952 resultados para orthonormal basis functions (OBF)
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Model Predictive Control (MPC) is a control method that solves in real time an optimal control problem over a finite horizon. The finiteness of the horizon is both the reason of MPC's success and its main limitation. In operational water resources management, MPC has been in fact successfully employed for controlling systems with a relatively short memory, such as canals, where the horizon length is not an issue. For reservoirs, which have generally a longer memory, MPC applications are presently limited to short term management only. Short term reservoir management can be effectively used to deal with fast process, such as floods, but it is not capable of looking sufficiently ahead to handle long term issues, such as drought. To overcome this limitation, we propose an Infinite Horizon MPC (IH-MPC) solution that is particularly suitable for reservoir management. We propose to structure the input signal by use of orthogonal basis functions, therefore reducing the optimization argument to a finite number of variables, and making the control problem solvable in a reasonable time. We applied this solution for the management of the Manantali Reservoir. Manantali is a yearly reservoir located in Mali, on the Senegal river, affecting water systems of Mali, Senegal, and Mauritania. The long term horizon offered by IH-MPC is necessary to deal with the strongly seasonal climate of the region.
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Neste trabalho é dado ênfase à inclusão das incertezas na avaliação do comportamento estrutural, objetivando uma melhor representação das características do sistema e uma quantificação do significado destas incertezas no projeto. São feitas comparações entre as técnicas clássicas existentes de análise de confiabilidade, tais como FORM, Simulação Direta Monte Carlo (MC) e Simulação Monte Carlo com Amostragem por Importância Adaptativa (MCIS), e os métodos aproximados da Superfície de Resposta( RS) e de Redes Neurais Artificiais(ANN). Quando possível, as comparações são feitas salientando- se as vantagens e inconvenientes do uso de uma ou de outra técnica em problemas com complexidades crescentes. São analisadas desde formulações com funções de estado limite explícitas até formulações implícitas com variabilidade espacial de carregamento e propriedades dos materiais, incluindo campos estocásticos. É tratado, em especial, o problema da análise da confiabilidade de estruturas de concreto armado incluindo o efeito da variabilidade espacial de suas propriedades. Para tanto é proposto um modelo de elementos finitos para a representação do concreto armado que incorpora as principais características observadas neste material. Também foi desenvolvido um modelo para a geração de campos estocásticos multidimensionais não Gaussianos para as propriedades do material e que é independente da malha de elementos finitos, assim como implementadas técnicas para aceleração das avaliações estruturais presentes em qualquer das técnicas empregadas. Para o tratamento da confiabilidade através da técnica da Superfície de Resposta, o algoritmo desenvolvido por Rajashekhar et al(1993) foi implementado. Já para o tratamento através de Redes Neurais Artificias, foram desenvolvidos alguns códigos para a simulação de redes percéptron multicamada e redes com função de base radial e então implementados no algoritmo de avaliação de confiabilidade desenvolvido por Shao et al(1997). Em geral, observou-se que as técnicas de simulação tem desempenho bastante baixo em problemas mais complexos, sobressaindo-se a técnica de primeira ordem FORM e as técnicas aproximadas da Superfície de Resposta e de Redes Neurais Artificiais, embora com precisão prejudicada devido às aproximações presentes.
