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Event-triggered consensus control of heterogeneous multi-agent systems: model- and data-based approaches

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Abstract

This article addresses the model- and data-based event-triggered consensus of heterogeneous leader/follower multi-agent systems (MASs). A dynamic periodic transmission protocol is developed to alleviate the communication and computational burden, where the followers can interact locally with neighbors to approach the dynamics of the leader. Capitalizing on a discrete-time looped-functional, a model-based consensus condition for the closed-loop MASs is derived as linear matrix inequalities (LMIs), along with a design method for obtaining distributed event-triggered controllers and the associated triggering parameters. Upon collecting noise-corrupted state-input measurements in offline open-loop experiments, a data-based leader/follower MAS representation is derived and employed to address the data-driven consensus control problem without explicit MAS models. This result is subsequently generalized to guarantee an \({{\cal H}_\infty }\) control performance. Finally, a simulation example is given to corroborate the efficiency of the proposed distributed triggering scheme and the data-driven consensus controller.

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References

  1. Dimarogonas D V, Frazzoli E, Johansson K H. Distributed event-triggered control for multi-agent systems. IEEE Trans Automat Contr, 2012, 57: 1291–1297

    Article  MathSciNet  MATH  Google Scholar 

  2. Ma L F, Wang Z D, Han Q-L, et al. Consensus control of stochastic multi-agent systems: a survey. Sci China Inf Sci, 2017, 60: 120201

    Article  MathSciNet  Google Scholar 

  3. Zhao J, Liu G P. Time-variant consensus tracking control for networked planar multi-agent systems with non-holonomic constraints. J Syst Sci Complex, 2018, 31: 396–418

    Article  MathSciNet  MATH  Google Scholar 

  4. Wu W, Peng Z, Liu L, et al. A general safety-certified cooperative control architecture for interconnected intelligent surface vehicles with applications to vessel train. IEEE Trans Intell Veh, 2022, 7: 627–637

    Article  Google Scholar 

  5. Shi J. Cooperative control for nonlinear multi-agent systems based on event-triggered scheme. IEEE Trans Circuits Syst II, 2021, 68: 1977–1981

    Google Scholar 

  6. Yang Y, Li Y F, Yue D. Event-trigger-based consensus secure control of linear multi-agent systems under DoS attacks over multiple transmission channels. Sci China Inf Sci, 2020, 63: 150208

    Article  MathSciNet  Google Scholar 

  7. Deng F, Ding N, Ye Z M, et al. Wearable ubiquitous energy system. Sci China Inf Sci, 2021, 64: 124201

    Article  Google Scholar 

  8. Xiao W, Yu J, Wang R, et al. Time-varying formation control for time-delayed multi-agent systems with general linear dynamics and switching topologies. Unmanned Sys, 2019, 7: 3–13

    Article  Google Scholar 

  9. Chen J, Sun J, Wang G. From unmanned systems to autonomous intelligent systems. Engineering, 2022, 12: 16–19

    Article  Google Scholar 

  10. Xu Y, Sun J, Wang G, et al. Dynamic triggering mechanisms for distributed adaptive synchronization control and its application to circuit systems. IEEE Trans Circ Syst I, 2021, 68: 2246–2256

    MathSciNet  Google Scholar 

  11. Li Y F, Wang X, Sun J, et al. Data-driven consensus control of fully distributed event-triggered multi-agent systems. Sci China Inf Sci, 2023, 66: 152202

    Article  MathSciNet  Google Scholar 

  12. Wang X, Sun J, Wang G, et al. Data-driven control of distributed event-triggered network systems. IEEE CAA J Autom Sin, 2023, 10: 351–364

    Article  Google Scholar 

  13. Liu W, Huang J. Leader-following consensus for linear multiagent systems via asynchronous sampled-data control. IEEE Trans Automat Contr, 2020, 65: 3215–3222

    Article  MathSciNet  MATH  Google Scholar 

  14. Qian Y Y, Liu L, Feng G. Output consensus of heterogeneous linear multi-agent systems with adaptive event-triggered control. IEEE Trans Automat Contr, 2019, 64: 2606–2613

