Control Theory and Technology

, Volume 16, Issue 2, pp 93–109 | Cite as

Distributed output feedback stationary consensus of multi-vehicle systems in unknown environments

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Abstract

In the traditional distributed consensus of multi-vehicle systems, vehicles agree on velocity and position using limited information exchange in their local neighborhoods. Recently, distributed leaderless stationary consensus has been proposed in which vehicles agree on a position and come to a stop. The proposed stationary consensus schemes are based on all vehicles’ access to their own absolute velocity measurements, and they do not guarantee this collective behavior in the presence of disturbances that persistently excite vehicles’ dynamics. On the other hand, traditional distributed disturbance rejection leaderless consensus algorithms may result in an uncontrolled increase in the speed of multi-vehicle system. In this paper, we propose a dynamic relative-output feedback leaderless stationary algorithm in which only a few vehicles have access to their absolute measurements. We systematically design the distributed algorithm by transforming this problem into a static feedback robust control design challenge for the low-order modified model of vehicles with fictitious modeling uncertainties. We further propose dynamic leader-follower stationary consensus algorithms for multi-vehicle systems with a static leader, and find closed-form solutions for the consensus gains based on design matrices and communication graph topology. Finally, we verify the feasibility of these ideas through simulation studies.

Keywords

Multi-vehicle system distributed control stationary consensus disturbance accommodation 

