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    Wyświetlanie 1-6 z 6
    Tytuł:
    Environment adaptive lighting systems for smart homes
    Autorzy:
    Catalbas, M. C.
    Powiązania:
    https://bibliotekanauki.pl/articles/102529.pdf
    Data publikacji:
    2017
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    lighting control
    fuzzy systems
    image segmentation
    pattern clustering
    smart home
    Opis:
    In this work, an application of adaptive lighting system is proposed for smart homes. In this paper, it is suggested that, an intelligent lighting system with outdoor adaptation can be realized via a real fisheye image. During the implementation of the proposed method, the fuzzy c-means method, which is a commonly used data clustering method, has been used. The input image is divided into three different regions according to its brightness levels. Then, the RGB image is converted to CIE 1931 XYZ color space; and the obtained XYZ values are converted to x and y values. The parameters of x and y values are shown in CIE Chromaticity Diagram for different regions in the sky. Thereafter, the coordinate values are converted to Correlated Color Temperature by using two different formulas. Additionally, the conversion results are examined with respect to actual and estimated CCT values.
    Źródło:
    Advances in Science and Technology. Research Journal; 2017, 11, 3; 172-178
    2299-8624
    Pojawia się w:
    Advances in Science and Technology. Research Journal
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    What is not clear in fuzzy control systems?
    Autorzy:
    Piegat, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/908467.pdf
    Data publikacji:
    2006
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    sterowanie rozmyte
    system rozmyty
    arytmetyka rozmyta
    logika rozmyta
    możliwość
    fuzzy control
    fuzzy systems
    fuzzy arithmetic
    fuzzy logic
    necessity
    possibility
    Opis:
    The paper presents a number of unclear, unsolved or partly solved problems of fuzzy logic, which hinder precise transformation of expert knowledge about proper control of a plant in a fuzzy controller. These vague problems comprise the realization of logical and arithmetic operations and another basic problem, i.e., the construction of membership functions. The paper also indicates how some of the above problems can be solved.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2006, 16, 1; 37-49
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Improving the Generalization Ability of Neuro-Fuzzy Systems by e-Insensitive Learning
    Autorzy:
    Łęski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/908037.pdf
    Data publikacji:
    2002
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    informatyka
    fuzzy systems
    neural networks
    tolerant learning
    generalization control
    robust methods
    Opis:
    A new learning method tolerant of imprecision is introduced and used in neuro-fuzzy modelling. The proposed method makes it possible to dispose of an intrinsic inconsistency of neuro-fuzzy modelling, where zero-tolerance learning is used to obtain a fuzzy model tolerant of imprecision. This new method can be called e-insensitive learning, where, in order to fit the fuzzy model to real data, the e-insensitive loss function is used. e-insensitive learning leads to a model with minimal Vapnik-Chervonenkis dimension, which results in an improved generalization ability of this system. Another advantage of the proposed method is its robustness against outliers. This paper introduces two approaches to solving e-insensitive learning problem. The first approach leads to a quadratic programming problem with bound constraints and one linear equality constraint. The second approach leads to a problem of solving a system of linear inequalities. Two computationally efficient numerical methods for e-insensitive learning are proposed. Finally, examples are given to demonstrate the validity of the introduced methods.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2002, 12, 3; 437-447
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Soft computing in model-based predictive control
    Autorzy:
    Tatjewski, P.
    Ławryńczuk, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/908473.pdf
    Data publikacji:
    2006
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    sterowanie procesami
    sterowanie predykcyjne
    system nieliniowy
    system rozmyty
    sieć neuronowa
    process control
    model predictive control
    nonlinear systems
    fuzzy systems
    neural networks
    Opis:
    The application of fuzzy reasoning techniques and neural network structures to model-based predictive control (MPC) is studied. First, basic structures of MPC algorithms are reviewed. Then, applications of fuzzy systems of the Takagi-Sugeno type in explicit and numerical nonlinear MPC algorithms are presented. Next, many techniques using neural network modeling to improve structural or computational properties of MPC algorithms are presented and discussed, from a neural network model of a process in standard MPC structures to modeling parts or entire MPC controllers with neural networks. Finally, a simulation example and conclusions are given.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2006, 16, 1; 7-26
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Robustifying analysis of the direct adaptive control of unknown multivariable nonlinear systems based on a new neuro-fuzzy method
    Autorzy:
    Theodoridis, D. C.