    Article  MathSciNet  MATH  Google Scholar 

  15. Chen Z Y, Han Q-L, Yan Y M, et al. How often should one update control and estimation: review of networked triggering techniques. Sci China Inf Sci, 2020, 63: 150201

    Article  MathSciNet  Google Scholar 

  16. Xin W, Sun J, Wang G, et al. A mixed switching event-triggered transmission scheme for networked control systems. IEEE Trans Control Netw Syst, 2022, 9: 390–402

    Article  MathSciNet  Google Scholar 

  17. Nowzari C, Garcia E, Cortés J. Event-triggered communication and control of networked systems for multi-agent consensus. Automatica, 2019, 105: 1–27

    Article  MathSciNet  MATH  Google Scholar 

  18. Girard A. Dynamic triggering mechanisms for event-triggered control. IEEE Trans Automat Contr, 2015, 60: 1992–1997

    Article  MathSciNet  MATH  Google Scholar 

  19. Tabuada P. Event-triggered real-time scheduling of stabilizing control tasks. IEEE Trans Automat Contr, 2007, 52: 1680–1685

    Article  MathSciNet  MATH  Google Scholar 

  20. Hu W, Yang C, Huang T, et al. A distributed dynamic event-triggered control approach to consensus of linear multiagent systems with directed networks. IEEE Trans Cybern, 2020, 50: 869–874

    Article  Google Scholar 

  21. Mishra R K, Ishii H. Dynamic event-triggered consensus control of discrete-time linear multi-agent systems. IFAC-PapersOnLine, 2021, 54: 123–128

    Article  Google Scholar 

  22. Borgers D P, Dolk V S, Heemels W P M H. Riccati-based design of event-triggered controllers for linear systems with delays. IEEE Trans Automat Contr, 2018, 63: 174–188

    Article  MathSciNet  MATH  Google Scholar 

  23. Åström K J, Wittenmark B. On self tuning regulators. Automatica, 1973, 9: 185–199

    Article  MATH  Google Scholar 

  24. Willems J C, Rapisarda P, Markovsky I, et al. A note on persistency of excitation. Syst Control Lett, 2005, 54: 325–329

    Article  MathSciNet  MATH  Google Scholar 

  25. de Persis C, Tesi P. Formulas for data-driven control: stabilization, optimality, and robustness. IEEE Trans Automat Contr, 2020, 65: 909–924

    Article  MathSciNet  MATH  Google Scholar 

  26. Coulson J, Lygeros J, Dorfler F. Data-enabled predictive control: in the shallows of the DeePC. In: Proceedings of the 18th European Control Conference (ECC), Naples, 2019, 1: 307–312

    Google Scholar 

  27. Allibhoy A, Cortés J. Data-based receding horizon control of linear network systems. IEEE Control Syst Lett, 2020, 5: 1207–1212

    Article  MathSciNet  Google Scholar 

  28. Berberich J, Kohler J, Muller M A, et al. Data-driven model predictive control with stability and robustness guarantees. IEEE Trans Automat Contr, 2021, 66: 1702–1717

    Article  MathSciNet  MATH  Google Scholar 

  29. Liu W, Sun J, Wang G, et al. Data-driven resilient predictive control under denial-of-service. IEEE Trans Automat Contr, 2022. doi: https://doi.org/10.1109/TAC.2022.3209399

  30. Abouheaf M I, Lewis F L, Vamvoudakis K G, et al. Multi-agent discrete-time graphical games and reinforcement learning solutions. Automatica, 2014, 50: 3038–3053

    Article  MathSciNet  MATH  Google Scholar 

  31. Li J, Ran M, Wang H, et al. A behavior-based mobile robot navigation method with deep reinforcement learning. Unmanned Sys, 2021, 9: 201–209

    Article  Google Scholar 

  32. Jiao J, van Waarde H J, Trentelman H L, et al. Data-driven output synchronization of heterogeneous leader-follower multi-agent systems. In: Proceedings of the 60th IEEE Conference on Decision and Control, 2021. 466–471

  33. Wang X, Berberich J, Sun J, et al. Model-based and data-driven control of event- and self-triggered discrete-time LTI systems. IEEE Trans Cybern, 2023. doi: https://doi.org/10.1109/TCYB.2023.3272216

