Abstract
In this paper, a distributed velocity sensor fault diagnosis scheme is presented for a formation of a second-order multi-agent system with unknown constant communication time delays. An existing distributed proportion-derivation (DPD) formation control law is adopted and a delay-independent condition is proposed to guarantee the asymptotical formation stability of the formation system based on the Nyquist stability criterion. Then a distributed fault diagnosis scheme is developed. In each agent, a distributed fault detection residual generator (DFDRG) and a bank of distributed fault isolation residual generators (DFIRGs) are designed based on the closed-loop model of the whole system. Each DFIRG is built up on the basis of a reduced-order unknown input observer (UIO) which is robust to the fault of one neighboring agent. According to the robust relationship between DFIRGs and faults, distributed fault isolation can be achieved. Conditions are presented to guarantee that each agent is able to diagnose faults of itself and its neighbors despite the disturbance of time delays. Finally, outdoor experimental results illustrate the effectiveness of the proposed schemes.
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Oh K K, Park M C, Ahn H S. A survey of multi-agent formation control. Automatica, 2015, 53: 424–440
Olfati-Saber R, Fax J A, Murray R M. Consensus and cooperation in networked multi-agent systems. Proc IEEE, 2007, 95: 215–233
Ren W, Atkins E. Distributed multi-vehicle coordinated controlvia local information exchange. Int J Robust Nonlin Control, 2007, 17: 1002–1033
Chen J, Gan MG, Huang J, et al. Formation control of multiple Euler-Lagrange systems via null-space-based behavioral control. Sci China Inf Sci, 2016, 59: 010202
Zhao D Y, Zhao Y R, Cui B H, et al. Sychronized control for mechanical systems. J Shandong Univ Sci Technol, 2013, 32: 1–6
Fax J A, Murray R M. Information flow and cooperative control of vehicle formations. IEEE Trans Automat Contr, 2004, 49: 1465–1476
Wang W, Huang J S, Wen C Y, et al. Distributed adaptive control for consensus tracking with application to formation control of nonholonomic mobile robots. Automatica, 2014, 50: 1254–1263
Zhao G, Zhao D Y, Zhao Y R, et al. Leader-follower based distributed synchronous control and simulation for multimanipulators system. J Shandong Univ Sci Technol, 2014, 33: 99–104
Campa G, Gu Y, Seanor B, et al. Design and flight-testing of non-linear formation control laws. Control Eng Practice, 2007, 15: 1077–1092
Shen D B, Sun Z D, Sun W J. Leader-follower formation control without leader’s velocity information. Sci China Inf Sci, 2014, 57: 092202
Nagy M, Ákos Z, Biro D, et al. Hierarchical group dynamics in pigeon flocks. Nature, 2010, 464: 890–893
Kozyreff G, Vladimirov A G, Mandel P. Global coupling with time delay in an array of semiconductor lasers. Phys Rev Lett, 2000, 85: 3809–3812
Lin P, Jia Y M, Li L. Distributed robust consensus control in directed networks of agents with time-delay. Syst Control Lett, 2008, 57: 643–653
Papachristodoulou A, Jadbabaie A, Münz U. Effects of delay in multi-agent consensus and oscillator synchronization. IEEE Trans Automat Contr, 2010, 55: 1471–1477
Abdessameud A, Tayebi A. Formation control of VTOL unmanned aerial vehicles with communication delays. Automatica, 2011, 47: 2383–2394
Olfati-Saber R, Murray R M. Consensus problems in networks of agents with switching topology and time-delays. IEEE Trans Automat Contr, 2004, 49: 1520–1533
Tian Y P, Liu C L. Consensus of multi-agent systems with diverse input and communication delays. IEEE Trans Automat Contr, 2008, 53: 2122–2128
Münz U, Papachristodoulou A, Allgöwer F. Delay robustness in consensus problems. Automatica, 2010, 46: 1252–1265
