.2015.02.002
  35. Mei, J.; Ren, W.; Ma, G.F. Distributed containment control for multiple nonlinear systems with identical dynamics. In Proceedings of the 30th Chinese Control Conference, Yantai, China, 22–24 July 2011; IEEE: New York, 2011; pp. 6544–6549.
  36. Wang, P.; Jia, Y.M. Distributed containment control of second-order multi-agent systems with inherent non-linear dynamics. IET Control Theory Appl., 2014, 8: 277−287. doi: 10.1049/iet-cta.2013.0686
  37. Xu, J.Q.; Liu, Y.R.; Cui, Y.; et al. Stochastic containment control for a class of nonlinear multi-agent system with switched topology and mixed time-delays. Int. J. Syst. Sci., 2020, 51: 2520−2532. doi: 10.1080/00207721.2020.1797229
  38. Hu, J.Q.; Yu, J.; Cao, J.D. Distributed containment control for nonlinear multi-agent systems with time-delayed protocol. Asian J. Control, 2016, 18: 747−756. doi: 10.1002/asjc.1131
  39. Ren, W.; Cao, Y.C. Distributed Coordination of Multi-Agent Networks: Emergent Problems, Models, and Issues; Springer: London, UK, 2011. doi: 10.1007/978-0-85729-169-1
  40. Tarbouriech, S.; Prieur, C.; da Silva, J.M.G. Stability analysis and stabilization of systems presenting nested saturations. IEEE Trans. Autom. Control, 2006, 51: 1364−1371. doi: 10.1109/TAC.2006.878743
  41. Yu, L.Y.; Liu, Y.R.; Cui, Y.; et al. Intermittent dynamic event-triggered state estimation for delayed complex networks based on partial nodes. Neurocomputing, 2021, 459: 59−69. doi: 10.1016/j.neucom.2021.06.017
  42. Liu, Y.R.; Wang, Z.D.; Liu, X.H. On synchronization of coupled neural networks with discrete and unbounded distributed delays. Int. J. Comput. Math., 2008, 85: 1299−1313. doi: 10.1080/00207160701636436
  43. Liu, Y.R.; Wang, Z.D.; Yuan, Y.; et al. Partial-nodes-based state estimation for complex networks with unbounded distributed delays. IEEE Trans. Neural Networks Learn. Syst., 2018, 29: 3906−3912. doi: 10.1109/TNNLS.2017.2740400
  44. Zou, L.; Wang, Z.D.; Shen, B.; et al. Secure recursive state estimation of networked systems against eavesdropping: A partial-encryption-decryption method. IEEE Trans. Autom. Control, 2024. in press, doi: 10.1109/TAC.2024.3512413
  45. Zou, L.; Wang, Z.D.; Shen, B.; et al. Recursive state estimation in relay channels with enhanced security against eavesdropping: An innovative encryption-decryption framework. Automatica, 2025, 174: 112159. doi: 10.1016/j.automatica.2025.112159