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References

  1. [1]
    D. Cruz, J. McClintock, B. Perteet, et al. Decentralized cooperative control. IEEE Control Systems Magazine, 2007, 27(3): 58–78.MathSciNetCrossRefGoogle Scholar
  2. [2]
    L. Bento, R. Parafita, U. Nunes. Inter-vehicle sensor fusion for accurate vehicle localization supported by V2V and V2I communications. International Conference on Intelligent Transportation Systems, Anchorage: IEEE, 2012: 907–914.Google Scholar
  3. [3]
    R. Langari. Autonomous vehicles: a tutorial on research and development issues. American Control Conference, Seattle: IEEE, 2017: 4018–4022.Google Scholar
  4. [4]
    P. Seiler, A. Pant, J. Hedrick. Disturbance propagation in vehicle strings. IEEE Transactions on Automatic Control, 2004, 49(10): 1835–1842.MathSciNetCrossRefMATHGoogle Scholar
  5. [5]
    Y. Zhao, P. Minero, V. Gupta. On disturbance propagation in leader-follower systems with limited leader information. Automatica, 2014, 50(2): 591–598.MathSciNetCrossRefMATHGoogle Scholar
  6. [6]
    W. Ren, E. Atkins. Distributed multi-vehicle coordinated control via local information exchange. International Journal of Robust and Nonlinear Control, 2007, 17(10/11): 1002–1033.MathSciNetCrossRefMATHGoogle Scholar
  7. [7]
    J. Lawton, R. Beard, B. Young. A decentralized approach to formation maneuvers. IEEE Transactions on Robotics and Automation, 2003, 19(6): 933–941.CrossRefGoogle Scholar
  8. [8]
    R. Xue, G. Cai. Formation flight control of multi-UAV system with communication constraints. Journal of Aerospace Technology Management, 2016, 8(2): 203–210.CrossRefGoogle Scholar
  9. [9]
    A. Jadbabaie, J. Lin, S. Morse. Coordination of groups of mobile autonomous agents using nearest neighbor rules. IEEE Transactions on Automatic Control, 2003, 48(6): 988–1001.MathSciNetCrossRefMATHGoogle Scholar
  10. [10]
    T. Yucelen, E. Johnson. Control of multi-vehicle systems in the presence of uncertain dynamics. International Journal of Control, 2013, 86(9): 1540–1553.MathSciNetCrossRefMATHGoogle Scholar
  11. [11]
    W. Ren, R. Beard, E. Atkins. A survey of consensus problems in multi-agent coordination. American Control Conference, Portland: IEEE, 2005: 1859–1864.Google Scholar
  12. [12]
    W. Yu, G. Chen, C. Ming. Some necessary and sufficient conditions for second-order consensus in multi-agent systems. Automatica, 2010, 46(6): 1089–1095.MathSciNetCrossRefMATHGoogle Scholar
  13. [13]
    N. Huang, Z. Duan, G. Chen. Some necessary and sufficient conditions for consensus of second-order multi-agent systems with sampled position data. Automatica, 2016, 63: 148–155.MathSciNetCrossRefMATHGoogle Scholar
  14. [14]
    C.-L. Liu, F. Liu. Stationary consensus of heterogeneous multiagent systems with bounded communication delays. Automatica, 2011, 47(9): 2130–2133.MathSciNetCrossRefMATHGoogle Scholar
  15. [15]
    J. Qin, C. Yu, S. Hirche. Stationary consensus of asynchronous discrete-time second-order multi-agent systems under switching topology. IEEE Transactions on Industrial Informatics, 2012, 8(4): 986–994.CrossRefGoogle Scholar
  16. [16]
    Y. Feng, S. Xu, F. Lewis, B. Zhang. Consensus of heterogeneous first- and second-order multi-agent systems with directed communication topologies. International Journal of Robust and Nonlinear Control, 2015, 25(3): 362–375.MathSciNetCrossRefMATHGoogle Scholar
  17. [17]
    Y. Pei, J. Sun. Necessary and sufficient conditions of stationary average consensus for second-order multi-agent systems. International Journal of Systems Science, 2016, 47(15): 3631–3636.MathSciNetCrossRefMATHGoogle Scholar
  18. [18]
    C. Gohrle, A. Schindler, A. Wagner, et al. Road profile estimation and preview control for low-bandwidth active suspension systems. IEEE/ASME Transactions on Mechatronics, 2015, 20(5): 2299–2310.CrossRefGoogle Scholar
  19. [19]
    I. Youn, M. Khan, N. Uddin, et al. Road disturbance estimation for the optimal preview control of an active suspension system based on tracked vehicle model. International Journal of Automotive Technology, 2017, 18(2): 307–316.CrossRefGoogle Scholar
  20. [20]
    A. Cho, S. Kim, C. Kee. Wind estimation and airspeed calibration using a UAV with a single-antenna GPS receiver and pitot tube. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47(1): 109–117.CrossRefGoogle Scholar
  21. [21]
    B. Arain, F. Kendoul. Real-time wind speed estimation and compensation for improved flight. IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(2): 1599–1606.CrossRefGoogle Scholar
  22. [22]
    H. Shen, N. Li, H. Griffiths, et al. Tracking control of a small unmanned air vehicle with airflow awareness. American Control Conference, Seattle: IEEE, 2017: 4153–4158.Google Scholar
  23. [23]
    T. Yucelen, M. Egerstedt. Control of multiagent systems under persistent disturbance. American Control Conference, Montreal: IEEE, 2012: 5264–5269.Google Scholar
  24. [24]
    M. Anderson, D. Dimarogonas, H. Sandberg, et al. Distributed control of networked dynamical systems: static feedback integral action and consensus. IEEE Transactions on Automatic Control, 2014, 59(7): 1750–1764.MathSciNetCrossRefMATHGoogle Scholar
  25. [25]
    W. Cao, W. Zhang, W. Ren. Leader-follower consensus of linear multi-agent systems with unknown external disturbance. Systems & Control Letters, 2015, 82: 64–70.MathSciNetCrossRefMATHGoogle Scholar
  26. [26]
    V. Rezaei, M. Stefanovic. Distributed leaderless and leaderfollower consensus of linear multiagent systems under persistent disturbances. Mediterranean Conference on Control and Automation, Athens, Greece: IEEE, 2016: 386–391.Google Scholar
  27. [27]
    R. Horn, C. Johnson, Matrix Analysis. Cambridge: Cambridge University Press, 2013.MATHGoogle Scholar
  28. [28]
    M. Mesbahi, M. Egerstedt. Graph Theoretic Methods in Multiagent Networks. Princeton: Princeton University Press, 2010.CrossRefMATHGoogle Scholar
  29. [29]
    W. Ni, D. Cheng. Leader-following consensus of multi-agent systems under fixed and switching topologies. Systems & Control Letters, 2010, 59(3/4): 209–217.MathSciNetCrossRefMATHGoogle Scholar
  30. [30]
    S.-E. Tuna. LQR-based coupling gain for synchronization of linear systems. arXiv, 2008: arXiv:0801.3390.Google Scholar
  31. [31]
    H. Zhang, F. Lewis, A. Das. Optimal design for synchronization of cooperative systems: state feedback, observer and output feedback. IEEE Transactions on Automatic Control, 2011, 56(8): 1948–1952.MathSciNetCrossRefMATHGoogle Scholar
  32. [32]
    Z. Li, Z. Duan, G. Chen, et al. Consensus of multiagent systems and synchronization of complex networks: a unified viewpoint. IEEE Transactions on Circuits and Systems I: Regular Papers, 2010, 57(1): 213–224.MathSciNetCrossRefGoogle Scholar
  33. [33]
    V. Rezaei, M. Stefanovic. Distributed decoupling of partiallyunknown interconnected linear multiagent systems: state and output feedback approaches. IFAC-PapersOnLine, 2017, 50(1): 1766–1771.CrossRefGoogle Scholar
  34. [34]
    D. Kirk. Optimal Control Theory: An Introduction. Englewood Cliffs: Prentice Hall, 1970.Google Scholar
  35. [35]
    H. Khalil. Nonlinear Control. Englewood Cliffs: Prentice Hall, 2014.Google Scholar

Copyright information

© South China University of Technology, Academy of Mathematics and Systems Science, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringUniversity of DenverDenverU.S.A.

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