Identificação em tempo real de modelo dinâmico de robô móvel com acionamento diferencial e zona morta

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

Identificação de modelos polinomiais narx utilizando algoritmos combinados de detecção de estrutura e estimação de parâmetros com aplicações práticas

A modelagem de processos industriais tem auxiliado na produção e minimização de custos, permitindo a previsão dos comportamentos futuros do sistema, supervisão de processos e projeto de controladores. Ao observar os benefícios proporcionados pela modelagem, objetiva-se primeiramente, nesta dissertação, apresentar uma metodologia de identificação de modelos não-lineares com estrutura NARX, a partir da implementação de algoritmos combinados de detecção de estrutura e estimação de parâmetros. Inicialmente, será ressaltada a importância da identificação de sistemas na otimização de processos industriais, especificamente a escolha do modelo para representar adequadamente as dinâmicas do sistema. Em seguida, será apresentada uma breve revisão das etapas que compõem a identificação de sistemas. Na sequência, serão apresentados os métodos fundamentais para detecção de estrutura (Modificado Gram- Schmidt) e estimação de parâmetros (Método dos Mínimos Quadrados e Método dos Mínimos Quadrados Estendido) de modelos. No trabalho será também realizada, através dos algoritmos implementados, a identificação de dois processos industriais distintos representados por uma planta de nível didática, que possibilita o controle de nível e vazão, e uma planta de processamento primário de petróleo simulada, que tem como objetivo representar um tratamento primário do petróleo que ocorre em plataformas petrolíferas. A dissertação é finalizada com uma avaliação dos desempenhos dos modelos obtidos, quando comparados com o sistema. A partir desta avaliação, será possível observar se os modelos identificados são capazes de representar as características estáticas e dinâmicas dos sistemas apresentados nesta dissertação

Construção, calibração e análise de desempenho de um piranômetro de baixo custo, baseado no modelo Kimball-Hobbs

In this work a pyrometer using the classic model of Kimball-Hobbs was developed, tested and calibrated. The solar radiation is verified through the temperature difference between the sensible elements covered by absorbing (black) and reflecting (white) pigmentations of the incoming radiation. The photoacoustic technique was used to optimize the choice of the pigments. Methodologies associated with linearity, thermo-variation, sensibility, response time and distance are also presented. To correctly classify the results, the international standard ISO 9060 as well as indicative parameters of World Meteorological Organization (WMO) are used. In addition a system of data acquisition of two channels with 12 bits, constructed during the this time, was used to measure the global solar radiation on the ground by the pyrometer and also by another pyrometer certified in the case of Keep & zonen. The results statistically show, through the hypothesis test presented here, that both equipments find population average with 95% of correctness

Estudo dos parâmetros de extração de fenol de efluentes aquosos por um tensoativo não iônico

Environmental sustainability has become one of the topics of greatest interest in industry, mainly due to effluent generation. Phenols are found in many industries effluents, these industries might be refineries, coal processing, pharmaceutical, plastics, paints and paper and pulp industries. Because phenolic compounds are toxic to humans and aquatic organisms, Federal Resolution CONAMA No. 430 of 13.05.2011 limits the maximum content of phenols, in 0.5 mg.L-1, for release in freshwater bodies. In the effluents treatment, the liquid-liquid extraction process is the most economical for the phenol recovery, because consumes little energy, but in most cases implements an organic solvent, and the use of it can cause some environmental problems due to the high toxicity of this compound. Because of this, exists a need for new methodologies, which aims to replace these solvents for biodegradable ones. Some literature studies demonstrate the feasibility of phenolic compounds removing from aqueous effluents, by biodegradable solvents. In this extraction kind called "Cloud Point Extraction" is used a nonionic surfactant as extracting agent of phenolic compounds. In order to optimize the phenol extraction process, this paper studies the mathematical modeling and optimization of extraction parameters and investigates the effect of the independent variables in the process. A 32 full factorial design has been done with operating temperature and surfactant concentration as independent variables and, parameters extraction: Volumetric fraction of coacervate phase, surfactant and residual concentration of phenol in dilute phase after separation phase and phenol extraction efficiency, as dependent variables. To achieve the objectives presented before, the work was carried out in five steps: (i) selection of some literature data, (ii) use of Box-Behnken model to find out mathematical models that describes the process of phenol extraction, (iii) Data analysis were performed using STATISTICA 7.0 and the analysis of variance was used to assess the model significance and prediction (iv) models optimization using the response surface method (v) Mathematical models validation using additional measures, from samples different from the ones used to construct the model. The results showed that the mathematical models found are able to calculate the effect of the surfactant concentration and the operating temperature in each extraction parameter studied, respecting the boundaries used. The models optimization allowed the achievement of consistent and applicable results in a simple and quick way leading to high efficiency in process operation.