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This work proposes a model to investigate the use of a cylindrical antenna used in the thermal method of recovering through electromagnetic radiation of high-viscosity oil. The antenna has a simple geometry, adapted dipole type, and it can be modelled by using Maxwell s equation. The wavelet transforms are used as basis functions and applied in conjunction with the method of moments to obtain the current distribution in the antenna. The electric field, power and temperature distribution are carefully calculated for the analysis of the antenna as electromagnetic heating. The energy performance is analyzed based on thermo-fluid dynamic simulations at field scale, and through the adaptation in the Steam Thermal and Advanced Processes Reservoir Simulator (STARS) by Computer Modelling Group (CMG). The model proposed and the numerical results obtained are stable and presented good agreement with the results reported in the specialized literature
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This work consists in the development of a theoretical and numerical analysis for frequency selective surfaces (FSS) structures with conducting patch elements, such as rectangular patches, thin dipoles and cross dipoles, on anisotropic dielectric substrates. The analysis is developed for millimeter wave band applications. The analytical formulation is developed in the spectral domain, by using a rigorous technique known as equivalent transmission line method, or immitance approach. The numerical analysis is completed through the use of the Galerkin's technique in the Fourier transform domain, using entire-domain basis functions. In the last decades, several sophisticated analytical techniques have been developed for FSS structure applications. Within these applications, it can be emphasized the use of FSS structures on reflecting antennas and bandpass radomes. In the analysis, the scattered fields of the FSS geometry are related to the surface induced currents on the conducting patches. After the formulation of the scattering problem, the numerical solution is obtained by using the moment method. The choice of the basis functions plays a very important role in the numerical efficiency of the numerical method, once they should provide a very good approximation to the real current distributions on the FSS analyzed structure. Thereafter, the dyadic Green's function components are obtained in order to evaluate the basis functions unknown coefficients. To accomplish that, the Galerkin's numerical technique is used. Completing the formulation, the incident fields are determined through the incident potential, and as a consequence the FSS transmission and reflection characteristics are determined, as function of the resonant frequency and structural parameters. The main objective of this work was to analyze FSS structures with conducting patch elements, such as thin dipoles, cross dipoles and rectangular patches, on anisotropic dielectric substrates, for high frequency applications. Therefore, numerical results for the FSS structure main characteristics were obtained in the millimeter wave bando Some of these FSS characteristics are the resonant
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This work presents a theoretical and numerical analysis of Frequency Selective Surfaces (FSS) with elements as rectangular patch, thin dipole and crossed dipole mounted on uniaxial anisotropic dielectric substrate layers for orientations of the optical axis along x, y and z directions. The analysis of these structures is accomplished by combination of the Hertz vector potentials method and the Galerkin's technique, in the Fourier transform-domain, using entire¬domain basis functions. This study consists in the use of one more technique for analysis of FSS on anisotropic dielectric substrate. And presents as the main contribution the introduction of one more project parameter to determinate the transmission and reflection characteristics of periodic structures, from the use of anisotropic dielectric with orientations of the crystal optical axis along x, y and z directions. To validate this analysis, the numerical results of this work are compared to those obtained by other authors, for FSS structures on anisotropic and isotropic dielectric substrates. Also are compared experimental results and the numerical correspondent ones for the FSS isotropic case. The technique proposed in this work is accurate and efficient. ln a second moment, curves are presented for the transmission and reflection characteristics of the FSS structures using conducting patch elements mounted on uniaxial anisotropic dielectric substrate layers with optical axis oriented along x, y and z directions. From analysis of these curves, the performance of the considered FSS structures as function of the optical axis orientation is described
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This study aims to seek a more viable alternative for the calculation of differences in images of stereo vision, using a factor that reduces heel the amount of points that are considered on the captured image, and a network neural-based radial basis functions to interpolate the results. The objective to be achieved is to produce an approximate picture of disparities using algorithms with low computational cost, unlike the classical algorithms
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The present work describes the use of a mathematical tool to solve problems arising from control theory, including the identification, analysis of the phase portrait and stability, as well as the temporal evolution of the plant s current induction motor. The system identification is an area of mathematical modeling that has as its objective the study of techniques which can determine a dynamic model in representing a real system. The tool used in the identification and analysis of nonlinear dynamical system is the Radial Basis Function (RBF). The process or plant that is used has a mathematical model unknown, but belongs to a particular class that contains an internal dynamics that can be modeled.Will be presented as contributions to the analysis of asymptotic stability of the RBF. The identification using radial basis function is demonstrated through computer simulations from a real data set obtained from the plant
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This work presents a theoretical analysis and numerical and experimental results of the scattering characteristics of frequency selective surfaces, using elements of type patch perfectly conductor. The structures are composed of two frequency selective surfaces on isotropic dielectric substrates cascaded, separated by a layer of air. The analysis is performed using the method of equivalent transmission line in combination with the Galerkin method, to determine the transmission and reflection characteristics of the structures analyzed. Specifically, the analysis uses the impedance method, which models the structure by an equivalent circuit, and applies the theory of transmission lines to determine the dyadic Green's function for the cascade structure. This function relates the incident field and surface current densities. These fields are determined algebraically by means of potential incidents and the imposition of the continuity of the fields in the dielectric interfaces. The Galerkin method is applied to the numerical determination of the unknown weight coefficients and hence the unknown densities of surface currents, which are expanded in terms of known basis functions multiplied by these weight coefficients. From the determination of these functions, it becomes possible to obtain numerical scattered fields at the top and bottom of the structures and characteristics of transmission and reflection of these structures. At work, we present numerical and experimental results for the characteristics of transmission and reflection. Comparisons were made with other results presented in literature, and it was observed a good agreement in the cases presented suggestions continuity of the work are presented