Xu J J, Zhang H S, Xie L H. Input delay margin for consensusability of multi-agent systems. Automatica, 2013, 49: 1816–1820
Dong X W, Yu B C, Shi Z Y, et al. Time-varying formation control for unmanned aerial vehicles: theories and applications. IEEE Trans Contr Syst Technol, 2015, 23: 340–348
Daigle M J, Koutsoukos X D, Biswas G. Distributed diagnosis in formations of mobile robots. IEEE Trans Robot, 2007, 23: 353–369
Qin L G, He X, Zhou D H. A survey of fault diagnosis for swarm systems. Syst Sci Control Eng, 2014, 2: 13–23
Micalizio R, Torasso P, Torta G. On-line monitoring and diagnosis of a team of service robots: a model-based approach. AI Commun, 2006, 19: 313–340
Léchevin N, Rabbath C A. Decentralized detection of a class of non-abrupt faults with application to formations of unmanned airships. IEEE Trans Contr Syst Technol, 2009, 17: 484–493
Zhang K, Jiang B, Shi P. Adjustable parameter-based distributed fault estimation observer design for multiagent systems with directed graphs. IEEE Trans Cybern, 2017, 47: 306–314
Meskin N, Khorasani K. Actuator fault detection and isolation for a network of unmanned vehicles. IEEE Trans Automat Contr, 2009, 54: 835–840
Davoodi M R, Khorasani K, Talebi H A, et al. Distributed fault detection and isolation filter design for a network of heterogeneous multiagent systems. IEEE Trans Contr Syst Technol, 2014, 22: 1061–1069
Arrichiello F, Marino A, Pierri F. Observer-based decentralized fault detection and isolation strategy for networked multirobot systems. IEEE Trans Contr Syst Technol, 2015, 23: 1465–1476
Shames I, Teixeira A M, Sandberg H, et al. Distributed fault detection for interconnected second-order systems. Automatica, 2011, 47: 2757–2764
Teixeira A, Shames I, Sandberg H, et al. Distributed fault detection and isolation resilient to network model uncertainties.. IEEE Trans Cybern, 2014, 44: 2024–2037
Shi J T, He X, Wang Z D, et al. Distributed fault detection for a class of second-order multi-agent systems: an optimal robust observer approach. IET Contr Theor Appl, 2014, 8: 1032–1044
Gao X W, Liu X H, Han J. Reduced order unknown input observer based distributed fault detection for multi-agent systems. J Franklin Institute, 2017, 354: 1464–1483
Qin L G, He X, Zhou D H. Distributed proportion-integration-derivation formation control for second-order multi-agent systems with communication time delays. Neurocomputing, 2017, 267: 271–282
Chen J, Patton R J. Robust Model-Based Fault Diagnosis for Dynamic. New York: Springer Science & Business Media, 1999. 51–54
Ding S X. Model-Based Fault Diagnosis Techniques: Design Schemes, Algorithms, and Tools. London: Springer-Verlag, 2008. 286–312
Hou M, Muller P C. Design of observers for linear systems with unknown inputs. IEEE Trans Automat Contr, 1992, 37: 871–875
Zhang Y M, Chamseddine A, Rabbath C A, et al. Development of advanced FDD and FTC techniques with application to an unmanned quadrotor helicopter testbed. J Franklin Institute, 2013, 350: 2396–2422
Qin L G, He X, Yan R, et al. Active fault-tolerant control for a quadrotor with sensor faults. J Intell Robot Syst, 2017, 88: 449–467
Acknowledgements
This work was supported by National Natural Science Foundation of China (Grant Nos. 61210012, 61490701, 61522309, 61473163), Tsinghua University Initiative Scientific Research Program, and Research Fund for the Taishan Scholar Project of Shandong Province of China.
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Zhou, D., Qin, L., He, X. et al. Distributed sensor fault diagnosis for a formation system with unknown constant time delays. Sci. China Inf. Sci. 61, 112205 (2018). https://doi.org/10.1007/s11432-017-9309-3
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DOI: https://doi.org/10.1007/s11432-017-9309-3