In this paper the problem of identifying a fuzzy model from noisy data is addressed. The piece-wise affine fuzzy model structure is used as non linear prototype for a multi--input, single--output unknown system. The consequents of the fuzzy model are identified from noisy data which are collected from experiments on the real system. The identification procedure is formulated within the Frisch scheme, well established for linear systems, which is extended so that it applies to piecewise-affine, constrained models
Parameter identification for piecewise affine fuzzy models in noisy environment / Silvio, Simani; Fantuzzi, Cesare; Riccardo, Rovatti; Sergio, Beghelli. - In: INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. - ISSN 0888-613X. - STAMPA. - 22:(1999), pp. 149-167.
Parameter identification for piecewise affine fuzzy models in noisy environment
FANTUZZI, Cesare;
1999
Abstract
In this paper the problem of identifying a fuzzy model from noisy data is addressed. The piece-wise affine fuzzy model structure is used as non linear prototype for a multi--input, single--output unknown system. The consequents of the fuzzy model are identified from noisy data which are collected from experiments on the real system. The identification procedure is formulated within the Frisch scheme, well established for linear systems, which is extended so that it applies to piecewise-affine, constrained models
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