Advertisement

Consensus Based Multi-Agent Control Algorithms

  • Miloš S. Stanković
  • Dušan M. Stipanović
  • Srdjan S. Stanković
Chapter

Abstract

Control of complex systems can be achieved via hierarchical multilayered agentbased structures benefiting from their inherent properties such as modularity, scalability, adaptability, flexibility and robustness. The agent-based structures consist of a number of simpler subsystems (or agents), each of which addresses in a coordinated manner a specific sub-objective or sub-task so as to attain the overall design objectives. The complexity of the behavior of such systems arises as a result of interactions between multiple agents and the environment in which they operate. More specifically, multi-agent control systems are fundamental parts of a wide range of safety-critical engineering systems, and are commonly found in aerospace, traffic control, chemical processes, power generation and distribution, flexible manufacturing, robotic system design and self-assembly structures. A multi-agent system can be considered as a loosely coupled network of problem-solver entities that work together to find answers to problems that are beyond the individual capabilities or knowledge of each entity, where local control law has to satisfy decentralized information structure constraints (see, e.g., [20]), and where no global system control (or supervision) is desired.

Keywords

Unmanned Aerial Vehicle Local Controller Feedback Gain Matrix Consensus Scheme Vector Lyapunov Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    B. Baran, E. Kaszkurewicz, and A. Bhaya, Parallel asynchronous team algorithms: convergence and performance analysis, IEEE Trans. Parallel Distrib. Syst. 7 (1996), 677–688CrossRefGoogle Scholar
  2. 2.
    D. P. Bertsekas and J. N. Tsitsiklis, Parallel and distributed computation: Numerical methods, Prentice-Hall, Englewood Cliffs, 1989MATHGoogle Scholar
  3. 3.
    V. D. Blondel, J. M. Hendrickx, A. Olshevsky, and J. N. Tsitsiklis, Convergence in multiagent coordination, consensus and flocking, Proc. IEEE Conf. Decision Contr., 2005Google Scholar
  4. 4.
    C. G. Cassandras and W. Li, Sensor networks and cooperative control, Eur. J. Contr. 11 (2005), 436–463CrossRefMathSciNetGoogle Scholar
  5. 5.
    X. B. Chen and S. S. Stanković, Decomposition and decentralized control of systems with multi-overlapping structure, Automatica 41 (2005), 1765–1772MATHCrossRefGoogle Scholar
  6. 6.
    A. Fax and R.M Murray, Information flow and cooperative control of vehicle formations, IEEE Trans. Automat. Contr. 49 (2004), 1465–1476CrossRefMathSciNetGoogle Scholar
  7. 7.
    H. Gharavi and S. Kumar (eds.), Proceedings of the IEEE: Special Isssue on Sensor Networks and Applications, vol. 91, August 2003Google Scholar
  8. 8.
    M. Ikeda and D. D. Šiljak, Decentralized control with overlapping information sets, J. Optim. Theory Applic. 34 (1981), 279–310MATHCrossRefGoogle Scholar
  9. 9.
    X. B. Chen and S. S. Stanković Overlapping decentralized control with input, state and output inclusion, Contr. Theory Adv. Technol. 2 (1986), 155–172MATHGoogle Scholar
  10. 10.
    M. Ikeda, D. D. Šiljak, and D.E. White, Decentralized control with overlapping information sets, J. Optim. Theory Applic. 34 (1981), 279–310MATHCrossRefGoogle Scholar
  11. 11.
    X. B. Chen and S. S. Stanković An inclusion principle for dynamic systems, IEEE Trans. Autom. Contr. 29 (1984), 244–249CrossRefGoogle Scholar
  12. 12.
    A. Jadbabaie, J. Lin, and A. Morse, Coordination of groups of mobile autonomous agents using nearest neighbor rules, IEEE Trans. Automat. Contr. 48 (2003), 988–1001CrossRefMathSciNetGoogle Scholar
  13. 13.
    Z. Lin, B. Francis, and M. Maggiore, Necessary and sufficient conditions for formation control of unicycles, IEEE Trans. Automat. Contr. 50 (2005), 121–127CrossRefMathSciNetGoogle Scholar
  14. 14.
