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- W137488774 abstract "When Zadeh introduced the Compositional Rule of Inference, one of the most important aspects was that by this new technique of modelling it became possible to describe very complex systems in a way that enables drastic reduction of computational complexity (both in the space and time sense), as compared to previous symbolic methods of Artificial Intelligence that always neglected the subsymbolic structural information in the model. A computationally more effective version of the same idea was soon proposed by Mamdani, and so practical applications of fuzzy models and controllers were suddenly possible. The Mamdani (M-)model was followed several years later by a simplified technique, proposed by Sugeno (S-controller) , a special case of the M-controller, using crisp output in the rules, and this was soon extended to the idea of Takagi-Sugeno-model that uses crisp outputs, however as functions valid for an element of the fuzzy partition of the input space. The existence of these models started a philosophical question: Do very complex systems with no identificable explicit models have a crisp transfer function at all that can be approximated (even if it is unknown)? The S- and TS-models seem to suggest an affirmative answer. The M-model, however, does not support the assumption. We think that both attitudes have a justification: some of the systems do have a theoretical crisp transfer function, but some of them do not. What is the solution of the problem in the latter case? There exists a fuzzy transfer function, that maps the fuzzy power set of the input universe of discourse onto the fuzzy power set of the output universe of discourse. We have recently discussed some aspects of this mapping, showing that all former models can be interpreted as special case of the general fuzzy model. (This model is also supported by recent considerations of Zadeh on a class of problems that cannot be discussed in terms of crisp transfer functions.) This paper will add a few aspects to the ways of approximation both types of transfer functions, crisp anf fuzzy. The most important elements here are the evidence obtained by analysing the explicit functions of the three classical fuzzy controllers, the results available on the universal approximator property of fuzzy controllers, and the method of rule interpolation that enables the uniform handling of all models in question. Some advantageous properties of the interpolation techniques proposed by Kôczy and Hirota will be shown, especially stressing the stability of such interpolations." @default.
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- W137488774 date "1998-01-01" @default.
- W137488774 modified "2023-09-25" @default.
- W137488774 title "Approximation of Transfer Functions by Various Fuzzy Controllers" @default.
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- W137488774 doi "https://doi.org/10.1007/978-3-7908-1885-7_13" @default.
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