1000 resultados para Sistemas lineares. Determinantes. Matrizes
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Versão com menu acessível para leitores de tela e vídeo com audiodescrição.
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O professor apresenta o que são vetores e matrizes na linguagem de programação Java e ilustra como utilizar vetores e matrizes na linguagem Java.
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Este trabalho compara as soluções disponibilizadas pelos sistemas Derive 5.0, Maple 6 e Mathematica 4.0 para problemas que encontramos no ensino secundário e também nos primeiros anos da universidade. Procuramos destacar os aspectos distintos entre cada um dos programas ao mesmo tempo que fazemos referência aos pontos em que tudo se passa de forma semelhante. Esta dissertação aborda o cálculo numérico, o cálculo simbólico, a programação e os gráficos. Para cada um dos assuntos é estudada a forma como se podem resolver os problemas através dos três sistemas comparando-se estas soluções. Inicialmente, é feita uma abordagem que permite ao utilizador adquirir os conhecimentos básicos acerca dos diversos programas. Tratamos de seguida de algumas questões relacionadas com o cálculo numérico e com algumas funções nomeadamente da Teoria dos Números. Referimos listas e funções e são analisadas diversas formas de manipular listas e os seus elementos bem como algumas áreas da Análise Matemática das quais destacamos as equações, a derivação e a integração compreendendo cálculo numérico e cálculo simbólico. Examinamos um vasto conjunto de operações definidas sobre matrizes (representadas como listas de listas) e polinómios que abrangem as operações mais comuns de cada um dos campos. Analisamos também a programação recursiva, a programação imperativa, a programação funcional e a programação por regras de reescrita. A abordagem aqui adoptada foi a de fornecer ao utilizador as construções chave mais importantes que cada paradigma de programação utiliza bem como as informações básicas acerca do funcionamento de cada uma delas de modo a permitir a resolução dos problemas propostos. Por último os gráficos sobre os quais incidiu a nossa análise foram os de uma e de duas variáveis representados no referencial cartesiano, gráficos estes que são os mais utilizados quer ao nível do ensino superior quer ao nível do ensino secundário. A qualidade e a facilidade de obter rapidamente as representações dão outra dimensão ao estudo dos gráficos principalmente quando estamos a falar de gráficos a três dimensões. A ideia de animação gráfica é também aqui abordada sendo evidente os benefícios da utilização da mesma nos programas em que é possível efectuá-la. Concluímos que na programação o Mathematica destaca-se em relação aos demais o mesmo se passando no Maple no respeitante à representação gráfica. O Derive permite que durante o contacto inicial seja mais fácil trabalhar e aprender a linguagem própria.
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Na unfolding method of linear intercept distributions and secction área distribution was implemented for structures with spherical grains. Although the unfolding routine depends on the grain shape, structures with spheroidal grains can also be treated by this routine. Grains of non-spheroidal shape can be treated only as approximation. A software was developed with two parts. The first part calculates the probability matrix. The second part uses this matrix and minimizes the chi-square. The results are presented with any number of size classes as required. The probability matrix was determined by means of the linear intercept and section area distributions created by computer simulation. Using curve fittings the probability matrix for spheres of any sizes could be determined. Two kinds of tests were carried out to prove the efficiency of the Technique. The theoretical tests represent ideal cases. The software was able to exactly find the proposed grain size distribution. In the second test, a structure was simulated in computer and images of its slices were used to produce the corresponding linear intercept the section area distributions. These distributions were then unfolded. This test simulates better reality. The results show deviations from the real size distribution. This deviations are caused by statistic fluctuation. The unfolding of the linear intercept distribution works perfectly, but the unfolding of section area distribution does not work due to a failure in the chi-square minimization. The minimization method uses a matrix inversion routine. The matrix generated by this procedure cannot be inverted. Other minimization method must be used
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The decomposition process exercises an extensive control over the carbon cycle, affecting its availability and nutrient cycling in terrestrial ecosystems. The understanding of leaf decomposition patterns above the soil and fine roots decomposition below the soil is necessary and essential to identify and quantify more accurately the flow of energy and matter in forest systems. There is still a lack of studies and a large gap in the knowledge about what environmental variables act as local determinants over decomposition drivers. The knowledge about the decomposition process is still immature for Brazilian semiarid region. The aim of this study was to analyze the decomposition process (on leaves and fine roots) of a mixture of three native species for 12 months in a semiarid ecosystem in Northeast Brazil. We also examined whether the rate of decomposition can be explained by local environmental factors, specifically plant species richness, plant density and biomass, soil macro-arthropods species richness and abundance, amount of litterfall and fine root stock. Thirty sampling points were randomly distributed within an area of 2000 m x 500 m. To determine the decomposition rate, the litterbag technique was used and the data analysis were made with multiple regressions. There was a high degradation of dead organic matter along the experiment. Above ground plant biomass was the only environmental local factor significantly related to leaf decomposition. The density of vegetation and litter production were positively and negatively related to decay rates of fine roots, respectively. The results suggest that Caatinga spatial heterogeneity may exert strong influences over the decomposition process, taking into account the action of environmental factors related to organic matter exposure of and the consequent action of solar radiation as the decomposition process main controller in this region
