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Wyszukujesz frazę "Sugeno fuzzy model" wg kryterium: Temat


Wyświetlanie 1-3 z 3
Tytuł:
Fuzzy adaptive control of a class of MISO nonlinear systems
Autorzy:
Lagrat, I.
Ouakka, H.
Boutnhidi, I.
Powiązania:
https://bibliotekanauki.pl/articles/971004.pdf
Data publikacji:
2008
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
identyfikacja
sterowanie adaptacyjne
układ nieliniowy
MISO systems
identification
fuzzy clustering
Takagi-Sugeno fuzzy model
adaptive control
nonlinear system
Opis:
This paper presents a fuzzy adaptive control of a class of MISO nonlinear systems. The dynamic behaviour of each MISO systems is composed of a nonlinear term, interactions effect between the inputs, and disturbances. In these circumstances, adaptive control becomes very difficult to implement and not always an evident task. Thus, the MISO system is approximated by the Takagi-Sugeno fuzzy model. The advantage of this approximation is beneficial in the sense that it allows for converting the nonlinear problem into a linear one. In this respect, the coupling, nonlinearity and unmodeled dynamics are easily compensated. The identification and the control are conducted at the level of each local linear model based on fuzzy approach. The computational load and the complexity of nonlinear approach are reduced and permit wide applicability. The validity and the performance are tested numerically.
Źródło:
Control and Cybernetics; 2008, 37, 1; 177-190
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Block-structured models composed of nonlinear fuzzy dynamic and static parts : a case study
Autorzy:
Bazydło, P.
Marusak, P.
Powiązania:
https://bibliotekanauki.pl/articles/384609.pdf
Data publikacji:
2018
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
block-structured model
Takagi-Sugeno model
identification
modelling
fuzzy logic
model blokowy
modele Takagi-Sugeno
identyfikacja
modelowanie
logika rozmyta
Opis:
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).
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2018, 12, 1; 50-60
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparision of Two Construction Algorithms for Takagi-Sugeno Fuzzy Models
Autorzy:
Nelles, O.
Fink, A.
Babuska, R.
Setnes, M.
Powiązania:
https://bibliotekanauki.pl/articles/911156.pdf
Data publikacji:
2000
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
modelowanie
identyfikacja
model rozmyty
turbosprężarka doładowująca
modeling
identification
Takagi-Sugeno fuzzy models
local linear models
turbocharger
Opis:
This paper compares two different approaches to the construction of Takagi-Sugeno fuzzy models from data. These models approximate nonlinear systems by means of interpolation between local linear models. The main issue in the construction of Takagi-Sugeno models is the decomposition of the operating space into validity regions for the local models. The way this decomposition is done influences the complexity, accuracy and transparency of the obtained model. The first of the presented methods, the local linear model tree (LOLIMOT) algorithm generates incrementally the fuzzy model by axis-orthogonal decomposition of the input space. In the other method, product-space fuzzy clustering (the Gustafson-Kessel algorithm) is used to partition the available data into fuzzy subsets. The fundamental advantages and drawbacks of both the alternative strategies are pointed out. Their properties and real-world applicability are illustrated by building a dynamic model of a truck Diesel engine turbocharger.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2000, 10, 4; 835-855
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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