Skip to main content

Integrated process supervision: A structured approach to expert control

  • Conference paper
  • First Online:
Progress in Artificial Intelligence (EPIA 1995)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 990))

Included in the following conference series:

Abstract

There is much interest in the use of expert systems in online process supervision and control. One of the better known Expert Control (EC) [1] architecture is that proposed by Karl J. Astrom. In this architecture, there are several alternative algorithms used for the same function. This is because there is seldom one single algorithm that works for the entire operation. These algorithms are coordinated by an expert system, which decides which algorithm to use and when to use it [1]. It is at this point that the architecture offers little assistance. As a result, most applications of the Expert Control (EC) tend to have ad hoc rules

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Astrom K.J., Arzen K.-E., Expert Control in An Introduction to Intelligent and Autonomous Control, Panos J. Antsakis, Kevin M. Passino (Editors), Kluwer Academic Publishers, 1993.

    Google Scholar 

  2. Astrom K. J., ”Intelligent Control” in Proceedings of the 1st European Control Conference, Grenoble, France, pp 2328–2339, 1991.

    Google Scholar 

  3. Astrom K.J. ”Self Tuning Regulators — Design Principles and Applications” in Applications of Adaptive Control, Kumpati S. Narendra, Richard V. Monopoli (Editors), pp 1–68, Academic Press, USA, 1979.

    Google Scholar 

  4. Kumpati S. Narendra, Yuan-Hao Lin, ”Design of Stable Model Reference Adaptive Controllers” in Applications of Adaptive Control, Kumpati S. Narendra, Richard V. Monopoli (Editors), pp 69–130, Academic Press, USA, 1979.

    Google Scholar 

  5. Astrom K.J., Hang C.C., Persson P., Ho. W.K. ”Towards Intelligent PID Control” in Automatica Vol 28. No. 1, pp 1–9, Great Britain, 1992.

    Article  Google Scholar 

  6. Krijgsman A.J., Verbruggen H.B., Brujin P.M., ”Knowledge Based Real-Time Control” in 3rd IFAC Workshop on Artificial Intelligence in Real-Time Control, Clyne Castle, Swansea, UK, pp 13–19, 1988.

    Google Scholar 

  7. H.B. Verbruggen, A.J. Krijgsman, P.M. Brujin, ”Towards Intelligent Control: Integration of AI in Control” in Application of Artificial Intelligence In Process Control, L. Boullart, A. Krijgsman, R.A. Vingerhoeds (Editors), pp 223–249, Pergamon Press, 1992

    Google Scholar 

  8. F. Morant, M. Martinez, J. Pico, ”Supervised Adaptive Control”, in Application of Artificial Intelligence In Process Control, L. Boullart, A. Krijgsman, R.A. Vingerhoeds (Editors), pp 223–249, Pergamon Press, 1992.

    Google Scholar 

  9. R. Leitch and C. Quek, ”Architecture for integrated process supervision”, IEE Proceedings-D, Control Theory and Application, Vol. 139, No. 3, pp 317–327, May 1992.

    Google Scholar 

  10. R. Leitch and C. Quek ”A behaviour classification for integrated process supervision”, IEE Proceedings of the 3rd International Conference on Control, Vol 1, pp 127–133, Edinburgh, Scotland, March 91

    Google Scholar 

  11. Quek H.C., Ng P.W., Ng G.S., ”Fuzzy Integrated Process Supervision of Neural Network Control Regimes” in Proceeings of the 2nd Singapore International Conference on Intelligent Systems, pp 153–158, Singapore, November 1994.

    Google Scholar 

  12. W.H.Schiffman and H.W.Geffers, ”Adaptive Control of Dynamic Systems by Backpropagation Networks”, Neural Networks, Vol. 6, pp 517–524, S.Grossberg, M.Kawato and J.Taylor (Ed.), Pergamon Press, USA, 1993.

    Google Scholar 

  13. C. Quek and R. Leitch, ”Direct method for model reference adaptive PI controller using the gradient approach”, Proceedings of IEEE Region 10 International Conference, Tencon 93, Vol. 4, pp 447–450, Beijing.

    Google Scholar 

  14. Q. Shen, Fuzzy qualitative simulation and Diagnosis of continuous dynamic systems, Ph.D. Thesis, Heriot-Watt University, Edinburgh, September 1991.

    Google Scholar 

  15. D.L. Dvorak and B. Kuipers, ”Model based monitoring of dynamic systems”, Proceedings of the 11th International Joint Conference on Artificial Intelligence, Vol. 2, pp 1338–1343, 1989.

    Google Scholar 

  16. D. Weld and J. DeKleer, Readings in qualitative simulation about physical systems, Morgan Kaufman Publisher, San Mateo, CA, 1989.

    Google Scholar 

  17. C. Quek, S.Y. Huang and J.C. Tay, ”Qualitative synchronous fault tracking for dynamic process diagnosis”, Proceedings of the 2nd International Conference for Intelligent Systems, pp 249–255, Singapore, 1994.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Carlos Pinto-Ferreira Nuno J. Mamede

Rights and permissions

Reprints and permissions

Copyright information

© 1995 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Quek, C., Ng, P.W., Pasquier, M. (1995). Integrated process supervision: A structured approach to expert control. In: Pinto-Ferreira, C., Mamede, N.J. (eds) Progress in Artificial Intelligence. EPIA 1995. Lecture Notes in Computer Science, vol 990. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60428-6_27

Download citation

  • DOI: https://doi.org/10.1007/3-540-60428-6_27

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60428-0

  • Online ISBN: 978-3-540-45595-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics