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Intelligent scheduling and optimisation for resource-constrained networks

Intelligent scheduling and optimisation for resource-constrained networks

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In control network with resources constraints, there is an unavoidable tradeoff between the quality of control (QoC) and requirement of bandwidth (RoB) in order to optimise the performance of control system. To address the impact of this contradiction, two intelligent and optimal scheduling strategies, which are respectively based on fuzzy logic control technique and neural network, are employed by a bandwidth scheduler according to corresponding dynamic resource allocation approach. In order to guarantee the system's stability, the lower and upper bounds of the assignable bandwidth are evaluated in terms of linear matrix inequalities and the resource constraints, respectively. In addition, the normalisable criterions of QoC and RoB are also defined, which can estimate the performance of the whole networked control systems. Preliminary simulations show that the proposed strategies can save significant bandwidth and simultaneously improve overall control performance in comparison with the fixed bandwidth allocation and optimal bandwidth allocation in the literatures.

References

    1. 1)
    2. 2)
    3. 3)
      • Li, Y., Fang, H.: `Control methodologies of large delays in networked control systems', Proc. Fifth Int. Conf. on Control and Automation, 2005, Budapest, Hungary, p. 1225–1230.
    4. 4)
    5. 5)
    6. 6)
    7. 7)
    8. 8)
    9. 9)
    10. 10)
    11. 11)
    12. 12)
    13. 13)
    14. 14)
    15. 15)
    16. 16)
    17. 17)
    18. 18)
    19. 19)
      • Zhang, W.: `Stability analysis of networked control systems', 2001, PhD, Case Western Reserve University, USA.
    20. 20)
      • Branicky, M.S., Phillips, S.M., Zhang, W.: `Scheduling and feedback co-design for networked control systems', Proc. IEEE Conf. on Decision and Control, 2002, Las Vegas, Nevada, p. 1211–1217.
    21. 21)
      • Ren, X.D., Li, S.B., Wang, Z., Yuan, M.Z., Sun, Y.X.: `A QoS management scheme for paralleled networked control systems with CAN bus', Proc. 29th Annual Conf. on IEEE Industrial Electronics Society, 2003, Virginia, USA, p. 842–847.
    22. 22)
      • Velasco, M., Fuertes, J.M., Lin, C.X., Marti, P., Brandt, S.: `A control approach to bandwidth management in networked control systems', Proc. 30th Annual Conf. on IEEE Industrial Electronics Society, 2004, Busan, Korea, p. 2343–2348.
    23. 23)
      • Velasco, M., Marti, P., Frigola, M.: `Bandwidth management for distributed control of highly articulated robots', Proc. 2005 IEEE Int. Conf. on Robotics and Automation, 2005, Barcelona, Spain, p. 265–270.
    24. 24)
      • Kim, Y.H., Park, H.S., Kwon, W.H.: `A scheduling method for network-based control systems', Proc. 17th ACC, 1998, Philadelphia, USA, p. 718–722.
    25. 25)
    26. 26)
      • Z.X. Li , W.L. Wang , B.C. Lei , H.Y. Chen . An approach to bandwidth management based on fuzzy logic. Eng. Sci. , 7 , 104 - 111
    27. 27)
      • H.Q. Li , B.W. Wan . A new global optimization algorithm for training feedforward neural networks and its application. Syst. Eng. Theory Pract. , 8 , 42 - 47
    28. 28)
    29. 29)
      • Marti, P., Lin, C.X., Brandt, S.A., Velasco, M., Fuertes, J.M.: `Optimal state feedback based resource allocation for resource-constrained control tasks', Proc. 25th Int. Real-Time Systems Symp., 2004, Lisbon, Portugal, p. 161–172.
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