Advertisement

Artificial Life and Robotics

, Volume 1, Issue 2, pp 59–63 | Cite as

A fuzzy-logic approach to industrial control problems

  • David J. G. JamesEmail author
  • Keith J. Burnham
Original Paper
  • 78 Downloads

Abstract

Increasing demands for improved profitability and product quality, together with a growing awareness of the effects of industrial wastage on the environment, is forcing manufacturers to closely examine their process operations. As a consequence there is currently significant research and development activity aimed at improving control system strategies in a variety of industrial sectors. Recent years have witnessed renewed interest in fuzzy logic and rule-based control strategies and, by considering two illustrative industrial case studies, this paper highlights some of the potential advantages.

Key words

Fuzzy based controllers Industrial applications Supervisory decision making 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Goodhart SG, Burnham KJ, James DJG (1994) Bilinear self-tuning control of a high temperature heat treatment plant. IEEE Proc D Control Theory and Applications 141(1):12–18zbMATHCrossRefGoogle Scholar
  2. 2.
    Burnham KJ, Disdell KJ, James DJG, Smith CA (1995) Developments in industrial applications of self-tuning. J Control Engineering Practice 3(9):1265–1276CrossRefGoogle Scholar
  3. 3.
    Dunlop JA (1995) Intelligent fuzzy controller for engine testing systems. PhD thesis, Coventry University, Coventry, UKGoogle Scholar
  4. 4.
    Dunlop JA, Burnham KJ, James DJG, King PJ (1995) Application of fuzzy logic based self-tuning control. Proceedings of the IEEE/IAS International Conference on Industrial Automation and Control, Hyderabad, India, pp 109–114Google Scholar
  5. 5.
    King PJ, Burnham KJ, James DJG (1994) A combined rule-based and model-based adaptive control scheme. Proceedings IEE Control '94, IEE Publication 389, London. pp 1484–1489Google Scholar
  6. 6.
    Mohler RR (1973) Bilinear control process. Academic, New York.Google Scholar
  7. 7.
    Bruni C, Di-Pillo G, Koch G (1974) Bilinear systems: an appealing class of “nearly linear” systems in theory and applications. IEEE Trans Aut Control 19:334–348zbMATHMathSciNetCrossRefGoogle Scholar
  8. 8.
    Pedryz W (1993) Fuzzy control and fuzzy systems, 2nd edn. Research Studies Press, Taunton, UKGoogle Scholar
  9. 9.
    Dunlop JA, Burnham KJ, James DJG, King PJ (1994) A self-tuning scaling method for fuzzy control. Proceedings of the 3rd IEEE Conference on Control Applications, Strathclyde, Glasgow UK, pp 683–687Google Scholar
  10. 10.
    Hehlhofer RH (1990) Combined-cycle gas and steam turbine power plants. Prentice-Hall, Englewood Cliffs, NJGoogle Scholar
  11. 11.
    Smith CA, Burnham KJ, Ham PAL, James DJG (1994) Accommodating thermal stress during the start up of a combined cycle plant. Proceedings of the 10th International Conference on Systems Engineering, Vol II, Coventry, UK, pp 1151–1158Google Scholar
  12. 12.
    Smith CA, Burnham KJ, James DJG, Ham PAL (1995) Fuzzy and model based supervisory controller for combined cycle plant start up using thermal stress constraints. Proceedings of the 3rd European Control Conference, vol 3, Rome, Italy, pp 2444–2449Google Scholar
  13. 13.
    Smith CA, Burnham KJ, Ham PAL, James DJG (1995) Adaptive fuzzy control of combined cycle plant. Proceedings of IFAC Symposium on Control of Power Plants, Cancun. Mexico, pp 263–268Google Scholar

Copyright information

© ISAROB 1997

Authors and Affiliations

  1. 1.Control Theory and Applications CentreConventry UniversityCoventryUK

Personalised recommendations