Skip to main content

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4681))

Included in the following conference series:

Abstract

In this paper, the application of fuzzy set theory, genetic algorithms and rough set theory techniques to the control of the High Voltage Direct Current (HVDC) system is studied. A fuzzy adaptive control scheme with the aid of rough set theory via genetic algorithms (GAs) finding the center scaling-factors in place of the classical control is proposed. On the one hand, genetic algorithm gets optimal parameters of an accurate domain model, which tunes the scaling factors of fuzzy adaptive control but is hardly established in a non-liner system. On the other hand, fuzzy adaptive control deals with the dynamics and complexity of responses from a HVDC system in the operation points, by adjusting its control parameters with the aid of rough tuner adaptively. Our study includes a brief introduction to fuzzy sets, fuzzy control and rough set algorithms, both theory and application. We also evaluate the performance of fuzzy adaptive control by simulation in the paper. The focus of our experiments is on the constant current control in HVDC system. The result shows there are many improvements offered by the fuzzy control scheme based on rough set theory in comparison with the conventional HVDC control scheme.

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 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
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. Wang, Z.X., Yang, J.J., Ahn, T.C.: The Design of Self-tuning Strategy of Genetically Optimized Fuzzy-PI Controller for HVDC System. LNCS. Springer, Heidelberg (2006)

    Google Scholar 

  2. Wang, Z.X., Yang, J.J., Rho, S.B., Ahn, T.C.: A New Design of Fuzzy Controller for HVDC System with the Aid of Gas. Journal of Control, Automation, and Systems Engineering 12(3), 221–226 (2006)

    Google Scholar 

  3. Wang, Z.X., Yang, J.J., Ahn, T.C.: Genetically Optimized FIS Controller by Means of Self-tuning Strategy in HVDC System. Dynamics of Continuous, Discrete and Impulsive Systems, Series B: Applications and Algorithms, ISSN 1492-8760 (2006)

    Google Scholar 

  4. Ahn, T.C.: Development of Adaptive Granular Control Technique for HVDC Transmission System (2005)

    Google Scholar 

  5. Wang, L.X.: A Course of Fuzzy System and Control. Prentice-Hall, Englewood Cliffs (1997)

    Google Scholar 

  6. Oh, S.K., Pedrycz, W., Rho, S.B., Ahn, T.C.: Parameter Estimation of Fuzzy Controller and Its Application to Inverted Pendulum. Engineering Applications of Artificial Intelligence 17(1), 37–60 (2004)

    Article  Google Scholar 

  7. Zhou, X.X.: The Analysis and Control of AC/DC Power System (2004)

    Google Scholar 

  8. Witold, P.: Granular Computing: An Introduction. IEEE Computer Society Press, Los Alamitos

    Google Scholar 

  9. MA, Y.F., ZHAO Y.: Research on A Data Mining Algorithm Based on Rough Set. Journal of Luoyuang University 21(2) (2006)

    Google Scholar 

  10. Li, M.X., Wu, C.D.: Rough Set Theory and Its Application. Journal of Shenyang Arch. and Civ. Eng. Univ. Nature Science 17(4) (2001)

    Google Scholar 

  11. Han, L., Xu, Z.G.: On-line Self-Tuning Fuzzy Controller Based on Rough Sets and Its Application in the Boiler Main Stream Temperature. Measurement and Control Technology 23(12) (2004)

    Google Scholar 

  12. Rough set theory and methods. Science Press, Beijing, China (2005)

    Google Scholar 

  13. Feng, H.: Adaptive Granular Control for a HVDC System (2002)

    Google Scholar 

  14. Liu, J.K.: Advanced PID Control with MATLAB Simulation. Electronic Industry Publishing, Company (2002)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

De-Shuang Huang Laurent Heutte Marco Loog

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer Berlin Heidelberg

About this paper

Cite this paper

Wang, ZX., Ahn, TC. (2007). Design of Adaptive Fuzzy-PI Control with the Aid of Rough Set Theory and Its Application to a HVDC System. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2007. Lecture Notes in Computer Science, vol 4681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74171-8_43

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-74171-8_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74170-1

  • Online ISBN: 978-3-540-74171-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics