32 resultados para Modelo linear de Heffron e Phillips

em Universidade Federal do Rio Grande do Norte(UFRN)


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This work presents a modelling and identification method for a wheeled mobile robot, including the actuator dynamics. Instead of the classic modelling approach, where the robot position coordinates (x,y) are utilized as state variables (resulting in a non linear model), the proposed discrete model is based on the travelled distance increment Delta_l. Thus, the resulting model is linear and time invariant and it can be identified through classical methods such as Recursive Least Mean Squares. This approach has a problem: Delta_l can not be directly measured. In this paper, this problem is solved using an estimate of Delta_l based on a second order polynomial approximation. Experimental data were colected and the proposed method was used to identify the model of a real robot

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This thesis presents a new structure of robust adaptive controller applied to mobile robots (surface mobile robot) with nonholonomic constraints. It acts in the dynamics and kinematics of the robot, and it is split in two distinct parts. The first part controls the robot dynamics, using variable structure model reference adaptive controllers. The second part controls the robot kinematics, using a position controller, whose objective is to make the robot to reach any point in the cartesian plan. The kinematic controller is based only on information about the robot configuration. A decoupling method is adopted to transform the linear model of the mobile robot, a multiple-input multiple-output system, into two decoupled single-input single-output systems, thus reducing the complexity of designing the controller for the mobile robot. After that, a variable structure model reference adaptive controller is applied to each one of the resulting systems. One of such controllers will be responsible for the robot position and the other for the leading angle, using reference signals generated by the position controller. To validate the proposed structure, some simulated and experimental results using differential drive mobile robots of a robot soccer kit are presented. The simulator uses the main characteristics of real physical system as noise and non-linearities such as deadzone and saturation. The experimental results were obtained through an C++ program applied to the robot soccer kit of Microrobot team at the LACI/UFRN. The simulated and experimental results are presented and discussed at the end of the text

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The dyslipidemia and excess weight in adolescents, when combined, suggest a progression of risk factors for cardiovascular disease (CVD). Besides these, the dietary habits and lifestyle have also been considered unsuitable impacting the development of chronic diseases. The study objectives were: (1) estimate the prevalence of lipid profile and correlate with body mass index (BMI), waist circumference (WC) and waist / height ratio (WHR) in adolescents, considering the maturation sexual, (2) know the sources of variance in the diet and the number of days needed to estimate the usual diet of adolescents and (3) describe the dietary patterns and lifestyle of adolescents, family history of CVD and age correlates them with the patterns of risk for CVD, adjusted for sexual maturation. A cross-sectional study was performed with 432 adolescents, aged 10-19 years from public schools of the Natal city, Brazil. The dyslipidemias were evaluated considering the lipid profile, the index of I Castelli (TC / HDL) and II (LDL / HDL) and non-HDL cholesterol. Anthropometric indicators were BMI, WC and WHR. The intake of energy, nutrients including fiber, fatty acids and cholesterol was estimated from two 24-hour recalls (24HR). The variables of lipid profile, anthropometric and clinical data were used in the models of Pearson correlation and linear regression, considering the sexual maturation. The variance ratio of the diet was calculated from the component-person variance, determined by analysis of variance (ANOVA). The definition of the number of days to estimate the usual intake of each nutrient was obtained by taking the hypothetical correlation (r) ≥ 0.9, between nutrient intake and the true observed. We used the principal component analysis as a method of extracting factors that 129 accounted for the dependent variables and known cardiovascular risk obtained from the lipid profile, the index for Castelli I and II, non-HDL cholesterol, BMI, and WC the WHR. Dietary patterns and lifestyle were obtained from the independent variables, based on nutrients consumed and physical activity weekly. In the study of principal component analysis (PCA) was investigated associations between the patterns of cardiovascular risk factors in dietary patterns and lifestyle, age and positive family history of CVD, through bivariate and multiple logistic regression adjusted for sexual maturation. The low HDL-C dyslipidemia was most prevalent (50.5%) for adolescents. Significant correlations were observed between hypercholesterolemia and positive family history of CVD (r = 0.19, p <0.01) and hypertriglyceridemia with BMI (r = 0.30, p <0.01), with the CC (r = 0.32, p <0.01) and WHR (r = 0.33, p <0.01). The linear model constructed with sexual maturation, age and BMI explained about 1 to 10.4% of the variation in the lipid profile. The sources of variance between individuals were greater for all nutrients in both sexes. The reasons for variances were  1 for all nutrients were higher in females. The results suggest that to assess the diet of adolescents with greater precision, 2 days would be enough to R24h consumption of energy, carbohydrates, fiber, saturated and monounsaturated fatty acids. In contrast, 3 days would be recommended for protein, lipid, polyunsaturated fatty acids and cholesterol. Two cardiovascular risk factors as have been extracted in the ACP, referring to the dependent variables: the standard lipid profile (HDL-C and non-HDL cholesterol) and "standard anthropometric index (BMI, WC, WHR) with a power explaining 75% of the variance of the original data. The factors are representative of two independent variables led to dietary patterns, "pattern 130 western diet" and "pattern protein diet", and one on the lifestyle, "pattern energy balance". Together, these patterns provide an explanation power of 67%. Made adjustment for sexual maturation in males remained significant variables: the associations between puberty and be pattern anthropometric indicator (OR = 3.32, CI 1.34 to 8.17%), and between family history of CVD and the pattern lipid profile (OR = 2.62, CI 1.20 to 5.72%). In females adolescents, associations were identified between age after the first stage of puberty with anthropometric pattern (OR = 3.59, CI 1.58 to 8.17%) and lipid profile (OR = 0.33, CI 0.15 to 0.75%). Conclusions: The low HDL-C was the most prevalent dyslipidemia independent of sex and nutritional status of adolescents. Hypercholesterolemia was influenced by family history of CVD and sexual maturation, in turn, hypertriglyceridemia was closely associated with anthropometric indicators. The variance between the diets was greater for all nutrients. This fact reflected in a variance ratio less than 1 and consequently in a lower number of days requerid to estimate the usual diet of adolescents considering gender. The two dietary patterns were extracted and the pattern considered unhealthy lifestyle as healthy. The associations were found between the patterns of CVD risk with age and family history of CVD in the studied adolescents

