Special Issue on Multi-Agent Collaborative Perception and Control

Fault-Tolerant Dynamical Consensus of Double-Integrator Multi-Agent Systems in the Presence of Asynchronous Self-Sensing Function Failures

Expand
  • (Engineering Research Center of Internet of Things Technology Applications of the Ministry of Education, School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, Jiangsu, China)

Accepted date: 2023-08-22

  Online published: 2024-07-28

Abstract

Double-integrator multi-agent systems (MASs) might not achieve dynamical consensus, even if only partial agents suffer from self-sensing function failures (SSFFs). SSFFs might be asynchronous in real engineering application. The existing fault-tolerant dynamical consensus protocol suitable for synchronous SSFFs cannot be directly used to tackle fault-tolerant dynamical consensus of double-integrator MASs with partial agents subject to asynchronous SSFFs. Motivated by these facts, this paper explores a new fault-tolerant dynamical consensus protocol suitable for asynchronous SSFFs. First, multi-hop communication together with the idea of treating asynchronous SSFFs as multiple piecewise synchronous SSFFs is used for recovering the connectivity of network topology among all normal agents. Second, a fault-tolerant dynamical consensus protocol is designed for doubleintegrator MASs by utilizing the history information of an agent subject to SSFF for computing its own state information at the instants when its minimum-hop normal neighbor set changes. Then, it is theoretically proved that if the strategy of network topology connectivity recovery and the fault-tolerant dynamical consensus protocol with proper time-varying gains are used simultaneously, double-integrator MASs with all normal agents and all agents subject to SSFFs can reach dynamical consensus. Finally, comparison numerical simulations are given to illustrate the effectiveness of the theoretical results.

Cite this article

WU Zhihai (吴治海), XIE Linbo (谢林柏) . Fault-Tolerant Dynamical Consensus of Double-Integrator Multi-Agent Systems in the Presence of Asynchronous Self-Sensing Function Failures[J]. Journal of Shanghai Jiaotong University(Science), 2024 , 29(4) : 613 -624 . DOI: 10.1007/s12204-024-2716-1