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An alternative nonlinear technique for decoupling and control is presented. This technique is based on a RBF (Radial Basis Functions) neural network and it is applied to the synchronous generator model. The synchronous generator is a coupled system, in other words, a change at one input variable of the system, changes more than one output. The RBF network will perform the decoupling, separating the control of the following outputs variables: the load angle and flux linkage in the field winding. This technique does not require knowledge of the system parameters and, due the nature of radial basis functions, it shows itself stable to parametric uncertainties, disturbances and simpler when it is applied in control. The RBF decoupler is designed in this work for decouple a nonlinear MIMO system with two inputs and two outputs. The weights between hidden and output layer are modified online, using an adaptive law in real time. The adaptive law is developed by Lyapunov s Method. A decoupling adaptive controller uses the errors between system outputs and model outputs, and filtered outputs of the system to produce control signals. The RBF network forces each outputs of generator to behave like reference model. When the RBF approaches adequately control signals, the system decoupling is achieved. A mathematical proof and analysis are showed. Simulations are presented to show the performance and robustness of the RBF network
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This dissertation presents a new proposal for the Direction of Arrival (DOA) detection problem for more than one signal inciding simultaneously on an antennas array with linear or planar geometry by using intelligent algorithms. The DOA estimator is developed by using techniques of Conventional Beam-forming (CBF), Blind Source Separation (BSS), and the neural estimator MRBF (Modular Structure of Radial Basis Functions). The developed MRBF estimator has its capacity extended due to the interaction with the BSS technique. The BSS makes an estimation of the steering vectors of the multiple plane waves that reach the array in the same frequency, that means, obtains to separate mixed signals without information a priori. The technique developed in this work makes possible to identify the multiple sources directions and to identify and to exclude interference sources
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This work describes the development of a nonlinear control strategy for an electro-hydraulic actuated system. The system to be controlled is represented by a third order ordinary differential equation subject to a dead-zone input. The control strategy is based on a nonlinear control scheme, combined with an artificial intelligence algorithm, namely, the method of feedback linearization and an artificial neural network. It is shown that, when such a hard nonlinearity and modeling inaccuracies are considered, the nonlinear technique alone is not enough to ensure a good performance of the controller. Therefore, a compensation strategy based on artificial neural networks, which have been notoriously used in systems that require the simulation of the process of human inference, is used. The multilayer perceptron network and the radial basis functions network as well are adopted and mathematically implemented within the control law. On this basis, the compensation ability considering both networks is compared. Furthermore, the application of new intelligent control strategies for nonlinear and uncertain mechanical systems are proposed, showing that the combination of a nonlinear control methodology and artificial neural networks improves the overall control system performance. Numerical results are presented to demonstrate the efficacy of the proposed control system
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Oil prospecting is one of most complex and important features of oil industry Direct prospecting methods like drilling well logs are very expensive, in consequence indirect methods are preferred. Among the indirect prospecting techniques the seismic imaging is a relevant method. Seismic method is based on artificial seismic waves that are generated, go through the geologic medium suffering diffraction and reflexion and return to the surface where they are recorded and analyzed to construct seismograms. However, the seismogram contains not only actual geologic information, but also noise, and one of the main components of the noise is the ground roll. Noise attenuation is essential for a good geologic interpretation of the seismogram. It is common to study seismograms by using time-frequency transformations that map the seismic signal into a frequency space where it is easier to remove or attenuate noise. After that, data is reconstructed in the original space in such a way that geologic structures are shown in more detail. In addition, the curvelet transform is a new and effective spectral transformation that have been used in the analysis of complex data. In this work, we employ the curvelet transform to represent geologic data using basis functions that are directional in space. This particular basis can represent more effectively two dimensional objects with contours and lines. The curvelet analysis maps real space into frequencies scales and angular sectors in such way that we can distinguish in detail the sub-spaces where is the noise and remove the coefficients corresponding to the undesired data. In this work we develop and apply the denoising analysis to remove the ground roll of seismograms. We apply this technique to a artificial seismogram and to a real one. In both cases we obtain a good noise attenuation
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Expressions for the Baker-Akhiezer function and their logarithmic space and time derivatives are derived in terms of the matrix elements of U - V matrices and 'squared basis functions'. These expressions generalize the well known formulas for the KdV equation case and establish links between different forms of the Whitham averaging procedure.
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A narrow S-wave resonance has been found in the positron-helium system at about 30 eV, using the close-coupling approach, in excitation and rearrangement cross sections to He(1s2s), He(1s2p), Ps(1s) and Ps(2s) states by employing different combinations of the following basis functions: He(1s1s), He(1s2s), He(1s2p), Ps(1s) and Ps(2s), where Ps stands for the positronium atom.