Propriedades críticas do modelo z(4) em sistemas bi e tridimensionais

A real space renormalization group method is used to investigate the criticality (phase diagrams, critical expoentes and universality classes) of Z(4) model in two and three dimensions. The values of the interaction parameters are chosen in such a way as to cover the complete phase diagrams of the model, which presents the following phases: (i) Paramagnetic (P); (ii) Ferromagnetic (F); (iii) Antiferromagnetic (AF); (iv) Intermediate Ferromagnetic (IF) and Intermediate Antiferromagnetic (IAF). In the hierarquical lattices, generated by renormalization the phase diagrams are exact. It is also possible to obtain approximated results for square and simple cubic lattices. In the bidimensional case a self-dual lattice is used and the resulting phase diagram reproduces all the exact results known for the square lattice. The Migdal-Kadanoff transformation is applied to the three dimensional case and the additional phases previously suggested by Ditzian et al, are not found

Danos e propriedades termodinâmicas no modelo de Ashkin-Teller de n cores

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Estimação de parâmetros genéticos para resistência à infecção por IMNV em camarões Litopenaeus vannamei por meio de análise de sobrevivência

The main specie of marine shrimp raised at Brazil and in the world is Litopenaeus vannamei, which had arrived in Brazil in the `80s. However, the entry of infectious myonecrosis virus (IMNV), causing the infectious myonecrosis disease in marine shrimps, brought economic losses to the national shrimp farming, with up to 70% of mortality in the shrimp production. In this way, the objective was to evaluate the survival of shrimps Litopenaeus vannamei infected with IMNV using the non parametric estimator of Kaplan-Meier and a model of frailty for grouped data. It were conducted three tests of viral challenges lasting 20 days each, at different periods of the year, keeping the parameters of pH, temperature, oxygen and ammonia monitored daily. It was evaluated 60 full-sib families of L. vannamei infected by IMNV in each viral challenge. The confirmation of the infection by IMNV was performed using the technique of PCR in real time through Sybr Green dye. Using the Kaplan-Meier estimator it was possible to detect significant differences (p <0.0001) between the survival curves of families and tanks and also in the joint analysis between viral challenges. It were estimated in each challenge, genetic parameters such as genetic value of family, it`s respective rate risk (frailty), and heritability in the logarithmic scale through the frailty model for grouped data. The heritability estimates were respectively 0.59; 0.36; and 0.59 in the viral challenges 1; 2; and 3, and it was also possible to identify families that have lower and higher rates of risk for the disease. These results can be used for selecting families more resistant to the IMNV infection and to include characteristic of disease resistance in L. vannamei into the genetic improvement programs

Administração repetida de baixas doses de reserpina: um possível modelo para o estudo de déficits cognitivos e motores associados à Doença de Parkinson

Parkinson's disease (PD) is one of the most common neurodegenerative brain disorders and is characterized primarily by a progressive degeneration of dopaminergic neurons nigroestriatais. The main symptoms of this disease are motor alterations (bradykinesia, rigidity, tremor at rest), which can be highly disabling in advanced stages of the condition. However, there are symptomatic manifestations other than motor impairment, such as changes in cognition, mood and sensory systems. Animal models that attempt to mimic clinical features of PD have been used to understand the behavioral and neural mechanisms underlying neurophysiological disturbance of this disease. However, most models promote an intense and immediate motor impairment, consistent with advanced stages of the disease, invalidating these studies for the evaluation of its progressive nature. The administration of reserpine (a monoamine depletor) in rodents has been considered an animal model for studying PD. Recently we found that reserpine (in doses lower than those usually employed to produce the motor symptoms) promotes a memory deficit in an aversive discrimination task, without changing the motor activity. It was suggested that the administration of this drug in low doses can be useful for the study of memory deficits found in PD. Corroborating this data, in another study, acute subcutaneous administration of reserpine, while preserving motor function, led to changes in emotional context-related (but not neutral) memory tasks. The goal of this research was to study the cognitive and motor deficits in rats repeatedly treated with low doses of reserpine, as a possible model that simulates the progressive nature of the PD. For this purpose, 5-month-old male Wistar rats were submitted to a repeated treatment with vehicle or different doses of reserpine on alternate days. Cognitive and motor parameters and possible changes in neuronal function were evaluated during treatment. The main findings were: repeated administration of 0.1 mg / kg of reserpine in rats is able to induce the gradual appearance of motor signs compatible with progressive features found in patients with PD; an increase in striatal levels of oxidative stress and changes in the concentrations of glutamate in the striatum were observed five days after the end of treatment; in animals repeatedly-treated with 0. 1 mg/kg, cognitive deficits were observed only after the onset of motor symptoms, but not prior to the onset of these symptoms; 0.2 mg / kg reserpine repeated treatment has jeopardized the cognitive assessment due to the presence of severe motor deficits. Thus, we suggest that the protocol of treatment with reserpine used in this work is a viable alternative for studies of the progressive appearance of parkinsonian signs in rats, especially concerning motor symptoms. As for the cognitive symptoms, we suggest that more studies are needed, possibly using other behavioral models, and / or changing the treatment regimen

