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A self tuning fuzzy controller

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Computational Intelligence Theory and Applications (Fuzzy Days 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1226))

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Abstract

Real industrial processes can never be modelled perfectly as simple as the linear first and second order systems. They have such marked characteristics as high-order, dead-time, non-linearity etc., and may be affected by noise, load disturbance and other ambinent conditions that cause parameter variation and sudden model structural change. The existing theories can no longer provide systematic and robust tuning laws for these complex situations. The operator intuitively regulates the executor to control the process by watching the error and the change rate of the error between the system's output and the set-point value. Usually fuzzy control rules are constructed by summarising the manual control experiences of an operator who has been controlling the industrial process skilfully and successfully.

In the presence of substantial parameter changes, however, or major external disturbances, PID-systems usually are faced with a trade-off between fast reaction with significant overshoot or smooth but slow reactions, or they even run into problems in stabilising the system at all. In this paper, fuzzy control adaptive system monitors its own performance and adjusts its control mechanism to improve performance for slowly time-varying processes. The whole controlling process is automatically adjusted on-line in response to the varying control situation with certain updating scheme. In this manner, an adaptive fuzzy controller can able to handle the complex situations and variety of non-linearities even when subject to random disturbances.

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Authors and Affiliations

  1. Technical Institute Of Cybernetics, Technical University Of Wroclaw, Poland

    Sireesh Kumar Pandey

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  1. Sireesh Kumar Pandey
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Bernd Reusch

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© 1997 Springer-Verlag Berlin Heidelberg

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Pandey, S.K. (1997). A self tuning fuzzy controller. In: Reusch, B. (eds) Computational Intelligence Theory and Applications. Fuzzy Days 1997. Lecture Notes in Computer Science, vol 1226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62868-1_128

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  • DOI: https://doi.org/10.1007/3-540-62868-1_128

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62868-2

  • Online ISBN: 978-3-540-69031-3

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