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Sistema de detecção e isolamento de falhas em sistemas dinâmicos baseado em identificação paramétrica
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The present research aims at contributing to the area of detection and diagnosis of failure through the proposal of a new system architecture of detection and isolation of failures (FDI, Fault Detection and Isolation). The proposed architecture presents innovations related to the way the physical values monitored are linked to the FDI system and, as a consequence, the way the failures are detected, isolated and classified. A search for mathematical tools able to satisfy the objectives of the proposed architecture has pointed at the use of the Kalman Filter and its derivatives EKF (Extended Kalman Filter) and UKF (Unscented Kalman Filter). The use of the first one is efficient when the monitored process presents a linear relation among its physical values to be monitored and its out-put. The other two are proficient in case this dynamics is no-linear. After that, a short comparative of features and abilities in the context of failure detection concludes that the UFK system is a better alternative than the EKF one to compose the architecture of the FDI system proposed in case of processes of no-linear dynamics. The results shown in the end of the research refer to the linear and no-linear industrial processes. The efficiency of the proposed architecture may be observed since it has been applied to simulated and real processes. To conclude, the contributions of this thesis are found in the end of the text
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The usual programs for load flow calculation were in general developped aiming the simulation of electric energy transmission, subtransmission and distribution systems. However, the mathematical methods and algorithms used by the formulations were based, in majority, just on the characteristics of the transmittion systems, which were the main concern focus of engineers and researchers. Though, the physical characteristics of these systems are quite different from the distribution ones. In the transmission systems, the voltage levels are high and the lines are generally very long. These aspects contribute the capacitive and inductive effects that appear in the system to have a considerable influence in the values of the interest quantities, reason why they should be taken into consideration. Still in the transmission systems, the loads have a macro nature, as for example, cities, neiborhoods, or big industries. These loads are, generally, practically balanced, what reduces the necessity of utilization of three-phase methodology for the load flow calculation. Distribution systems, on the other hand, present different characteristics: the voltage levels are small in comparison to the transmission ones. This almost annul the capacitive effects of the lines. The loads are, in this case, transformers, in whose secondaries are connected small consumers, in a sort of times, mono-phase ones, so that the probability of finding an unbalanced circuit is high. This way, the utilization of three-phase methodologies assumes an important dimension. Besides, equipments like voltage regulators, that use simultaneously the concepts of phase and line voltage in their functioning, need a three-phase methodology, in order to allow the simulation of their real behavior. For the exposed reasons, initially was developped, in the scope of this work, a method for three-phase load flow calculation in order to simulate the steady-state behaviour of distribution systems. Aiming to achieve this goal, the Power Summation Algorithm was used, as a base for developping the three phase method. This algorithm was already widely tested and approved by researchers and engineers in the simulation of radial electric energy distribution systems, mainly for single-phase representation. By our formulation, lines are modeled in three-phase circuits, considering the magnetic coupling between the phases; but the earth effect is considered through the Carson reduction. Its important to point out that, in spite of the loads being normally connected to the transformers secondaries, was considered the hypothesis of existence of star or delta loads connected to the primary circuit. To perform the simulation of voltage regulators, a new model was utilized, allowing the simulation of various types of configurations, according to their real functioning. Finally, was considered the possibility of representation of switches with current measuring in various points of the feeder. The loads are adjusted during the iteractive process, in order to match the current in each switch, converging to the measured value specified by the input data. In a second stage of the work, sensibility parameters were derived taking as base the described load flow, with the objective of suporting further optimization processes. This parameters are found by calculating of the partial derivatives of a variable in respect to another, in general, voltages, losses and reactive powers. After describing the calculation of the sensibility parameters, the Gradient Method was presented, using these parameters to optimize an objective function, that will be defined for each type of study. The first one refers to the reduction of technical losses in a medium voltage feeder, through the installation of capacitor banks; the second one refers to the problem of correction of voltage profile, through the instalation of capacitor banks or voltage regulators. In case of the losses reduction will be considered, as objective function, the sum of the losses in all the parts of the system. To the correction of the voltage profile, the objective function will be the sum of the square voltage deviations in each node, in respect to the rated voltage. In the end of the work, results of application of the described methods in some feeders are presented, aiming to give insight about their performance and acuity
