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    Wyświetlanie 1-8 z 8
    Tytuł:
    Nonlinear actuator fault estimation observer: an inverse system approach via a T-S fuzzy model
    Autorzy:
    Xu, D.
    Jiang, B.
    Shi, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/331464.pdf
    Data publikacji:
    2012
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    model rozmyty Takagi-Sugeno
    obserwator ślizgowy
    system odwrotny
    actuator fault estimation
    Takagi-Sugeno fuzzy models
    robust sliding mode observer
    inverse system method
    Opis:
    Based on a Takagi-Sugeno (T-S) fuzzy model and an inverse system method, this paper deals with the problem of actuator fault estimation for a class of nonlinear dynamic systems. Two different estimation strategies are developed. Firstly, T-S fuzzy models are used to describe nonlinear dynamic systems with an actuator fault. Then, a robust sliding mode observer is designed based on a T-S fuzzy model, and an inverse system method is used to estimate the actuator fault. Next, the second fault estimation strategy is developed. Compared with some existing techniques, such as adaptive and sliding mode methods, the one presented in this paper is easier to be implemented in practice. Finally, two numerical examples are given to demonstrate the efficiency of the proposed techniques.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2012, 22, 1; 183-196
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A novel fuzzy c-regression model algorithm using a new error measure and particle swarm optimization
    Autorzy:
    Soltani, M.
    Chaari, A.
    Ben Hmida, F.
    Powiązania:
    https://bibliotekanauki.pl/articles/330134.pdf
    Data publikacji:
    2012
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    model rozmyty Takagi-Sugeno
    algorytm grupowania
    metoda najmniejszych kwadratów
    optymalizacja rojem cząstek
    Takagi-Sugeno fuzzy models
    noise clustering algorithm
    fuzzy c-regression model
    orthogonal least squares
    particle swarm optimization (PSO)
    Opis:
    This paper presents a new algorithm for fuzzy c-regression model clustering. The proposed methodology is based on adding a second regularization term in the objective function of a Fuzzy C-Regression Model (FCRM) clustering algorithm in order to take into account noisy data. In addition, a new error measure is used in the objective function of the FCRM algorithm, replacing the one used in this type of algorithm. Then, particle swarm optimization is employed to finally tune parameters of the obtained fuzzy model. The orthogonal least squares method is used to identify the unknown parameters of the local linear model. Finally, validation results of two examples are given to demonstrate the effectiveness and practicality of the proposed algorithm.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2012, 22, 3; 617-628
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    T–S fuzzy BIBO stabilisation of non-linear systems under persistent perturbations using fuzzy Lyapunov functions and non-PDC control laws
    Autorzy:
    Salcedo, José V.
    Martínez, Miguel
    García-Nieto, Sergio
    Hilario, Adolfo
    Powiązania:
    https://bibliotekanauki.pl/articles/330030.pdf
    Data publikacji:
    2020
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    linear matrix inequalities
    Takagi–Suegno fuzzy system
    fuzzy Lyapunov function
    integral delayed Lyapunov function
    nonparallel distributed fuzzy controller
    generalised inescapable ellipsoids
    liniowe nierówności macierzowe
    model rozmyty Takagi-Sugeno
    funkcja Lapunowa
    Opis:
    This paper develops an innovative approach for designing non-parallel distributed fuzzy controllers for continuous-time non-linear systems under persistent perturbations. Non-linear systems are represented using Takagi–Sugeno fuzzy models. These non-PDC controllers guarantee bounded input bounded output stabilisation in closed-loop throughout the computation of generalised inescapable ellipsoids. These controllers are computed with linear matrix inequalities using fuzzy Lyapunov functions and integral delayed Lyapunov functions. LMI conditions developed in this paper provide non-PDC controllers with a minimum ⋆-norm (upper bound of the 1-norm) for the T–S fuzzy system under persistent perturbations. The results presented in this paper can be classified into two categories: local methods based on fuzzy Lyapunov functions with guaranteed bounds on the first derivatives of membership functions and global methods based on integral-delayed Lyapunov functions which are independent of the first derivatives of membership functions. The benefits of the proposed results are shown through some illustrative examples.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2020, 30, 3; 529-550
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Further results on robust fuzzy dynamic systems with LMI D-stability constraints
    Autorzy:
    Assawinchaichote, W.