  34. Berberich J, Scherer C W, Allgower F. Combining prior knowledge and data for robust controller design. IEEE Trans Automat Contr, 2022. doi: https://doi.org/10.1109/TAC.2022.3209342

  35. Wildhagen S, Berberich J, Hertneck M, et al. Data-driven analysis and controller design for discrete-time systems under aperiodic sampling. IEEE Trans Automat Contr, 2022. doi: https://doi.org/10.1109/TAC.2022.3183969

  36. Chen J, Xu S, Jia X, et al. Novel summation inequalities and their applications to stability analysis for systems with time-varying delay. IEEE Trans Automat Contr, 2017, 62: 2470–2475

    Article  MathSciNet  MATH  Google Scholar 

  37. Fridman E. A refined input delay approach to sampled-data control. Automatica, 2010, 46: 421–427

    Article  MathSciNet  MATH  Google Scholar 

  38. Fujioka H. Stability analysis of systems with aperiodic sample-and-hold devices. Automatica, 2009, 45: 771–775

    Article  MathSciNet  MATH  Google Scholar 

  39. Seuret A. A novel stability analysis of linear systems under asynchronous samplings. Automatica, 2012, 48: 177–182

    Article  MathSciNet  MATH  Google Scholar 

  40. Wang X, Sun J, Dou L. Improved results on stability analysis of sampled-data systems. Int J Robust Nonlinear Control, 2021, 31: 6549–6561

    Article  MathSciNet  Google Scholar 

  41. Berberich J, Wildhagen S, Hertneck M, et al. Data-driven analysis and control of continuous-time systems under aperiodic sampling. IFAC-PapersOnLine, 2021, 54: 210–215

    Article  Google Scholar 

  42. Scherer C W. LPV control and full block multipliers. Automatica, 2001, 37: 361–375

    Article  MathSciNet  MATH  Google Scholar 

  43. Chung Y F, Kia S S. Distributed leader following of an active leader for linear heterogeneous multi-agent systems. Syst Control Lett, 2020, 137: 104621

    Article  MathSciNet  MATH  Google Scholar 

  44. Sturm J F. Using SeDuMi 1.02, a Matlab toolbox for optimization over symmetric cones. Optim Methods Softw, 1999, 11: 625–653

    Article  MathSciNet  MATH  Google Scholar 

  45. Kiumarsi B, Lewis F L. Output synchronization of heterogeneous discrete-time systems: a model-free optimal approach. Automatica, 2017, 84: 86–94

    Article  MathSciNet  MATH  Google Scholar 

  46. Wang X, Sun J, Berberich J, et al. Data-driven control of dynamic event-triggered systems with delays. Int J Robust Nonlinear Control, 2023. doi:https://doi.org/10.1002/rnc.6740

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Acknowledgements

This work was supported in part by National Key R&D Program of China (Grant No. 2021YFB1714800) and National Natural Science Foundation of China (Grant Nos. 62173034, 61925303, 62088101, U20B2073).

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Authors and Affiliations

  1. School of Automation, Beijing Institute of Technology, Beijing, 100081, China

    Xin Wang, Jian Sun, Fang Deng & Gang Wang

  2. National Key Lab of Autonomous Intelligent Unmanned Systems, Beijing, 100081, China

    Xin Wang, Jian Sun, Fang Deng, Gang Wang & Jie Chen

  3. Beijing Institute of Technology Chongqing Innovation Center, Chongqing, 401120, China

    Xin Wang, Jian Sun, Fang Deng & Gang Wang

  4. Department of Control Science and Engineering, Tongji University, Shanghai, 201804, China

    Jie Chen

Authors
  1. Xin Wang
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  2. Jian Sun
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  3. Fang Deng
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  4. Gang Wang
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  5. Jie Chen
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Corresponding author

Correspondence to Gang Wang.

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Wang, X., Sun, J., Deng, F. et al. Event-triggered consensus control of heterogeneous multi-agent systems: model- and data-based approaches. Sci. China Inf. Sci. 66, 192201 (2023). https://doi.org/10.1007/s11432-022-3683-y

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  • DOI: https://doi.org/10.1007/s11432-022-3683-y

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