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Fuzzy Cognitive Networks: Adaptive Network Estimation and Control Paradigms

  • Chapter
Fuzzy Cognitive Maps

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 247))

Abstract

Fuzzy Cognitive Networks (FCN) constitutes an operational extension of Fuzzy Cognitive Maps (FCM), which assume that they always reach equilibrium points during their operation. Moreover, they are in continuous interaction with the system they describe and may be used to control it. FCN are capable of capturing steady state operational conditions of the system they describe and associate them with input values and appropriate weight sets. In the sequence they store the acquired knowledge in fuzzy rule based data bases, which can be used in determining subsequent control actions. This chapter presents basic theoretical results related to the existence and uniqueness of equilibrium points in FCN, the adaptive weight estimation based on system operation data, the fuzzy rule storage mechanism and the use of the entire framework to control unknown plants. The results are validated using well known control benchmarks.

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Author information

Authors and Affiliations

  1. Democritus University of Thrace, Xanthi, V.Sofias 12, Greece

    Thodoris L. Kottas & Yiannis S. Boutalis

  2. Technical University of Crete, Chania, Crete, Greece

    Manoli A. Christodoulou

Authors
  1. Thodoris L. Kottas
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  2. Yiannis S. Boutalis
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  3. Manoli A. Christodoulou
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  1. University of Aegean, Chios, Greece

    Michael Glykas

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Kottas, T.L., Boutalis, Y.S., Christodoulou, M.A. (2010). Fuzzy Cognitive Networks: Adaptive Network Estimation and Control Paradigms. In: Glykas, M. (eds) Fuzzy Cognitive Maps. Studies in Fuzziness and Soft Computing, vol 247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03220-2_5

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  • DOI: https://doi.org/10.1007/978-3-642-03220-2_5

  • Publisher Name: Springer, Berlin, Heidelberg

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  • Online ISBN: 978-3-642-03220-2

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