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Prediction Using Relational Models

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Fuzzy Modelling

Part of the book series: International Series in Intelligent Technologies ((ISIT,volume 7))

Abstract

Prediction is the problem of extrapolating a given signal sequence (or time series) into the future. The many theoretical assumptions required for the formulation of well-posed problems using relational models are stated. Specific issues of the identification and modelling of dynamic systems are studied. These include model feedback topologies, and the concerns with the maintenance of the set-theoretical (or logical) nature of fuzzy models during parameter estimation. Examples are included. A typical prediction application crystalized in the form of a predictive control algorithm is presented and applied to the control of a physical system.

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Author information

Authors and Affiliations

  1. Research Group on Control of Dynamic Systems, INESC, Apartado 13069, 1000, Lisboa, Portugal

    José Valente de Oliveira

Authors
  1. José Valente de Oliveira
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Editor information

Editors and Affiliations

  1. Electrical and Computer Engineering, University of Manitoba, Winnipeg, R3T 2N2, Canada

    Witold Pedrycz

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© 1996 Kluwer Academic Publishers

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de Oliveira, J.V. (1996). Prediction Using Relational Models. In: Pedrycz, W. (eds) Fuzzy Modelling. International Series in Intelligent Technologies, vol 7. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1365-6_5

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  • DOI: https://doi.org/10.1007/978-1-4613-1365-6_5

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4612-8589-2

  • Online ISBN: 978-1-4613-1365-6

  • eBook Packages: Springer Book Archive

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