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Distributed sensor fault diagnosis for a formation system with unknown constant time delays

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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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References

  1. Oh K K, Park M C, Ahn H S. A survey of multi-agent formation control. Automatica, 2015, 53: 424–440

    Article  MathSciNet  Google Scholar 

  2. Olfati-Saber R, Fax J A, Murray R M. Consensus and cooperation in networked multi-agent systems. Proc IEEE, 2007, 95: 215–233

    Article  Google Scholar 

  3. Ren W, Atkins E. Distributed multi-vehicle coordinated controlvia local information exchange. Int J Robust Nonlin Control, 2007, 17: 1002–1033

    Article  Google Scholar 

  4. 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

    Google Scholar 

  5. 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

    Google Scholar 

  6. Fax J A, Murray R M. Information flow and cooperative control of vehicle formations. IEEE Trans Automat Contr, 2004, 49: 1465–1476

    Article  MathSciNet  Google Scholar 

  7. 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

    Article  MathSciNet  Google Scholar 

  8. 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

    Google Scholar 

  9. 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

    Article  Google Scholar 

  10. 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

    MATH  Google Scholar 

  11. Nagy M, Ákos Z, Biro D, et al. Hierarchical group dynamics in pigeon flocks. Nature, 2010, 464: 890–893

    Article  Google Scholar 

  12. 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

    Article  Google Scholar 

  13. 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

    Article  MathSciNet  Google Scholar 

  14. Papachristodoulou A, Jadbabaie A, Münz U. Effects of delay in multi-agent consensus and oscillator synchronization. IEEE Trans Automat Contr, 2010, 55: 1471–1477

    Article  MathSciNet  Google Scholar 

  15. Abdessameud A, Tayebi A. Formation control of VTOL unmanned aerial vehicles with communication delays. Automatica, 2011, 47: 2383–2394

    Article  MathSciNet  Google Scholar 

  16. 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

    Article  MathSciNet  Google Scholar 

  17. 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

    Article  MathSciNet  Google Scholar 

  18. Münz U, Papachristodoulou A, Allgöwer F. Delay robustness in consensus problems. Automatica, 2010, 46: 1252–1265

    Article  MathSciNet  Google Scholar 

  19. Xu J J, Zhang H S, Xie L H. Input delay margin for consensusability of multi-agent systems. Automatica, 2013, 49: 1816–1820

    Article  MathSciNet  Google Scholar 

  20. 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

    Article  Google Scholar 

  21. Daigle M J, Koutsoukos X D, Biswas G. Distributed diagnosis in formations of mobile robots. IEEE Trans Robot, 2007, 23: 353–369

    Article  Google Scholar 

  22. Qin L G, He X, Zhou D H. A survey of fault diagnosis for swarm systems. Syst Sci Control Eng, 2014, 2: 13–23

    Article  Google Scholar 

  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

    MathSciNet  MATH  Google Scholar 

  24. 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

    Article  Google Scholar 

  25. 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

    Google Scholar 

  26. Meskin N, Khorasani K. Actuator fault detection and isolation for a network of unmanned vehicles. IEEE Trans Automat Contr, 2009, 54: 835–840

    Article  MathSciNet  Google Scholar 

  27. 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

    Article  Google Scholar 

  28. 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

    Article  Google Scholar 

  29. Shames I, Teixeira A M, Sandberg H, et al. Distributed fault detection for interconnected second-order systems. Automatica, 2011, 47: 2757–2764

    Article  MathSciNet  Google Scholar 

  30. 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

    Article  Google Scholar 

  31. 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

    Article  MathSciNet  Google Scholar 

  32. 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

    Article  MathSciNet  Google Scholar 

  33. 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

    Article  Google Scholar 

  34. Chen J, Patton R J. Robust Model-Based Fault Diagnosis for Dynamic. New York: Springer Science & Business Media, 1999. 51–54

    Book  Google Scholar 

  35. Ding S X. Model-Based Fault Diagnosis Techniques: Design Schemes, Algorithms, and Tools. London: Springer-Verlag, 2008. 286–312

    Google Scholar 

  36. Hou M, Muller P C. Design of observers for linear systems with unknown inputs. IEEE Trans Automat Contr, 1992, 37: 871–875

    Article  MathSciNet  Google Scholar 

  37. 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

    Article  Google Scholar 

  38. 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

    Article  Google Scholar 

Download references

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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Authors and Affiliations

  1. College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, 266590, China

    Donghua Zhou

  2. Department of Automation, TNList, Tsinghua University, Beijing, 100084, China

    Donghua Zhou, Liguo Qin, Xiao He, Rui Yan & Ruiliang Deng

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  1. Donghua Zhou
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  2. Liguo Qin
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  3. Xiao He
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  4. Rui Yan
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  5. Ruiliang Deng
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Correspondence to Donghua Zhou.

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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

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