159 resultados para Uncertain nonlinear systems


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Dynamical systems of the billiard type are of fundamental importance for the description of numerous phenomena observed in many different fields of research, including statistical mechanics, Hamiltonian dynamics, nonlinear physics, and many others. This Focus Issue presents the recent progress in this area with contributions from the mathematical as well as physical stand point. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4730155]

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This paper describes a novel approach for mapping lightning processes using fuzzy logic. The core regarding lightning process is to identify and to model those uncertain information on mathematical principles. In fact, the lightning process involves several nonlinear features that our current mathematical tools would not be able to model. The estimation process has been carried out using a fuzzy system based on Sugeno's architecture. Simulation results confirm that proposed approach can be efficiently used in these types of problem.

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Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements. Neural networks with feedback connections provide a computing model capable of solving a rich class of optimization problems. In this paper, a modified Hopfield network is developed for solving constrained nonlinear optimization problems. The internal parameters of the network are obtained using the valid-subspace technique. Simulated examples are presented as an illustration of the proposed approach.

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This article presents a new approach to minimize the losses in electrical power systems. This approach considers the application of the primal-dual logarithmic barrier method to voltage magnitude and tap-changing transformer variables, and the other inequality constraints are treated by augmented Lagrangian method. The Lagrangian function aggregates all the constraints. The first-order necessary conditions are reached by Newton's method, and by updating the dual variables and penalty factors. Test results are presented to show the good performance of this approach.

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The influence of La2O3, Pr2O3 and CeO2 on a new class of polycrystalline ceramics with nonlinear properties based on SnO2, was investigated. La2O3 and Pr2O3 were found to precipitate at the grain boundary region, causing a considerable increase in the nonlinear behavior. It was found that CeO2 forms a solid solution in the bulk but. unlike La2O3 and Pr2O3, it does not increase the nonlinear behavior. A higher nonlinear coefficient of similar to80 was obtained for La2O3-doped SnO2-based systems. (C) 2002 Elsevier B.V. B.V. All rights reserved.

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This work illustrates the advancement of research on TiO2-based electroceramics. In this work will be presented that the addition of different dopants, as well as thermal treatments at oxidizing and inert atmosphere, influences of the densification, the mean grain size and the electrical properties of the TiO2-based varistor ceramics. Dopants like Ta2O5, Nb2O5, and Cr2O3 have an especial role in the barrier formation at the grain boundary in the TiO2 varistors, increasing the nonlinear coefficient and decreasing the breakdown electric field. The influence of Cr'(Ti) is to increase the O' and O'(2) adsorption at the grain boundary interface and to promote a decrease in the conductivity by donating electrons to O-2 adsorbed at the grain boundary. In this paper, TiO2 and (Sn,Ti)O-2-based studies of polycrystalline ceramics, which show a non-linear I-V electrical response typical of low voltage varistor systems are also presented. All these systems are potentially promising for varistor applications. (C) 2004 Kluwer Academic Publishers.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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In this paper we get some lower bounds for the number of critical periods of families of centers which are perturbations of the linear one. We give a method which lets us prove that there are planar polynomial centers of degree l with at least 2[(l - 2)/2] critical periods as well as study concrete families of potential, reversible and Lienard centers. This last case is studied in more detail and we prove that the number of critical periods obtained with our approach does not. increases with the order of the perturbation. (C) 2007 Elsevier Ltd. All rights reserved.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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In this study we consider the SIS epidemiological model (susceptible-infected-susceptible) in which the transmission and recuperation rates are considered fuzzy sets. The concepts of possibility measures and fuzzy expectancy value are used to obtain the basic reproduction value for infected groups with different viral charge.

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Here we present two-phase flow nonlinear parameter estimation for HFC's flow through capillary tube-suction line heat exchangers, commonly used as expansion devices in small refrigeration systems. The simplifying assumptions adopted are: steady state, pure refrigerant, one-dimensional flow, negligible axial heat conduction in the fluid, capillary tube and suction line walls. Additionally, it is considered that the refrigerant is free from oil and both phases are assumed to be at the same pressure, that is, surface tension effects are neglected. Metastable flow effects are also disregarded, and the vapor is assumed to be saturated at the local pressure. The so-called homogeneous model, involving three, first order, ordinary differential equations is applied to analyze the two-phase flow region. Comparison is done with experimental measurements of the mass flow rate and temperature distribution along capillary tubes working with refrigerant HFC-134a in different operating conditions.

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Predictability is related to the uncertainty in the outcome of future events during the evolution of the state of a system. The cluster weighted modeling (CWM) is interpreted as a tool to detect such an uncertainty and used it in spatially distributed systems. As such, the simple prediction algorithm in conjunction with the CWM forms a powerful set of methods to relate predictability and dimension.