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Tracking Consensus of Networked Random Nonlinear Multi-agent Systems with Intermittent Communications (2401.05808v1)

Published 11 Jan 2024 in eess.SY and cs.SY

Abstract: The paper proposes an intermittent communication mechanism for the tracking consensus of high-order nonlinear multi-agent systems (MASs) surrounded by random disturbances. Each collaborating agent is described by a class of high-order nonlinear uncertain strict-feedback dynamics which is disturbed by a wide stationary process representing the external noise. The resiliency level of this networked control system (NCS) to the failures of physical devices or unreliability of communication channels is analyzed by introducing a linear auxiliary trajectory of the system. More precisely, the unreliability of communication channels sometimes makes an agent incapable of sensing the local information or receiving it from neighboring nodes. Therefore, an intermittent communication scheme is proposed among the follower agents as a consequence of employing the linear auxiliary dynamics. The closed-loop networked system signals are proved to be noise-to-state practically stable in probability (NSpS-P). It has been justified that each agent follows the trajectory of the corresponding local auxiliary virtual system practically in probability. The simulation experiments finally quantify the effectiveness of our proposed approach in terms of providing a resilient performance against unreliability of communication channels and reaching the tracking consensus.

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References (27)
  1. R. Olfati-Saber, J. A. Fax, and R. M. Murray, “Consensus and cooperation in networked multi-agent systems,” Proceedings of the IEEE, vol. 95, no. 1, pp. 215–233, 2007.
  2. A. Azarbahram, A. Amini, and N. Pariz, “Event-triggered tracking formation of networked nonlinear intelligent transportation systems surrounded by random disturbances,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 11, pp. 21959–21970, 2022.
  3. M. Shahvali, A. Azarbahram, M.-B. Naghibi-Sistani, and J. Askari, “Bipartite consensus control for fractional-order nonlinear multi-agent systems: An output constraint approach,” Neurocomputing, vol. 397, pp. 212–223, 2020.
  4. A. Amini, A. Azarbahram, and M. Sojoodi, “h∞subscriptℎh_{\infty}italic_h start_POSTSUBSCRIPT ∞ end_POSTSUBSCRIPT consensus of nonlinear multi-agent systems using dynamic output feedback controller: an lmi approach,” Nonlinear Dynamics, vol. 85, pp. 1865–1886, 2016.
  5. M. Shahvali, A. Azarbahram, and N. Pariz, “Adaptive output consensus of nonlinear fractional-order multi-agent systems: a fractional-order backstepping approach,” International Journal of General Systems, vol. 52, no. 2, pp. 147–168, 2023.
  6. B. Wu, M. D. Lemmon, and H. Lin, “Formal methods for stability analysis of networked control systems with ieee 802.15.4 protocol,” IEEE Transactions on Control Systems Technology, vol. 26, no. 5, pp. 1635–1645, 2018.
  7. A. Azarbahram and A. Amini, “Secure event-triggered tracking consensus under denial of service: A resilient periodically intermittent approach,” IEEE Control Systems Letters, vol. 6, pp. 2786–2791, 2022.
  8. A. Amini, A. Asif, A. Mohammadi, and A. Azarbahram, “Sampled-data dynamic event-triggering control for networked systems subject to dos attacks,” IEEE Transactions on Network Science and Engineering, 2021.
  9. A. Amini, A. Azarbahram, A. Mohammadi, and A. Asif, “Resilient event-triggered average consensus under denial of service attack and uncertain network,” in 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT), pp. 291–296, IEEE, 2019.
  10. W. Zou, C. K. Ahn, and Z. Xiang, “Event-triggered consensus tracking control of stochastic nonlinear multiagent systems,” IEEE Systems Journal, vol. 13, no. 4, pp. 4051–4059, 2019.
  11. A. Azarbahram, N. Pariz, M.-B. Naghibi-Sistani, and R. Kardehi Moghaddam, “Event-triggered formation control of n-link networked stochastic robotic manipulators,” Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, vol. 236, no. 5, pp. 927–943, 2022.
  12. A. Azarbahram, N. Pariz, M.-B. Naghibi-Sistani, and R. Kardehi Moghaddam, “Platoon of uncertain unmanned surface vehicle teams subject to stochastic environmental loads,” International Journal of Adaptive Control and Signal Processing, vol. 36, no. 3, pp. 729–750, 2022.
  13. W. Zou, P. Shi, Z. Xiang, and Y. Shi, “Consensus tracking control of switched stochastic nonlinear multiagent systems via event-triggered strategy,” IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 3, pp. 1036–1045, 2020.
  14. Z. Wu, H. R. Karimi, and P. Shi, “Practical trajectory tracking of random lagrange systems,” Automatica, vol. 105, pp. 314–322, 2019.
  15. Y. Li, Y. Wu, and S. He, “Distributed consensus control for a group of autonomous marine vehicles with nonlinearity and external disturbances,” Neurocomputing, vol. 443, pp. 380–387, 2021.
  16. L. Yao, W. Zhang, and X.-J. Xie, “Stability analysis of random nonlinear systems with time-varying delay and its application,” Automatica, vol. 117, p. 108994, 2020.
  17. H. Zhang, R. Xi, Y. Wang, S. Sun, and J. Sun, “Event-triggered adaptive tracking control for random systems with coexisting parametric uncertainties and severe nonlinearities,” IEEE Transactions on Automatic Control, pp. 1–1, 2021.
  18. H. Wang, W. Li, and M. Tang, “Distributed output tracking of nonlinear multi-agent systems perturbed by second-order moment processes,” Neurocomputing, vol. 452, pp. 789–795, 2021.
  19. X. Bao, H. Wang, and W. Li, “Containment control for upper-triangular nonlinear multi-agent systems perturbed by second-order moment processes,” IEEE Access, vol. 9, pp. 21102–21111, 2021.
  20. C. Li, G. Feng, and X. Liao, “Stabilization of nonlinear systems via periodically intermittent control,” IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 54, no. 11, pp. 1019–1023, 2007.
  21. W. Guo and H. Xiao, “Distributed consensus of the nonlinear second-order multi-agent systems via mixed intermittent protocol,” Nonlinear Analysis: Hybrid Systems, vol. 30, pp. 189–198, 2018.
  22. H. Li, J. Zhang, L. Jing, and W. Ying, “Neural-network-based adaptive quasi-consensus of nonlinear multi-agent systems with communication constrains and switching topologies,” Nonlinear Analysis: Hybrid Systems, vol. 35, p. 100833, 2020.
  23. N. Xavier and B. Bandyopadhyay, “Practical sliding mode using state depended intermittent control,” IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 68, no. 1, pp. 341–345, 2020.
  24. Q. Wang and Y. He, “Time-triggered intermittent control of continuous systems,” International Journal of Robust and Nonlinear Control, vol. 31, no. 14, pp. 6867–6879, 2021.
  25. Y. Yang and Y. He, “Non-fragile observer-based robust control for uncertain systems via aperiodically intermittent control,” Information Sciences, vol. 573, pp. 239–261, 2021.
  26. B. Liu, M. Yang, T. Liu, and D. J. Hill, “Stabilization to exponential input-to-state stability via aperiodic intermittent control,” IEEE Transactions on Automatic Control, vol. 66, no. 6, pp. 2913–2919, 2020.
  27. F. L. Lewis, K. Liu, and A. Yesildirek, “Neural net robot controller with guaranteed tracking performance,” IEEE Trans. Neural Netw., vol. 6, no. 3, pp. 703–715, 1995.

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