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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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The pumping through progressing cavities system has been more and more employed in the petroleum industry. This occurs because of its capacity of elevation of highly viscous oils or fluids with great concentration of sand or other solid particles. A Progressing Cavity Pump (PCP) consists, basically, of a rotor - a metallic device similar to an eccentric screw, and a stator - a steel tube internally covered by a double helix, which may be rigid or deformable/elastomeric. In general, it is submitted to a combination of well pressure with the pressure generated by the pumping process itself. In elastomeric PCPs, this combined effort compresses the stator and generates, or enlarges, the clearance existing between the rotor and the stator, thus reducing the closing effect between their cavities. Such opening of the sealing region produces what is known as fluid slip or slippage, reducing the efficiency of the PCP pumping system. Therefore, this research aims to develop a transient three-dimensional computational model that, based on single-lobe PCP kinematics, is able to simulate the fluid-structure interaction that occurs in the interior of metallic and elastomeric PCPs. The main goal is to evaluate the dynamic characteristics of PCP s efficiency based on detailed and instantaneous information of velocity, pressure and deformation fields in their interior. To reach these goals (development and use of the model), it was also necessary the development of a methodology for generation of dynamic, mobile and deformable, computational meshes representing fluid and structural regions of a PCP. This additional intermediary step has been characterized as the biggest challenge for the elaboration and running of the computational model due to the complex kinematic and critical geometry of this type of pump (different helix angles between rotor and stator as well as large length scale aspect ratios). The processes of dynamic generation of meshes and of simultaneous evaluation of the deformations suffered by the elastomer are fulfilled through subroutines written in Fortan 90 language that dynamically interact with the CFX/ANSYS fluid dynamic software. Since a structural elastic linear model is employed to evaluate elastomer deformations, it is not necessary to use any CAE package for structural analysis. However, an initial proposal for dynamic simulation using hyperelastic models through ANSYS software is also presented in this research. Validation of the results produced with the present methodology (mesh generation, flow simulation in metallic PCPs and simulation of fluid-structure interaction in elastomeric PCPs) is obtained through comparison with experimental results reported by the literature. It is expected that the development and application of such a computational model may provide better details of the dynamics of the flow within metallic and elastomeric PCPs, so that better control systems may be implemented in the artificial elevation area by PCP

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The waste in the industries of escargot processing is very big. This is composed basically of escargot meat out of the commercialization patterns and the visceras. In this context, there is a need to take advantage to the use of these sub-products. A possibility should be drying them and transforming them in a certain form to be reused. Than, the present work has the objective of studying the reutilization of the sub-products of the escargot industrialization for by means of drying process. The samples were transformed in pastes, through a domestic processor for approximately 1 minute and compacted in trays of aluminum without perforations with three different heights (5 mm, 10 mm and 15 mm). The drying was accomplished in a tray dryer with air circulation and transverse flow at a speed of 0,2 m/s and three temperature levels (70°C, 80°C and 90ºC). A drying kinetics study was accomplished for the obtained curves and for the heat and mass transfer coefficients using experimental procedures based in an experimental planning of 22 factorial type. Microbiological and physiochemical analysis were also accomplished for the in nature and the dehydrated sub-products. In the drying process, it was observed the great importance of the external resistances to the mass transfer and heat in the period of constant tax influenced by the temperature. The evaporation taxes indicated a mixed control of the mass transfer for the case of the thickest layers. As already expected, the drying constant behavior was influenced by the temperature and thickness of the medium, increasing and decreasing. The statistical analysis of the results, in agreement with the factorial planning 22, showed that the fissures, the shrinking of the transfer area and the formation of a crust on the surface might have contributed to the differences between the practical results and the linear model proposed. The temperature and the thickness influenced significantly in the answers of the studied variables: evaporation tax and drying constant. They were obtained significant statistical models and predictive ones for evaporation tax for the meat as well as for the visceras