References

[1] YANG Y Z, CHEN Y Y, YANG H Y. Robust flocking of multiple intelligent agents with multiple disturbances [J]. International Journal of Intelligent Systems, 2022, 37(10): 7571-7583.
[2] DE S, SAHOO S R, WAHI P. A rendezvous strategy with R2 reachability for kinematic agents [J]. IEEE Transactions on Automatic Control, 2021, 66(1): 369-374.
[3] ZHU G L, LIU K X, GU H B, et al. Observerbased event-triggered formation control of multi-agent systems with switching directed topologies [J]. IEEE Transactions on Circuits and Systems I: Regular Papers, 2022, 69(3): 1323-1332.
[4] LIU C D, NIU B, LIU L, et al. Event-triggered adaptive bipartite asymptotic tracking control using intelligent technique for stochastic nonlinear multiagent systems [J]. IEEE Transactions on Artificial Intelligence, 2023, 4(6): 1616-1626.
[5] YANG Y H, HU W F. Containment control of doubleintegrator multi-agent systems with time-varying delays [J]. IEEE Transactions on Network Science and Engineering, 2022, 9(2): 457-466.
[6] YU X, SU R. Decentralized circular formation control of nonholonomic mobile robots under a directed sensorgraph [J]. IEEE Transactions on Automatic Control, 2023, 68(6): 3656-3663.
[7] WANG F K, HUANG J L, LOW K H, et al. AGDS: Adaptive goal-directed strategy for swarm drones flying through unknown environments [J]. Complex & Intelligent Systems, 2023, 9(2): 2065-2080.
[8] NURELLARI E, MCLERNON D, GHOGHO M. Distributed two-step quantized fusion rules via consensus algorithm for distributed detection in wireless sensor networks [J]. IEEE Transactions on Signal and Information Processing Over Networks, 2016, 2(3): 321-335.
[9] SHI F R, TUO X G, RAN L L, et al. Fast convergence time synchronization in wireless sensor networks based on average consensus [J]. IEEE Transactions on Industrial Informatics, 2020, 16(2): 1120-1129.
[10] ZHANG Y, RAHBARI-ASR N, DUAN J, et al. Day-ahead smart grid cooperative distributed energy scheduling with renewable and storage integration [J]. IEEE Transactions on Sustainable Energy, 2016, 7(4): 1739-1748.
[11] WUTHISHUWONG C, TRAECHTLER A. Distributed control system architecture for balancing and stabilizing traffic in the network of multiple autonomous intersections using feedback consensus and route assignment method [J]. Complex & Intelligent Systems, 2020, 6(1): 165-187.
[12] LI Y J, TAN C. A survey of the consensus for multiagent systems [J]. Systems Science & Control Engineering, 2019, 7(1): 468-482.
[13] YANG H, HAN Q L, GE X H, et al. Fault-tolerant cooperative control of multiagent systems: A survey of trends and methodologies [J]. IEEE Transactions on Industrial Informatics, 2020, 16(1): 4-17.
[14] ZHANG D, FENG G, SHI Y, et al. Physical safety and cyber security analysis of multi-agent systems: A survey of recent advances [J]. IEEE/CAA Journal of Automatica Sinica, 2021, 8(2): 319-333.
[15] HE W L, XU W Y, GE X H, et al. Secure control of multiagent systems against malicious attacks: A brief survey [J]. IEEE Transactions on Industrial Informatics, 2022, 18(6): 3595-3608.
[16] AMIRKHANI A, BARSHOOI A H. Consensus in multi-agent systems: A review [J]. Artificial Intelligence Review, 2022, 55(5): 3897-3935.
[17] GAO C, HE X, DONG H L, et al. A survey on fault-tolerant consensus control of multi-agent systems: Trends, methodologies and prospects [J]. International Journal of Systems Science, 2022, 53(13): 2800-2813.
[18] ISHII H, WANG Y, FENG S. An overview on multiagent consensus under adversarial attacks [J]. Annual Reviews in Control, 2022, 53: 252-272.
[19] REN W, ATKINS E. Distributed multi-vehicle coordinated control via local information exchange [J]. International Journal of Robust and Nonlinear Control, 2007, 17(10/11): 1002-1033.
[20] WU Z H, XIE L B. Fault-tolerant dynamical consensus of double-integrator multi-agent systems with partial agents subject to synchronous self-sensing function failure [C]//2022 6th International Conference on Automation, Control and Robots. Shanghai: IEEE, 2022: 137-141.
[21] WU Z H, XIE L B. Fault-tolerant finite-time dynamical consensus of double-integrator multi-agent systems with partial agents subject to synchronous self-sensing function failure [J]. Chinese Physics B, 2022, 31(12): 128902.
[22] CHEN C, LEWIS F L, XIE S L, et al. Resilient adaptive and H ∞ controls of multi-agent systems under sensor and actuator faults [J]. Automatica, 2019, 102: 19-26.
[23] YAN B, WU C F, SHI P. Formation consensus for discrete-time heterogeneous multi-agent systems with link failures and actuator/sensor faults [J]. Journal of the Franklin Institute, 2019, 356(12): 6547-6570.
[24] SUN Y R, XIA Y X, ZHANG J, et al. Adaptive faulttolerant output regulation of linear multi-agent systems with sensor faults [J]. IEEE Access, 2020, 8: 159440-159448.
[25] CAO L, LI H Y, DONG G W, et al. Event-triggered control for multiagent systems with sensor faults and input saturation [J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021, 51(6): 3855-3866.
[26] DONG G W, LI X M, YAO D Y, et al. Command filtered fixed-time control for a class of multi-agent systems with sensor faults [J]. International Journal of Robust and Nonlinear Control, 2021, 31(18): 9588-9603.
[27] SUNDARAM S, HADJICOSTIS C N. Distributed function calculation and consensus using linear iterative strategies [J]. IEEE Journal on Selected Areas in Communications, 2008, 26(4): 650-660.
[28] SUNDARAM S, HADJICOSTIS C N. Distributed function calculation via linear iterative strategies in the presence of malicious agents [J]. IEEE Transactions on Automatic Control, 2011, 56(7): 1495-1508.
[29] PASQUALETTI F, BICCHI A, BULLO F. Consensus computation in unreliable networks: A system theoretic approach [J]. IEEE Transactions on Automatic Control, 2012, 57(1): 90-104.
[30] WU Y M, HE X X, LIU S, et al. Consensus of discretetime multi-agent systems with adversaries and time delays [J]. International Journal of General Systems, 2014, 43(3/4): 402-411.
[31] JIN Z P, MURRAY R M. Multi-hop relay protocols for fast consensus seeking [C]//Proceedings of the 45th IEEE Conference on Decision and Control. San Diego: IEEE, 2006: 1001-1006.
[32] YUAN D M, XU S Y, ZHAO H Y, et al. Accelerating distributed average consensus by exploring the information of second-order neighbors [J]. Physics Letters A, 2010, 374(24): 2438-2445.
[33] LU J, TANG C Y. Controlled hopwise averaging and its convergence rate [J]. IEEE Transactions on Automatic Control, 2012, 57(4): 1005-1012.
[34] RONG L N, XU S Y, ZHANG B Y, et al. Accelerating average consensus by using the information of secondorder neighbours with communication delays [J]. International Journal of Systems Science, 2013, 44(6): 1181-1188.
[35] PAN H, NIAN X H, GUO L. Second-order consensus in multi-agent systems based on second-order neighbours’information [J]. International Journal of Systems Science, 2014, 45(5): 902-914.
Outlines

/