    Boutalis, Y.S.
    Christodoulou, M. A.
    Powiązania:
    https://bibliotekanauki.pl/articles/91598.pdf
    Data publikacji:
    2011
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    nonlinear systems
    control
    neuro-fuzzy dynamical system
    fuzzy systems
    FS
    fuzzy recurrent high order neural network
    F-RHONN
    adaptive regulator
    parameter
    “Hopping”
    “Modified Hopping”
    modeling errors
    asymptotic regulation
    Opis:
    In this paper, we are dealing with the problem of directly regulating unknown multivariable affine in the control nonlinear systems and its robustness analysis. The method employs a new Neuro-Fuzzy Dynamical System definition, which uses the concept of Fuzzy Systems (FS) operating in conjunction with High Order Neural Networks. In this way the unknown plant is modeled by a fuzzy - recurrent high order neural network structure (F-RHONN), which is of the known structure considering the neglected nonlinearities. The development is combined with a sensitivity analysis of the closed loop in the presence of modeling imperfections and provides a comprehensive and rigorous analysis showing that our adaptive regulator can guarantee the convergence of states to zero or at least uniform ultimate boundedness of all signals in the closed loop when a not-necessarily-known modeling error is applied. The existence and boundedness of the control signal is always assured by employing a method of parameter “Hopping” and “Modified Hopping”, which appears in the weight updating laws. Simulations illustrate the potency of the method showing that by following the proposed procedure one can obtain asymptotic regulation despite the presence of modeling errors. Comparisons are also made to simple recurrent high order neural network (RHONN) controllers, showing that our approach is superior to the case of simple RHONN’s.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2011, 1, 1; 59-79
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Szybkie prototypowanie sterownika rozmytego dla robota mobilnego
    Rapid prototyping of the fuzzy controller for a mobile robot
    Autorzy:
    Przystałka, P.
    Poloczek, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/155289.pdf
    Data publikacji:
    2013
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    robotyka mobilna
    szybkie prototypowanie systemów sterowania
    systemy rozmyte
    nawigacja robotów mobilnych
    mobile robotics
    rapid prototyping of control systems
    fuzzy systems
    mobile robot navigation
    Opis:
    W artykule przedstawiono zastosowanie techniki szybkiego prototypowania podczas realizacji sterownika rozmytego do unikania kolizji robota mobilnego z przeszkodami. Opisano w jaki sposób można wykorzystać w tym celu środowiska Microsoft® Robotics Developer Studio (MRDS) oraz MATLAB®. Artykuł zawiera badania weryfikacyjne różnych przykładów implementacji sterownika rozmytego. Otrzymane wyniki testów potwierdzają poprawność zaproponowanego podejścia.
    The paper deals with the application of the rapid prototyping technique for control system modeling. The proposed methodology is applied to creating a fuzzy controller that can be used to avoid collisions of a wheeled mobile robot with obstacles. In the paper there is described how to combine and apply two well-known development environments, that is, Microsoft® Robotics Developer Studio and MATLAB® software for rapid prototyping purposes. Important components of the proposed framework such as Visual Programming Language, Visual Simulation Environment and Fuzzy Logic Toolbox are briefly discussed. The main part of the paper focuses on the implementation of a few variants of the fuzzy controller for managing the robot movements in the virtual world (Tab. 1). These controllers differ from each other in such properties as the type of a distance sensor and the number of rules included in the fuzzy knowledge base. The merits and limits of the elaborated solution are considered taking into account the results obtained during verification tests. These experiments were carried out with the use of several environments of different complexity. The results of the verification tests which are included in Tab. 2 show the effectiveness of the proposed approach.
    Źródło:
    Pomiary Automatyka Kontrola; 2013, R. 59, nr 12, 12; 1275-1278
    0032-4140
    Pojawia się w:
    Pomiary Automatyka Kontrola
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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