Skip to main content
SpringerLink
Log in

Adaptive Granular Control of an HVDC System: A Rough Set Approach

  • Conference paper
  • First Online:
Book cover Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2639))

  • 697 Accesses

Abstract

This article reports the results of a three-year study of adaptive granular control of High-Voltage Direct Current (HVDC) systems using a combination of rough sets and granular computing techniques. A proportional integral (PI) control strategy is commonly used for constant current and extinction angle control in an HVDC system. A PI control strategy is based on a static design where the gains of a PI controller are fixed. Since the response of a HVDC plant dynamically changes with variations in the operating point, a PI controller’s performance is far from optimal. By contrast, an adaptive controller makes changes in the gains relative to the observed changes in HVDC system behavior. However, adaptive controllers require for their design, a frequency domain model of the controlled plant. Due to the non-linear operation of the HVDC system, such a model is difficult to establish. Because rough set theory makes it possible to set up a decision-making utility that approximates a control engineer’s knowledge about how to tune the controller of a system to improve its behavior, rough sets can be used to design an adaptive controller for the HVDC system. The contribution of this paper is the presentation of the design of a rough set based, granular control scheme. Experimental results that compare the performance of the adaptive control and PI control schemes are also given.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

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. J. Arrillaga, High Voltage Direct Current Transmission, Peter Pereginus, London, 1983.

    Google Scholar 

  2. E. Czogala, A. Mrozek, Z. Pawlak, The idea of a rough fuzzy controller and its application in the stabilization of a pendulum-car system, Fuzzy Sets and Systems 72, 1995, 61–63.

    Article  Google Scholar 

  3. H. Feng, Adaptive Granular Control for a HVDC System, M.Sc. Thesis, supervisor: J.F. Peters, Department of Electrical Engineering and Computer Engineering, Dec. 2002.

    Google Scholar 

  4. A.M. Gole, A. Daneshpooy, D.G. Chapman, J.B. Davies, Fuzzy logic control for HVDC transmission, IEEE Winter Meeting, New York, 1997.

    Google Scholar 

  5. E.W. Kimbark, Direct Current Transmission, Wiley, London, 1971.

    Google Scholar 

  6. T.Y. Lin, N. Cercone (Eds.), Rough Sets and Data Mining: Analysis of Imprecise Data. Kluwer Academic Publishers, Dordrecht, 1997.

    MATH  Google Scholar 

  7. A. Mrozek, L. Plonka, R. Winiarczyk, J. Majtan, Rough sets for controller synthesis. In: T.Y. Lin (Ed.), Proc. of the Third Int. Workshop on Rough Sets and Soft Computing (RSSC’94), San Jose, California, 10–12 November 1994, 498–505.

    Google Scholar 

  8. A. Mrozek, L. Plonka, J. Kedziera, The methodology of rough controller synthesis. In: Proc. 5th IEEE Int. Congress on Fuzzy Systems (FUZZ-IEEE’96), New Orleans, 8–11 September 1996, 1135–1139.

    Google Scholar 

  9. T. Munakata, Rough control: A Perspective. In: [6], 77–90.

    Google Scholar 

  10. Z. Pawlak, Rough real functions and rough controllers. In [6], 139–148.

    Google Scholar 

  11. Z. Pawlak, Rough Sets: Theoretical Aspects of Reasoning About Data, Boston, MA, Kluwer Academic Publishers, 1991.

    MATH  Google Scholar 

  12. J.F. Peters, V. Degtyaryov, M. Borkowski, S. Ramanna, Line-crawling robot navigation: Rough neurocomputing approach. In: C. Zhou, D. Maravall, D. Ruan, Fusion of Soft Computing and Hard Computing for Autonomous Robotic Systems. Berlin: Physica-Verlag, 2002.

    Google Scholar 

  13. J.F. Peters, S. Ramanna, A. Skowron, M. Borkowski: Wireless agent guidance of remote mobile robots: Rough integral approach to sensor signal analysis. In: N. Zhong, Y.Y. Yao, J. Liu, S. Ohsuga (Eds.), Web Intelligence, Lecture Notes in Artificial Intelligence 2198. Berlin: Springer-Verlag, 2001, 413–422.

    Chapter  Google Scholar 

  14. J.F. Peters, A. Skowron, Z. Suraj, An application of rough set methods to automatic concurrent control design. Fundamenta Informaticae, vol. 43, nos. 1–4, 2000, 269–290.