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The Predictive Controller has been receiving plenty attention in the last decades, because the need to understand, to analyze, to predict and to control real systems has been quickly growing with the technological and industrial progress. The objective of this thesis is to present a contribution for the development and implementation of Nonlinear Predictive Controllers based on Hammerstein model, as well as to its make properties evaluation. In this case, in the Nonlinear Predictive Controller development the time-step linearization method is used and a compensation term is introduced in order to improve the controller performance. The main motivation of this thesis is the study and stability guarantee for the Nonlinear Predictive Controller based on Hammerstein model. In this case, was used the concepts of sections and Popov Theorem. Simulation results with literature models shows that the proposed approaches are able to control with good performance and to guarantee the systems stability

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The separation methods are reduced applications as a result of the operational costs, the low output and the long time to separate the uids. But, these treatment methods are important because of the need for extraction of unwanted contaminants in the oil production. The water and the concentration of oil in water should be minimal (around 40 to 20 ppm) in order to take it to the sea. Because of the need of primary treatment, the objective of this project is to study and implement algorithms for identification of polynomial NARX (Nonlinear Auto-Regressive with Exogenous Input) models in closed loop, implement a structural identification, and compare strategies using PI control and updated on-line NARX predictive models on a combination of three-phase separator in series with three hydro cyclones batteries. The main goal of this project is to: obtain an optimized process of phase separation that will regulate the system, even in the presence of oil gushes; Show that it is possible to get optimized tunings for controllers analyzing the mesh as a whole, and evaluate and compare the strategies of PI and predictive control applied to the process. To accomplish these goals a simulator was used to represent the three phase separator and hydro cyclones. Algorithms were developed for system identification (NARX) using RLS(Recursive Least Square), along with methods for structure models detection. Predictive Control Algorithms were also implemented with NARX model updated on-line, and optimization algorithms using PSO (Particle Swarm Optimization). This project ends with a comparison of results obtained from the use of PI and predictive controllers (both with optimal state through the algorithm of cloud particles) in the simulated system. Thus, concluding that the performed optimizations make the system less sensitive to external perturbations and when optimized, the two controllers show similar results with the assessment of predictive control somewhat less sensitive to disturbances

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This research aims to understand the factors that influence intention to online purchase of consumers, and to identify between these factors those that influence the users and the nonusers of electronic commerce. Thus, it is an applied, exploratory and descriptive research, developed in a quantitative model. Data collection was done through a questionnaire administered to a sample of 194 graduate students from the Centre for Applied Social Sciences of UFRN and data analysis was performed using descriptive statistics, confirmatory factorial analysis and simple and multiple linear regression analysis. The results of descriptive statistics revealed that respondents in general and users of electronic commerce have positive perceptions of ease of use, usefulness and social influence about buying online, and intend to make purchases on Internet over the next six months. As for the non-users of electronic commerce, they do not trust the Internet to transact business, have negative perceptions of risk and social influence over purchasing online, and does not intend to make purchases on Internet over the next six months. Through confirmatory factorial analysis six factors were set up: behavioral intention, perceived ease of use, perceived usefulness, perceived risk, trust and social influence. Through multiple regression analysis, was observed that all these factors influence online purchase intentions of respondents in general, that only the social influence does not influence the intention to continue buying on the Internet from users of electronic commerce, and that only trust and social influence affect the intention to purchase online from non-users of electronic commerce. Through simple regression analysis, was found that trust influences perceptions of ease of use, usefulness and risk of respondents in general and users of electronic commerce, and that trust does not influence the perceptions of risk of non-users of electronic commerce. Finally, it was also found that the perceived ease of use influences perceived usefulness of the three groups. Given this scenario, it was concluded that it is extremely important that organizations that work with online sales know the factors that influence consumers purchasing intentions in order to gain space in their market

