Skip to main content

Neural Feedback Scheduling

  • Chapter
Control and Scheduling Codesign

Part of the book series: Advanced Topics in Science and Technology in China ((ATSTC))

  • 581 Accesses

Abstract

Optimal feedback scheduling schemes are usually too computationally expensive to be used online, though they are in principle capable of maximizing the overall QoC of Real-Time Control Systems. With the goal of optimizing the overall QoC of multitasking embedded control systems, the problem of optimal feedback scheduling is explicitly formulated, and relevant mathematical solutions are discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 159.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. K.E. Årzén, B. Bernhardsson, J. Eker, A. Cervin, P. Persson, K. Nilsson, L. Sha. Integrated Control and Scheduling. Research Report, ISSN 0820-5316, Dept. Automatic Control, Lund Institute of Technology, 1999.

    Google Scholar 

  2. K.E. Årzén, A. Cervin, D. Henriksson. Resource-Constrained Embedded Control Systems: Possibilities and Research Issues. Proc. of Codesign of Embedded Real-Time Systems Workshop, Porto, Portugal, 2003.

    Google Scholar 

  3. K.J. Åström, B. Wittenmark. Computer Controlled Systems: Theory and Design, 3rd Edition. Prentice Hall, 1997.

    Google Scholar 

  4. S. Boyd, L. Vandenberghe. Convex Optimization, Cambridge Press, 2004.

    Google Scholar 

  5. M.S. Branicky, S.M. Philips, W. Zhang. Scheduling and Feedback Codesign for Networked Control Systems. Proc. 41st IEEE CDC, Las Vegas, pp.1211–1217, 2002.

    Google Scholar 

  6. R. Castañé, P. Marti, M. Velasco, A. Cervin, D. Henriksson. Resource Management for Control Tasks Based on the Transient Dynamics of Closed Loop Systems. 18th Euromicro Conf. on Real-Time Systems, Dresden, Germany, 2006.

    Google Scholar 

  7. A. Cervin, J. Eker, B. Bernhardsson, K.E. Årzén. Feedback-Feedforward Scheduling of Control Tasks. Real-Time Systems, Vol. 23, No.l, pp.25–53, 2002.

    Article  MATH  Google Scholar 

  8. A. Cervin, P. Alriksson. Optimal On-line Scheduling of Multiple Control Tasks: A Case Study. Proc. of the 18th Euromicro Conf. on Real-Time Systems, Dresden, Germany, 2006.

    Google Scholar 

  9. J. Eker, P. Hagander, K.E. Årzén. A Feedback Scheduler for Real-Time Controller Tasks. Control Engineering Practice, Vol. 8, No.l2, pp.1369–1378, 2000.

    Article  Google Scholar 

  10. R. Fletcher. Practical Methods of Optimization. John Wiley & Sons, 1987.

    Google Scholar 

  11. J. He, H. Zhang, Y. Jing. An Integrated Control and Scheduling Optimization Method of Networked Control Systems. Journal of Electronic Science and Technology of China, No.02, pp.57–60, 2004.

    Google Scholar 

  12. D. Henriksson, A. Cervin. Optimal On-line Sampling Period Assignment for Real-Time Control Tasks Based on Plant State Information. Proc. of the 44th IEEE Conf. on Decision and Control and European Control Conf. ECC, Seville, Spain, 2005.

    Google Scholar 

  13. H. Jin, H. Wang, H.A. Wang, G. Dai. Optimization Design of Controller Periods Using Evolution Strategy. CIS’05, Lecture Notes in Artificial Intelligence, Vol. 3801, pp.1100–1105, 2005.

    Google Scholar 

  14. B. Kook Kim. Task Scheduling with Feedback Latency for Real-Time Control Systems. 5th Int. Conf. on Real-Time Computing Systems and Applications (RTCSA), Hiroshima, Japan, pp.37–41, 1998.

    Google Scholar 

  15. P. Martí. Analysis and Design of Real-Time Control Systems with Varying Control Timing Constraints. Ph.D Thesis, Technical University of Catalonia, 2002.

    Google Scholar 

  16. D. Seto, J.P. Lehoczky, L. Sha, K.G. Shin. On Task Schedulability in Real-Time Control Systems. Proc. 17th IEEE RTSS, Washington, DC, pp.13–21, 1996.

    Google Scholar 

  17. G. Su, F. Deng. On the Improving Backpropagation Algorithms of the Neural Networks Based on MATLAB Language: A Review. Chinese Bulletin of Science and Technology, Vol. 19, No.2, pp. 130–135, 2003.

    Google Scholar 

  18. Z. Sun, Z. Zhang, Z. Deng. Theory and Technology of Intelligent Control. Beijing: Tsinghua University Press, 1997.

    Google Scholar 

  19. W. Sun, C. Xu, D. Zhu. Optimization Methods. Beijing: Higher Education Press, 2004.

    Google Scholar 

  20. Y.X. Sun, J. Chu. Industrial Process Control Technology. Beijing: Chemical Industry Press, 2006.

    Google Scholar 

  21. F. Xia, Y.X. Sun. Neural Network Based Feedback Scheduling of Multitasking Control Systems. Lecture Notes in Artificial Intelligence, Vol. 3682, pp.193–199, 2005.

    Google Scholar 

  22. F. Xia, Y.C. Tian, Y.X. Sun, J.X. Dong. Neural Feedback Scheduling of Real-Time Control Tasks. Submitted, 2007.

    Google Scholar 

  23. X.H. Yang. Neural Networks with Applications to Control. Ph.D Thesis, Zhejiang University, 2004.

    Google Scholar 

Download references

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Zhejiang University Press, Hangzhou and Springer-Verlag GbmH Berlin Heidelberg

About this chapter

Cite this chapter

(2008). Neural Feedback Scheduling. In: Control and Scheduling Codesign. Advanced Topics in Science and Technology in China. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78255-1_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-78255-1_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78254-4

  • Online ISBN: 978-3-540-78255-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics