Block-structured models composed of nonlinear fuzzy dynamic and static parts : a case study

• Autorzy: Bazydło P. , Marusak P.

Identyfikatory

DOI

10.14313/JAMRIS_1-2018/7

• Języki publikacji: EN

Abstrakty

EN

The paper addresses issues of the dynamic fuzzy Takagi- Sugeno models identification for multi-step ahead prediction. In the case of highly nonlinear models, standard Takagi-Sugeno models may be hard to identify if they should be designed for recurrent prediction generation. In such a case, alternative fuzzy block-structured models composed of fuzzy dynamic and fuzzy static parts may be useful. Two main benefits of the proposed models are: (1) possibility to speed-up model tuning procedure, (2) potential to fine-tune an already available, standard Takagi-Sugeno model. The benefits offered by the proposed models are illustrated using the example of identification of a nonlinear process – a system consisting of two tanks of different shapes (cylindrical and conical ones).

Słowa kluczowe

EN

block-structured model; Takagi-Sugeno model; identification; modelling; fuzzy logic

PL

model blokowy; modele Takagi-Sugeno; identyfikacja; modelowanie; logika rozmyta

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2018
• Tom: Vol. 12, No. 1
• Strony: 50--60
• Opis fizyczny: Bibliogr,. 19 poz., rys.

Twórcy

autor

Bazydło P.

• Research and Academic Computer Network (NASK), Kolska 12, 01-045 Warsaw, Poland

autor

Marusak P.

• Institute of Control and Computation Engineering, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warsaw, Poland

Bibliografia

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).