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This work develops a robustness analysis with respect to the modeling errors, being applied to the strategies of indirect control using Artificial Neural Networks - ANN s, belong to the multilayer feedforward perceptron class with on-line training based on gradient method (backpropagation). The presented schemes are called Indirect Hybrid Control and Indirect Neural Control. They are presented two Robustness Theorems, being one for each proposed indirect control scheme, which allow the computation of the maximum steady-state control error that will occur due to the modeling error what is caused by the neural identifier, either for the closed loop configuration having a conventional controller - Indirect Hybrid Control, or for the closed loop configuration having a neural controller - Indirect Neural Control. Considering that the robustness analysis is restrict only to the steady-state plant behavior, this work also includes a stability analysis transcription that is suitable for multilayer perceptron class of ANN s trained with backpropagation algorithm, to assure the convergence and stability of the used neural systems. By other side, the boundness of the initial transient behavior is assured by the assumption that the plant is BIBO (Bounded Input, Bounded Output) stable. The Robustness Theorems were tested on the proposed indirect control strategies, while applied to regulation control of simulated examples using nonlinear plants, and its results are presented
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Dados de rebanhos bovinos comerciais foram analisados com o objetivo de estimar as interações dos efeitos genéticos com o ambiente que podem influenciar a avaliação de características de crescimento em rebanhos de animais puros e cruzados. O conjunto de dados analisado foi obtido a partir de animais das raças Hereford, Nelore e seus cruzamentos. As características em estudo foram os pesos à desmama e ao sobreano dos animais. As análises estatísticas foram realizadas pelo método dos quadrados mínimos e o modelo proposto incluiu os efeitos de região, grupo de contemporâneos dentro de região, mês de nascimento e sexo do bezerro, os efeitos lineares e quadráticos para a idade do bezerro e idade da vaca ao parto, ambas analisadas dentro de sexo, e os efeitos de grupo genético e da interação grupo genético × região. de modo geral, o desempenho de todos os grupos genéticos foi influenciado pelo efeito de região. Além disso, observou-se tendência de que o aumento da proporção de genes zebuínos promoveu diminuição na diferença de desempenho entre as regiões. Todos os genótipos foram beneficiados no ambiente menos restritivo, o que indica a existência de interação genótipo-ambiente e comprova a importância de que sistemas de cruzamento sejam realizados de forma a manter a adaptação das matrizes e de seus produtos.
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Wavelet coding is an efficient technique to overcome the multipath fading effects, which are characterized by fluctuations in the intensity of the transmitted signals over wireless channels. Since the wavelet symbols are non-equiprobable, modulation schemes play a significant role in the overall performance of wavelet systems. Thus the development of an efficient design method is crucial to obtain modulation schemes suitable for wavelet systems, principally when these systems employ wavelet encoding matrixes of great dimensions. In this work, it is proposed a design methodology to obtain sub-optimum modulation schemes for wavelet systems over Rayleigh fading channels. In this context, novels signal constellations and quantization schemes are obtained via genetic algorithm and mathematical tools. Numerical results obtained from simulations show that the wavelet-coded systems derived here have very good performance characteristics over fading channels
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This work deals with an on-line control strategy based on Robust Model Predictive Control (RMPC) technique applied in a real coupled tanks system. This process consists of two coupled tanks and a pump to feed the liquid to the system. The control objective (regulator problem) is to keep the tanks levels in the considered operation point even in the presence of disturbance. The RMPC is a technique that allows explicit incorporation of the plant uncertainty in the problem formulation. The goal is to design, at each time step, a state-feedback control law that minimizes a 'worst-case' infinite horizon objective function, subject to constraint in the control. The existence of a feedback control law satisfying the input constraints is reduced to a convex optimization over linear matrix inequalities (LMIs) problem. It is shown in this work that for the plant uncertainty described by the polytope, the feasible receding horizon state feedback control design is robustly stabilizing. The software implementation of the RMPC is made using Scilab, and its communication with Coupled Tanks Systems is done through the OLE for Process Control (OPC) industrial protocol
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Conventional methods to solve the problem of blind source separation nonlinear, in general, using series of restrictions to obtain the solution, often leading to an imperfect separation of the original sources and high computational cost. In this paper, we propose an alternative measure of independence based on information theory and uses the tools of artificial intelligence to solve problems of blind source separation linear and nonlinear later. In the linear model applies genetic algorithms and Rényi of negentropy as a measure of independence to find a separation matrix from linear mixtures of signals using linear form of waves, audio and images. A comparison with two types of algorithms for Independent Component Analysis widespread in the literature. Subsequently, we use the same measure of independence, as the cost function in the genetic algorithm to recover source signals were mixed by nonlinear functions from an artificial neural network of radial base type. Genetic algorithms are powerful tools for global search, and therefore well suited for use in problems of blind source separation. Tests and analysis are through computer simulations
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Electro-hydraulic servo-systems are widely employed in industrial applications such as robotic manipulators, active suspensions, precision machine tools and aerospace systems. They provide many advantages over electric motors, including high force to weight ratio, fast response time and compact size. However, precise control of electro-hydraulic systems, due to their inherent nonlinear characteristics, cannot be easily obtained with conventional linear controllers. Most flow control valves can also exhibit some hard nonlinearities such as deadzone due to valve spool overlap on the passage´s orifice of the fluid. This work describes the development of a nonlinear controller based on the feedback linearization method and including a fuzzy compensation scheme for an electro-hydraulic actuated system with unknown dead-band. Numerical results are presented in order to demonstrate the control system performance
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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