    MATH  MathSciNet  Google Scholar 

  15. J.F. Peters, K. Ziaei, S. Ramanna, Approximate time rough control: Concepts and application to satellite attitude control. In: L. Polkowski and A. Skowron (Eds.), Rough Sets and Current Trends in Computing, Lecture Notes in Artificial Intelligence, vol. 1424. Berlin, Springer-Verlag, 1998, 491–498.

    Chapter  Google Scholar 

  16. J.F. Peters, W. Pedrycz, Computational Intelligence. In: J.G. Webster (Ed.), Encyclopedia of Electrical and Electronic Engineering. 22 vols. NY, John Wiley & Sons, Inc., 1999.

    Google Scholar 

  17. J.F. Peters, S. Ramanna, Framework for approximate time rough control systems: An integrated fuzzy sets-rough sets approach. In: Proc. 7th Int. Symposium on Artificial Intelligence in Real-Time Control (AIRTC98), Grand Canyon, Arizona. 5–8 October, 1998, 1–8.

    Google Scholar 

  18. A. Skowron, Toward intelligent systems: Calculi of information granules. In: S. Hirano, M. Inuiguchi, S. Tsumoto (Eds.), Bulletin of the International Rough Set Society, vol. 5, no. 1/2, 2001, 9–30.

    Google Scholar 

  19. A. Skowron, J. Stepaniuk, S. Tsumoto, Information granules for spatial reasoning, Bulletin of the International Rough Set Society, vol. 3, no. 4, 1999, 147–154.

    Google Scholar 

  20. A. Skowron, J. Stepaniuk, J.F. Peters, Extracting patterns using information granules. In: S. Hirano, M. Inuiguchi, S. Tsumoto (Eds.), Bulletin of the International Rough Set Society, vol. 5, no. 1/2, 2001, 135–142.

    Google Scholar 

  21. A. Skowron, J. Stepaniuk, Information Granules: Towards foundations of granular computing, International Journal of Intelligent Systems, vol. 16, no. 1, Jan. 2001, 57–104.

    Article  MATH  Google Scholar 

  22. A. Skowron, J. Stepaniuk, J.F. Peters, Hierarchy of information granules. In: H.D. Burkhard, L. Czaja, H.S. Nguyen, P. Starke (Eds.), Proc. of the Workshop on Concurrency, Specification and Programming, Oct. 2001, Warsaw, Poland, 254–268.

    Google Scholar 

  23. T. Furuhashi, H. Yamamoto, J.F. Peters, W. Pedrycz, A stability analysis of fuzzy control systems using generalized fuzzy Petri net model, International Journal of Advanced Computational Intelligence 3(2), 1999, 99–106.

    Google Scholar 

  24. J.J. Alpigini, J.F. Peters, Dynamic visualization with rough performance maps. In: W. Ziarko, Y. Yao (Eds.), Rough Sets and Current Trends in Computing (RSCTC’00), Lectures Notes in Artificial Intelligence 2005. Berlin: Springer-Verlag, 2001, 90–97.

    Chapter  Google Scholar 

  25. L.A. Zadeh, Fuzzy sets, Information Control 8, 1965, 338–353.

    Article  MATH  MathSciNet  Google Scholar 

  26. L.A. Zadeh, Toward a theory of fuzzy information granulation and its certainty in human reasoning and fuzzy logic, Fuzzy Sets and Systems 90(2), 1997, 111–128.

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Manitoba, 15 Gillson Street, ENGR 504, Winnipeg, Manitoba, R3T 5V6, Canada

    J. F. Peters, H. Feng & S. Ramanna

Authors
  1. J. F. Peters
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. H. Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S. Ramanna
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to J. F. Peters .

Editor information

Editors and Affiliations

  1. Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, P.R. China

    Guoyin Wang

  2. Department of Computer Science, Nanchang University, Nanchang, 330029, P.R. China

    Qing Liu

  3. Department of Computer Science, University of Regina, Regina, Saskatchewan, S4S 0A2, Canada

    Yiyu Yao

  4. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Peters, J.F., Feng, H., Ramanna, S. (2003). Adaptive Granular Control of an HVDC System: A Rough Set Approach. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2003. Lecture Notes in Computer Science(), vol 2639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39205-X_27

Download citation

  • DOI: https://doi.org/10.1007/3-540-39205-X_27

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-14040-5

  • Online ISBN: 978-3-540-39205-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation