930 resultados para Cargas não-lineares
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Com o objetivo de obter uma equação que, por meio de parâmetros lineares dimensionais das folhas, permita a estimativa da área foliar de Brachiaria plantaginea, estudaram-se relações entre a área foliar real (Sf) e os parâmetros dimensionais do limbo foliar, como o comprimento ao longo da nervura principal (C) e a largura máxima (L), perpendicular à nervura principal. As equações lineares simples, exponenciais e geométricas obtidas podem ser usadas para estimação da área foliar do capim-marmelada. do ponto de vista prático, deve-se optar pela equação linear simples, envolvendo o produto C x L, usando-se a equação de regressão Sf = 0,7338 x (C x L), o que equivale a tomar 73,38% do produto entre o comprimento ao longo da nervura principal e a largura máxima, com um coeficiente de determinação de 0,8754.
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Com o objetivo de obter uma equação que, por meio de parâmetros lineares dimensionais das folhas, permitisse a estimativa da área foliar de Ipomoea hederifolia e Ipomoea nil, estudaram-se correlações entre a área foliar real (Sf) e os parâmetros dimensionais do limbo foliar, como o comprimento ao longo da nervura principal (C) e a largura máxima (L), perpendicular à nervura principal. Todas as - equações exponenciais, geométricas ou lineares simples - permitiram boas estimativas da área foliar. do ponto de vista prático, sugere-se optar pela equação linear simples envolvendo o produto C x L, considerando-se o coeficiente linear igual a zero. Desse modo, a estimativa da área foliar de I. hederifolia pode ser feita pela fórmula Sf = 0,7583 x (C x L), ou seja, 75,83% do produto entre o comprimento ao longo da nervura principal e a largura máxima, ao passo que, para I. nil, a estimativa da área foliar pode ser feita pela fórmula Sf = 0,6122 x (C x L), ou seja, 61,22% do produto entre o comprimento ao longo da nervura principal e a largura máxima da folha.
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A estimativa da área foliar pode auxiliar na compreensão de relações de interferência entre plantas daninhas e cultivadas. Com o objetivo de obter uma equação que, por meio de parâmetros lineares dimensionais das folhas, permita a estimativa da área foliar de Sida cordifolia e Sida rhombifolia, estudaram-se as correlações entre área foliar real (Af) e parâmetros dimensionais do limbo foliar, como o comprimento (C) ao longo da nervura principal e a largura máxima (L) perpendicular à nervura principal. Foram analisados 200 limbos foliares de cada espécie, coletados em diferentes agroecossistemas na Universidade Estadual Paulista, campus de Jaboticabal. Os modelos estatísticos utilizados foram linear: Y = a + bx; linear simples: Y = bx; geométrico: Y = ax b; e exponencial: Y = ab x. Todos os modelos analisados podem ser empregados para estimação da área foliar de S. cordifolia e S. rhombifolia. Sugere-se optar pela equação linear simples, envolvendo o produto C*L, considerando-se o coeficiente linear igual a zero, em função da praticidade desta. Desse modo, a estimativa da área foliar de S. cordifolia pode ser obtida pela fórmula Af = 0,7878*(C*L), com coeficiente de determinação de 0,9307, enquanto para S. rhombifolia a estimativa da área foliar pode ser obtida pela fórmula Af = 0,6423*(C*L), com coeficiente de determinação de 0,9711.
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Com o objetivo de obter uma equação que, através de parâmetros lineares dimensionais das folhas, permita a estimativa da área foliar de Typha latifolia, estudaram-se relações entre a área foliar real (Sf) e parâmetros dimensionais do limbo foliar, como o comprimento ao longo da nervura principal (C) e a largura máxima (L), perpendicular à nervura principal. As equações lineares simples, exponenciais e geométricas obtidas podem ser usadas para estimação da área foliar da taboa. do ponto de vista prático, sugere-se optar pela equação linear simples que envolve o produto C x L, usando-se a equação de regressão Sf = 0,9651 x (C x L), que equivale a tomar 96,51% do produto entre o comprimento ao longo da nervura principal e a largura máxima, com um coeficiente de determinação de 0,9411.
