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Soft Computing

Erschienen in:

01.01.2006 | Original Paper

New dynamic fuzzy structure and dynamic system identification

verfasst von: Musa Alci

Erschienen in: Soft Computing | Ausgabe 2/2006

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Abstract

In this study, a new fuzzy system structure that reduces the number of inputs is proposed for dynamic system identification applications. Algebraic fuzzy systems have some disadvantages due to many inputs. As the number of inputs increase, the number of parameters in the training process increase and hence the classical fuzzy system becomes more complex. In the conventional fuzzy system structure, the past information of both inputs and outputs are also regarded as inputs for dynamic systems, therefore the number of inputs may not be manageable even for “single input and single output” systems. The new dynamic fuzzy system module (DFM) proposed here has only a single input and a single output. We have carried out identification simulations to test the proposed approach and shown that the DFM can successfully identify non-linear dynamic systems and it performs better than the classical fuzzy system.

Vorheriger Artikel Regular grammars with truth values in lattice-ordered monoid and their languages

Nächster Artikel Conceptual procedure for ranking fuzzy numbers based on adaptive two-dimensions dominance

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Titel: New dynamic fuzzy structure and dynamic system identification
verfasst von: Musa Alci
Publikationsdatum: 01.01.2006
Verlag: Springer-Verlag
Erschienen in: Soft Computing / Ausgabe 2/2006
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-004-0428-x

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