    Powiązania:
    https://bibliotekanauki.pl/articles/331041.pdf
    Data publikacji:
    2014
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    fuzzy controller
    robust control
    LMI approach
    D-stability
    Takagi-Sugeno fuzzy model
    regulator rozmyty
    sterowanie odporne
    stabilność
    model Takagi-Sugeno
    Opis:
    This paper examines the problem of designing a robust H∞ fuzzy controller with D-stability constraints for a class of nonlinear dynamic systems which is described by a Takagi–Sugeno (TS) fuzzy model. Fuzzy modelling is a multi-model approach in which simple sub-models are combined to determine the global behavior of the system. Based on a linear matrix inequality (LMI) approach, we develop a robust H∞ fuzzy controller that guarantees (i) the L2-gain of the mapping from the exogenous input noise to the regulated output to be less than some prescribed value, and (ii) the closed-loop poles of each local system to be within a specified stability region. Sufficient conditions for the controller are given in terms of LMIs. Finally, to show the effectiveness of the designed approach, an example is provided to illustrate the use of the proposed methodology.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2014, 24, 4; 785-794
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    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
    Tytuł:
    Design and Stability of Fuzzy Logic Multi-Regional Output Controllers
    Autorzy:
    Domański, P.
    Brdyś, M. A.
    Tatjewski, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/908274.pdf
    Data publikacji:
    1999
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    sterowanie nieliniowe
    sterowanie wewnętrzne
    zbiór rozmyty
    model Takagi-Sugeno
    nonlinear output control
    fuzzy logic
    Takagi-Sugeno models
    stability conditions
    Opis:
    Design and stability analysis of fuzzy multi-regional digital controllers is considered in the paper. The controllers are based on a notion of NARMAX systems, very similar to the Takagi-Sugeno fuzzy model. The nonlinear system is approximated by a number of linear subsystems. Linear controllers are designed for all subsystems. It can be made in a classical way due to the subsystems linearity. The controllers are blended into one controller by employing fuzzy logic, the result being the fuzzy multi-regional controller (FuMR). The stability analysis of nonlinear systems with FuMR controllers composed of dynamic output feedback local linear controllers is provided. Examples illustrate the design procedure and the meaning of the stability criterion.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 1999, 9, 4; 883-897
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Wykorzystanie modeli Takagi-Sugeno do krótkoterminowego prognozowania zapotrzebowania na energię elektryczną odbiorców wiejskich
    Using the Takagi-Sugeno models for short-term forecasting of rural consumers demand for electric energy
    Autorzy:
    Trojanowska, M.
    Małopolski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/289025.pdf
    Data publikacji:
    2009
    Wydawca:
    Polskie Towarzystwo Inżynierii Rolniczej
    Tematy:
    energia elektryczna
    prognozowanie krótkoterminowe
    model rozmyty
    electric energy
    short-term forecasting
    fuzzy model
    Opis:
    Opracowano modele z wnioskowaniem typu Takagi-Sugeno o gaussowskich funkcjach przynależności w przestrzeni wejściowej do krótkoterminowego prognozowania zapotrzebowania na energię elektryczną odbiorców wiejskich. Ze względu na charakter zmienności obciążeń opracowano odrębne modele dla typowych dni tygodnia. Przeprowadzona analiza wykazała przydatność modeli Takagi-Sugeno do predykcji z wyprzedzeniem godzinowym i ich konkurencyjność w stosunku do rozmytych modeli Mamdaniego.
    Models with concluding, Takagi-Sugeno type, with Gaussian functions of affiliation in entry space were developed for short-term forecasting of rural consumers' demand for electric energy. Due to loads variability character separate models were developed for typical week days. Completed analysis proved usability of the Takagi-Sugeno models for prediction with hourly advance, and their competitiveness compared to Mamdani fuzzy models.
    Źródło:
    Inżynieria Rolnicza; 2009, R. 13, nr 1, 1; 325-330
    1429-7264
    Pojawia się w:
    Inżynieria Rolnicza
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A new fuzzy Lyapunov approach to non-quadratic stabilization of Takagi-Sugeno fuzzy models
    Autorzy:
    Abdelmalek, I.
    Goléa, N.
    Hadjili, M. L.
    Powiązania:
    https://bibliotekanauki.pl/articles/911242.pdf
    Data publikacji:
    2007
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    liniowe nierówności macierzowe
    stabilizacja
    funkcja Lapunowa
    model Takagi-Sugeno
    system rozmyty
    T-S fuzzy systems
    non-quadratic stability conditions
    linear matrix inequalities
    parallel distributed compensation
    stabilization
    Opis:
    In this paper, new non-quadratic stability conditions are derived based on the parallel distributed compensation scheme to stabilize Takagi-Sugeno (T-S) fuzzy systems. We use a non-quadratic Lyapunov function as a fuzzy mixture of multiple quadratic Lyapunov functions. The quadratic Lyapunov functions share the same membership functions with the T-S fuzzy model. The stability conditions we propose are less conservative and stabilize also fuzzy systems which do not admit a quadratic stabilization. The proposed approach is based on two assumptions. The first one relates to a proportional relation between multiple Lyapunov functions and the second one considers an upper bound to the time derivative of the premise membership functions. To illustrate the advantages of our proposal, four examples are given.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2007, 17, 1; 39-51
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-8 z 8

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