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Com o objetivo de obter uma equação que, através de parâmetros lineares dimensionais das folhas, permita a estimativa da área foliar de Tridax procumbens, estudaram-se relações entre a área foliar real (Sf) e os parâmetros dimensionais do limbo foliar, como o comprimento ao longo da nervura principal (C) e a largura máxima (L), perpendicular à nervura principal. As equações lineares simples, exponenciais e geométricas obtidas podem ser usadas para estimação da área foliar da erva-de-touro. do ponto de vista prático, sugere-se optar pela equação linear simples envolvendo o produto C x L, usando-se a equação de regressão Sf = 0,6008 x (C x L), que equivale a tomar 60,08% do produto entre o comprimento ao longo da nervura principal e a largura máxima, com um coeficiente de determinação de 0,8731.
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Esta pesquisa teve como objetivo obter uma equação, por meio de medidas lineares dimensionais das folhas, que permitisse a estimativa da área foliar de Momordica charantia e Pyrostegia venusta. Entre maio e dezembro de 2007, foram estudadas as correlações entre a área folia real (Sf) e as medidas dimensionais do limbo foliar, como o comprimento ao longo da nervura principal (C) e a largura máxima (L) perpendicular à nervura principal. Todas as equações, exponenciais geométricas ou lineares simples, permitiram boas estimativas da área foliar. do ponto de vista prático, sugere-se optar pela equação linear simples envolvendo o produto C x L, considerando-se o coeficiente linear igual a zero. Desse modo, a estimativa da área foliar de Momordica charantia pode ser feita pela fórmula Sf = 0,4963 x (C x L), e a de Pyrostegia venusta, por Sf = 0,6649 x (C x L).
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O sucesso de implantação de uma cultura pode ser garantido por uma semeadura bem realizada, e as rodas compactadoras utilizadas nessa operação devem ser capazes de melhorar o contato solo-semente para promover boa emergência das plântulas. O objetivo deste trabalho foi estudar a influência de três modelos de rodas compactadoras, três profundidades de semeadura e três níveis de carga sobre a roda compactadora na germinação e no desenvolvimento da cultura do milho, em uma pista de ensaios projetada para essa finalidade, no município de Uberaba - MG, em Latossolo Vermelho distrófico, textura média. O delineamento experimental utilizado foi o de parcelas subsubdivididas, com 27 tratamentos e quatro repetições. Os resultados obtidos evidenciaram que a profundidade de semeadura foi o fator que mais afetou o desenvolvimento vegetativo da cultura do milho no estádio 2, enquanto no estádio 4 nenhum dos fatores afetou as medidas de desenvolvimento da cultura.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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This paper presents a new multi-model technique of dentification in ANFIS for nonlinear systems. In this technique, the structure used is of the fuzzy Takagi-Sugeno of which the consequences are local linear models that represent the system of different points of operation and the precursors are membership functions whose adjustments are realized by the learning phase of the neuro-fuzzy ANFIS technique. The models that represent the system at different points of the operation can be found with linearization techniques like, for example, the Least Squares method that is robust against sounds and of simple application. The fuzzy system is responsible for informing the proportion of each model that should be utilized, using the membership functions. The membership functions can be adjusted by ANFIS with the use of neural network algorithms, like the back propagation error type, in such a way that the models found for each area are correctly interpolated and define an action of each model for possible entries into the system. In multi-models, the definition of action of models is known as metrics and, since this paper is based on ANFIS, it shall be denominated in ANFIS metrics. This way, ANFIS metrics is utilized to interpolate various models, composing a system to be identified. Differing from the traditional ANFIS, the created technique necessarily represents the system in various well defined regions by unaltered models whose pondered activation as per the membership functions. The selection of regions for the application of the Least Squares method is realized manually from the graphic analysis of the system behavior or from the physical characteristics of the plant. This selection serves as a base to initiate the linear model defining technique and generating the initial configuration of the membership functions. The experiments are conducted in a teaching tank, with multiple sections, designed and created to show the characteristics of the technique. The results from this tank illustrate the performance reached by the technique in task of identifying, utilizing configurations of ANFIS, comparing the developed technique with various models of simple metrics and comparing with the NNARX technique, also adapted to identification