    R. Olfati-Saber and R. Murray, Consensus problems in networks of agents with switching topology and time-delays, IEEE Trans. Automat. Contr. 49 (2004), 1520–1533CrossRefMathSciNetGoogle Scholar
  15. 15.
    W. Ren and E. Atkins, Distributed multi-vehicle coordinated control via local information exchange, Int. J. Robust Nonlinear Contr. 17 (2007), 1002–1033CrossRefMathSciNetGoogle Scholar
  16. 16.
    W. Ren, R. W. Beard, and E. M. Atkins, A survey of consensus problems in multi-agent coordination, Proceedings of American Control Conference, 2005, pp. 1859–1864Google Scholar
  17. 17.
    W. Ren, R. W. Beard, and D. B. Kingston, Multi-agent Kalman consensus with relative uncertainty, Proceedings of American Control Conference, 2005Google Scholar
  18. 18.
    W. Ren and R.W. Beard, Consensus seeking in multi-agent systems using dynamically changing interaction topologies, IEEE Trans. Autom. Contr. 50 (2005), 655–661CrossRefMathSciNetGoogle Scholar
  19. 19.
    D. D. Šiljak, Large scale dynamic systems: Stability and structure, North-Holland, New York 1978MATHGoogle Scholar
  20. 20.
    D. D. Šiljak, Decentralized control of complex systems, Academic, New York, 1991Google Scholar
  21. 21.
    R. S. Smith and F. Y. Hadaegh, Closed-loop dynamics of cooperative vehicle formations with parallel estimators and communication, IEEE Trans. Autom. Contr. 52 (2007), 1404–1414CrossRefMathSciNetGoogle Scholar
  22. 22.
    S. S. Stanković and D. D. Šiljak, Contractibility of overlapping decentralized control, Syst. Contr. Lett. 44 (2001), 189–199MATHCrossRefGoogle Scholar
  23. 23.
    S. S. Stanković and D. D. Šiljak, Stabilization of fixed modes in expansions of LTI systems, Syst. Contr. Lett. 57 (2008), 365–370MATHCrossRefGoogle Scholar
  24. 24.
    S. S. Stanković, M. S. Stanković, and D. M. Stipanović, Consensus based overlapping decentralized estimation with missing observations and communication faults, Automatica 45 (2009), 1397–1406MATHCrossRefGoogle Scholar
  25. 25.
    S. S. Stanković, M. S. Stanković, and D. M. Stipanović, Consensus based overlapping decentralized estimator, IEEE Trans. Autom. Contr. 54 (2009), 410–415CrossRefGoogle Scholar
  26. 26.
    S. S. Stanković, M. J. Stanojević, and D. D. Šiljak, Decentralized overlapping control of a platoon of vehicles, IEEE Trans. Contr. Syst. Technol. 8 (2000), 816–832CrossRefGoogle Scholar
  27. 27.
    S. S. Stanković, D. M. Stipanović, and M. S. Stanković, Decentralized overlapping tracking control of a formation of autonomous unmanned vehicles, Proceedings of American Control Conference, 2009Google Scholar
  28. 28.
    D. M. Stipanović, G. İnhalan, R. Teo, and C. Tomlin, Decentralized overlapping control of a formation of unmanned aerial vehicles, Automatica 40 (2004), 1285–1296MATHCrossRefGoogle Scholar
  29. 29.
    J. N. Tsitsiklis, Problems in decentralized decision making and computation, Ph.D. thesis, Dep. Electrical Eng. Comput. Sci., M.I.T., Cambridge, MA, 1984Google Scholar
  30. 30.
    J. N. Tsitsiklis, D. P. Bertsekas, and M. Athans, Distributed asynchronous deterministic and stochastic gradient optimization algorithms, IEEE Trans. Autom. Contr. 31 (1986), 803–812MATHCrossRefMathSciNetGoogle Scholar
  31. 31.
    P. Yang, R.A. Freeman, and K.M. Lynch, Multi-agent coordination by decentralized estimation and control, IEEE Trans. Autom. Contr. 53 (2008), 2480–2496CrossRefMathSciNetGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Miloš S. Stanković
    • 1
  • Dušan M. Stipanović
    • 2
  • Srdjan S. Stanković
    • 3
  1. 1.ACCESS Linnaeus Center, School of Electrical EngineeringRoyal Institute of TechnologyStockholmSweden
  2. 2.Department of Industrial and Enterprise Systems Engineering and the Coordinated Science LaboratoryUniversity of Illinois at Urbana-ChampaignIllinoisUSA
  3. 3.School of Electrical EngineeringUniversity of BelgradeSerbiaEurope

Personalised recommendations