Advertisement

A New Dynamic Scheduling Method for Networked Control Systems

  • Feng Du
  • Xiaoyu Zhang
  • Zhi Lei
  • Jia Ren
  • Cheng Guo
  • Jinyu Li
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 208)

Abstract

For networked control systems with limited network bandwidth, the conflict will reduce control performance of the system. This paper puts forward a new dynamic scheduling. This method guarantees the quality of control (output is into its steady state value: −5 to 5 % range) as the goal, and set deadband in the controller. It bases on the two parameters: error and error change rate adaptive to adjust the network load. Lastly, do the simulation based on CSMA/CD network simulation. The results verify the proposed method can improve the utilization rate of the network bandwidth, to improve the quality of control performance, enhance the stability of the system.

Keywords

Networked control systems Deadband scheduling Dynamic scheduling 

Notes

Acknowledgments

This work is partially supported by National Natural Science Foundation of China, as well as the Research Project of Hainan University under Grant No. hd09xm85 and kyqd-1214.

References

  1. 1.
    Li ZX (2008) Networked control system of intelligent scheduling and its optimization. Zhejiang university Ph.D. thesis 12(32):9–10Google Scholar
  2. 2.
    Cui XZ, Han P (2008) A mixed scheduling algorithm for thermal process network control systems. In: Proceedings of the 27th Chinese control conference, vol 31, pp 207–210Google Scholar
  3. 3.
    Wang BR, Shi DG (2007) Study on dynamic priority scheduling based on fuzzy logic for networked control systems. In: Proceedings of the IEEE international conference on automation and logistics, vol 8, pp 1182–1186Google Scholar
  4. 4.
    Zhang XF, Wang ZJ (2009) An immune-genetic algorithm-based scheduling optimization in a networked control system. Glob Congr Intell Syst 4:32–35CrossRefGoogle Scholar
  5. 5.
    Zhang XF, Li GH (2009) Real-time elastic network scheduling of networked control systems. In: The 1st international conference on information science and engineering, vol 22, pp 5017–5021 Google Scholar
  6. 6.
    Xu LJ (2010) A hybrid quantum clone evolutionary algorithm-based scheduling optimization in a networked learning control system. Control Decis Conf 12(9):3632–3637Google Scholar
  7. 7.
    Li Z (2010) Brief paper intelligent scheduling and optimization for resource constrained networks. Control Theor Appl 23:2982–2992CrossRefGoogle Scholar
  8. 8.
    Branicky MS, Phillips SM, Zhang W (2002) Scheduling and feedback co-design for networked control systems. In: Proceedings of IEEE conference on decision and control, vol 3(2), pp 1211–1217Google Scholar
  9. 9.
    Liu CL, Layland J (1973) Scheduling algorithms for multi programming in a hard real-time environment. J Assoc Comput Mach 20(1):46–61MathSciNetMATHCrossRefGoogle Scholar
  10. 10.
    Walsh GC, Ye H (2001) Scheduling of networked control systems. IEEE Control Syst Mag 21(1):57–65CrossRefGoogle Scholar
  11. 11.
    Otaneg P, Moyne J, Tilbury D (2002) Using deadbands to reduce in networked control systems. In: Proceedings of the American control conference anchorage: IEEE press, pp 46615–619Google Scholar
  12. 12.
    Tang XM (2007) Networked control system dynamic deadband feedback scheduling. J S Chin Univ Technol 6(5):716–721Google Scholar
  13. 13.
    Zhang P (2009) Based on switch ethernet network control system of scheduling research. Nanjing university of technology master thesis, vol 68(9), pp 35-38 Google Scholar

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Feng Du
    • 1
  • Xiaoyu Zhang
    • 1
  • Zhi Lei
    • 1
  • Jia Ren
    • 1
  • Cheng Guo
    • 1
  • Jinyu Li
    • 1
  1. 1.University of HainanHaikouChina

Personalised recommendations