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Most algorithms for state estimation based on the classical model are just adequate for use in transmission networks. Few algorithms were developed specifically for distribution systems, probably because of the little amount of data available in real time. Most overhead feeders possess just current and voltage measurements at the middle voltage bus-bar at the substation. In this way, classical algorithms are of difficult implementation, even considering off-line acquired data as pseudo-measurements. However, the necessity of automating the operation of distribution networks, mainly in regard to the selectivity of protection systems, as well to implement possibilities of load transfer maneuvers, is changing the network planning policy. In this way, some equipments incorporating telemetry and command modules have been installed in order to improve operational features, and so increasing the amount of measurement data available in real-time in the System Operation Center (SOC). This encourages the development of a state estimator model, involving real-time information and pseudo-measurements of loads, that are built from typical power factors and utilization factors (demand factors) of distribution transformers. This work reports about the development of a new state estimation method, specific for radial distribution systems. The main algorithm of the method is based on the power summation load flow. The estimation is carried out piecewise, section by section of the feeder, going from the substation to the terminal nodes. For each section, a measurement model is built, resulting in a nonlinear overdetermined equations set, whose solution is achieved by the Gaussian normal equation. The estimated variables of a section are used as pseudo-measurements for the next section. In general, a measurement set for a generic section consists of pseudo-measurements of power flows and nodal voltages obtained from the previous section or measurements in real-time, if they exist -, besides pseudomeasurements of injected powers for the power summations, whose functions are the load flow equations, assuming that the network can be represented by its single-phase equivalent. The great advantage of the algorithm is its simplicity and low computational effort. Moreover, the algorithm is very efficient, in regard to the accuracy of the estimated values. Besides the power summation state estimator, this work shows how other algorithms could be adapted to provide state estimation of middle voltage substations and networks, namely Schweppes method and an algorithm based on current proportionality, that is usually adopted for network planning tasks. Both estimators were implemented not only as alternatives for the proposed method, but also looking for getting results that give support for its validation. Once in most cases no power measurement is performed at beginning of the feeder and this is required for implementing the power summation estimations method, a new algorithm for estimating the network variables at the middle voltage bus-bar was also developed
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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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Este trabalho propõe um ambiente computacional aplicado ao ensino de sistemas de controle, denominado de ModSym. O software implementa uma interface gráfica para a modelagem de sistemas físicos lineares e mostra, passo a passo, o processamento necessário à obtenção de modelos matemáticos para esses sistemas. Um sistema físico pode ser representado, no software, de três formas diferentes. O sistema pode ser representado por um diagrama gráfico a partir de elementos dos domínios elétrico, mecânico translacional, mecânico rotacional e hidráulico. Pode também ser representado a partir de grafos de ligação ou de diagramas de fluxo de sinal. Uma vez representado o sistema, o ModSym possibilita o cálculo de funções de transferência do sistema na forma simbólica, utilizando a regra de Mason. O software calcula também funções de transferência na forma numérica e funções de sensibilidade paramétrica. O trabalho propõe ainda um algoritmo para obter o diagrama de fluxo de sinal de um sistema físico baseado no seu grafo de ligação. Este algoritmo e a metodologia de análise de sistemas conhecida por Network Method permitiram a utilização da regra de Mason no cálculo de funções de transferência dos sistemas modelados no software
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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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A neuro-fuzzy system consists of two or more control techniques in only one structure. The main characteristic of this structure is joining one or more good aspects from each technique to make a hybrid controller. This controller can be based in Fuzzy systems, artificial Neural Networks, Genetics Algorithms or rein forced learning techniques. Neuro-fuzzy systems have been shown as a promising technique in industrial applications. Two models of neuro-fuzzy systems were developed, an ANFIS model and a NEFCON model. Both models were applied to control a ball and beam system and they had their results and needed changes commented. Choose of inputs to controllers and the algorithms used to learning, among other information about the hybrid systems, were commented. The results show the changes in structure after learning and the conditions to use each one controller based on theirs characteristics
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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