论文信息 - Noise rejection in parameters identification for piecewise linear fuzzy models

Noise rejection in parameters identification for piecewise linear fuzzy models

The fuzzy model identification problem from noisy data is addressed. The piecewise linear fuzzy model structure is used as a nonlinear prototype for a multi-input, single-output unknown system. The consequent of the fuzzy model is identified using noisy data, e.g. collected from experiments on a real system. The identification procedure is formulated within the Frisch scheme, well established for linear systems, which has been modified and improved to be applied in fuzzy systems field.

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