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Existem diversas equações para predição do VO2máx a partir de variáveis dentro do teste ergométrico em vários ergômetros, no entanto equação semelhante utilizando os limiares ventilatórios na ergoespirometria em teste sub-máximo no cicloergômetro não está disponível. O objetivo do presente estudo foi avaliar a precisão de modelos de predição do VO2máx com base em indicadores de esforço sub-máximo. Neste sentido foram testados em protocolo incremental máximo no cicloergômetro 7.877 voluntários, sendo 4640 indivíduos do sexo feminino e 3147 do sexo masculino, todos saudáveis não atletas, com idades acima de 20 anos, divididos randomicamente em dois grupos: A de estimação e B de validação. A partir das variáveis independentes massa corporal (MC) em kg, carga de trabalho no limiar 2 (WL2) e freqüência cardíaca no limiar 2 (FCL2) foi possível construir um modelo de regressão linear múltipla para predição do VO2máx. Os resultados demonstram que em indivíduos saudáveis não atletas de ambos os sexos é possível predizer o VO2máx com um erro mínimo (EPE = 1,00%) a partir de indicadores submáximos obtidos em teste incremental. O caráter multidisciplinar do trabalho pôde ser caracterizado pelo emprego de técnicas que envolveram pneumologia, educação física, fisiologia e estatística

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An important unsolved problem in medical science concerns the physical origin of the sigmoidal shape of pressure volume curves of healthy (and some unhealthy) lungs. Such difficulties are expected because the lung, which is the most important structure in the respiratory system, is extremely complex. Its rheological properties are unknown and seem to depend on phenomena occurring from the alveolar scale up to the thoracic scale. Conventional wisdom holds that linear response, i.e., Hooke s law, together with alveolar overdistention, play a dominant role in respiration, but such assumptions cannot explainthe crucial empirical sigmoidal shape of the curves. In this doctorate thesis, we propose an alternative theory to solve this problem, based on the alveolar recruitment together with the nonlinear elasticity of the alveoli. This theory suggests that recruitment may be the predominant factor shaping these curves in the entire range of pressures normally employed in experiments. The proposed model correctly predicts the observed sigmoidal pressure volume curves, allowing us to discuss adequately the importance of this result, as well as its implications for medical practice

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The spread of the Web boosted the dissemination of Information Systems (IS) based on the Web. In order to support the implementation of these systems, several technologies came up or evolved with this purpose, namely the programming languages. The Technology Acceptance Model TAM (Davis, 1986) was conceived aiming to evaluate the acceptance/use of information technologies by their users. A lot of studies and many applications have used the TAM, however, in the literature it was not found a mention of the use of such model related to the use of programming languages. This study aims to investigate which factors influence the use of programming languages on the development of Web systems by their developers, applying an extension of the TAM, proposed in this work. To do so, a research was done with Web developers in two Yahoo groups: java-br and python-brasil, where 26 Java questionnaires and 39 Python questionnaires were fully answered. The questionnaire had general questions and questions which measured intrinsic and extrinsic factors of the programming languages, the perceived usefulness, the perceived ease of use, the attitude toward the using and the programming language use. Most of the respondents were men, graduate, between 20 and 30 years old, working in the southeast and south regions. The research was descriptive in the sense of its objectives. Statistical tools, descriptive statistics, main components and linear regression analysis were used for the data analysis. The foremost research results were: Java and Python have machine independence, extensibility, generality and reliability; Java and Python are more used by corporations and international organizations than supported by the government or educational institutions; there are more Java programmers than Python programmers; the perceived usefulness is influenced by the perceived ease of use; the generality and the extensibility are intrinsic factors of programming languages which influence the perceived ease of use; the perceived ease of use influences the attitude toward the using of the programming language

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In this thesis, it is developed the robustness and stability analysis of a variable structure model reference adaptive controller considering the presence of disturbances and unmodeled dynamics. The controller is applied to uncertain, monovariable, linear time-invariant plants with relative degree one, and its development is based on the indirect adaptive control. In the direct approach, well known in the literature, the switching laws are designed for the controller parameters. In the indirect one, they are designed for the plant parameters and, thus, the selection of the relays upper bounds becomes more intuitive, whereas they are related to physical parameters, which present uncertainties that can be known easier, such as resistances, capacitances, inertia moments and friction coefficients. Two versions for the controller algorithm with the stability analysis are presented. The global asymptotic stability with respect to a compact set is guaranteed for both cases. Simulation results under adverse operation conditions in order to verify the theoretical results and to show the performance and robustness of the proposed controller are showed. Moreover, for practical purposes, some simplifications on the original algorithm are developed

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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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Several mobile robots show non-linear behavior, mainly due friction phenomena between the mechanical parts of the robot or between the robot and the ground. Linear models are efficient in some cases, but it is necessary take the robot non-linearity in consideration when precise displacement and positioning are desired. In this work a parametric model identification procedure for a mobile robot with differential drive that considers the dead-zone in the robot actuators is proposed. The method consists in dividing the system into Hammerstein systems and then uses the key-term separation principle to present the input-output relations which shows the parameters from both linear and non-linear blocks. The parameters are then simultaneously estimated through a recursive least squares algorithm. The results shows that is possible to identify the dead-zone thresholds together with the linear parameters