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A guide to the design offuzzy control systems for manufacturing processes

Abstract

While classical control theory has been demonstrated to be highly successful in many manufacturing technology applications, there are shortcomings when applied to processes that require the intuitive skills of a human operator. Fuzzy logic technique can be a significant aid in enabling machine systems to imitate the control stategy of an operator and so achieve an efficient control function. Commencing with the basic principles of fuzzy logic theory, the paper provides a practical guide to the design techniques used to establish fuzzy controller. An example of a welding robot to achieve an irregular weld path profile is used to illustrate the procedure.

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References

  1. Assilian, S. (1974) Artificial Intelligence in the control of real dynamic systems. PhD Thesis, University of London, UK.

    Google Scholar 

  2. Coles, O. and Burnham, K. J. (1985) Closed loop control of a simple robot—a fuzzy approach, inProceedings of the Fourth International Conference on System Engineering, Coventry, pp. 76–80.

  3. Hirota, K., Arai, Y. and Pedrycz, W. (1985) Robot control based on membership and vagueness, inApproximate Reasoning in Expert Systems, Guptaet al. (Eds).

  4. King, R. E. (1982) Fuzzy logic control of a cement kiln precalciner flash furnace,IEEE (Hull) papers of ‘Application of Adaptive and Multivariable Control Conference’.

  5. Kouatli, I. M. (1990) An improved method for the design of fuzzy controllers. Ph. D. Thesis, University of Birmingham, UK.

    Google Scholar 

  6. Kouatli, I. and Jones, B. (1990) An improved design procedure for fuzzy control systems.International Journal of Machine Tool and Manufacture, in press.

  7. Lakov, D. (1985) Adaptive robot under fuzzy control.Fuzzy Sets and Systems 17, 1–8.

    Google Scholar 

  8. Pedrycz, W. (1989)Fuzzy Control and Fuzzy Systems, Research Studies Press.

  9. Scharf, E. M., Mandie, N. J. and Mamdani, E. H. (1985). A self-organising algorithm for the control of robot arm, inProceedings of the 23rd ISMM International Symposium: Mini and Microcomputers and their Applications.

  10. Uragami, M., Mizumoto, M. and Tanaka, K. (1976) Fuzzy robot controls.Journal of Cybernetics 6, 39–64.

    Google Scholar 

  11. Zadeh, L. A. (1965) Fuzzy sets.Information Control 8, 338–53.

    Google Scholar 

  12. Zadeh, L. A. (1973) Outline of a new approach to the analysis of complex systems and decision processes.IEEE Transactions on Systems, Man and Cybernetics 3, 28–44.

    Google Scholar 

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Kouatli, I., Jones, B. A guide to the design offuzzy control systems for manufacturing processes. J Intell Manuf 1, 231–243 (1990). https://doi.org/10.1007/BF01471189

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Keywords

  • Artificial Intelligence
  • fuzzy control
  • robot applications
  • manufacturing systems
  • fuzzy algorithm