Estudo da água produzida em diferentes zonas de produção de petróleo, utilizando a hidroquímica e a análise estatística de parâmetros químicos

Over exploitation of oil deposits on land onshore or offshore, there is simultaneous generation of waste water, known as produced water, which represents the largest waste stream in the production of crude oil. The relationship between the chemical composition of oil and water production and the conditions in which this process occurs or is favored are still poorly studied. The area chosen for the study has an important oil reserve and an important aquifer saturated with freshwater meteoric. The aim of this work is to study some chemical parameters in water produced for each reservoir zone of production in mature oil fields of Açu Formation, using the hydrochemical and statistical analysis to serve as a reference and be used as tools against the indicator ranges water producers in oil producing wells. Samples were collected from different wells in 6 different areas of production and were measured 50 parameters, which can be classified into three groups: anions, cations and physicochemical properties (considering only the parameters that generated values above detection limits in all samples). Through the characterization hydrochemistry observed an area of water and chlorinated sodium, chlorinated calcium or magnesium (mixed) in well water in different areas of Açu, by applying a statistical treatment, we obtained a discriminant function that distinguishes chemically production areas. Thus, it was possible to calculate the rate of correct classification of the function was 76.3%. To validate this model the accuracy rate was 86%

Espectroscopia no infravermelho próximo e métodos de calibração multivariada aplicados à determinação simultânea de parâmetros bioquímicos em plasma sanguíneo

In this work, the quantitative analysis of glucose, triglycerides and cholesterol (total and HDL) in both rat and human blood plasma was performed without any kind of pretreatment of samples, by using near infrared spectroscopy (NIR) combined with multivariate methods. For this purpose, different techniques and algorithms used to pre-process data, to select variables and to build multivariate regression models were compared between each other, such as partial least squares regression (PLS), non linear regression by artificial neural networks, interval partial least squares regression (iPLS), genetic algorithm (GA), successive projections algorithm (SPA), amongst others. Related to the determinations of rat blood plasma samples, the variables selection algorithms showed satisfactory results both for the correlation coefficients (R²) and for the values of root mean square error of prediction (RMSEP) for the three analytes, especially for triglycerides and cholesterol-HDL. The RMSEP values for glucose, triglycerides and cholesterol-HDL obtained through the best PLS model were 6.08, 16.07 e 2.03 mg dL-1, respectively. In the other case, for the determinations in human blood plasma, the predictions obtained by the PLS models provided unsatisfactory results with non linear tendency and presence of bias. Then, the ANN regression was applied as an alternative to PLS, considering its ability of modeling data from non linear systems. The root mean square error of monitoring (RMSEM) for glucose, triglycerides and total cholesterol, for the best ANN models, were 13.20, 10.31 e 12.35 mg dL-1, respectively. Statistical tests (F and t) suggest that NIR spectroscopy combined with multivariate regression methods (PLS and ANN) are capable to quantify the analytes (glucose, triglycerides and cholesterol) even when they are present in highly complex biological fluids, such as blood plasma

Desenvolvimento e teste de um modelo estatístico de identificação das proporções de água produzida em zonas de produção de um campo maduro de petróleo

This study investigates the chemical species produced water from the reservoir areas of oil production in the field of Monte Alegre (onshore production) with a proposal of developing a model applied to the identification of the water produced in different zones or groups of zones.Starting from the concentrations of anions and cátions from water produced as input parameters in Linear Discriminate Analysis, it was possible to estimate and compare the model predictions respecting the particularities of their methods in order to ascertain which one would be most appropriate. The methods Resubstitution, Holdout Method and Lachenbruch were used for adjustment and general evaluation of the built models. Of the estimated models for Wells producing water for a single production area, the most suitable method was the "Holdout Method and had a hit rate of 90%. Discriminant functions (CV1, CV2 and CV3) estimated in this model were used to modeling new functions for samples ofartificial mixtures of produced water (producedin our laboratory) and samples of mixtures actualproduced water (water collected inwellsproducingmore thanonezone).The experiment with these mixtures was carried out according to a schedule experimental mixtures simplex type-centroid also was simulated in which the presence of water from steam injectionin these tanks fora part of amostras. Using graphs of two and three dimensions was possible to estimate the proportion of water in the production area

Avaliação de uma fração polissacaridica da alga Lobophora variegata (Lamouroux) em modelo de artrite induzida em ratos por Zymosan

Fucans seaweed Lobophora variegata estructures are known for their chemical and biological properties. In this study, we analyzed, the action of fucans L. variegata and the fractions purified with acetone in Zymosan-induced arthritis. After differential fractionation with acetone, six fractions were obtained and named F0.3, F0.5, F0.8, F1, F1.5 and F2. The results showed that the fraction F1 showed high yield (51.9%) and was chosen for studies of antioxidant activity and induced arthritis. Nuclear magnetic resonance (NMR) of 13C showed signals at 103.3 and 15.78 ppm that are assigned to links β13 galactose and of the C6 methyl fucose, respectively. The infrared (IR) showed absorbance at 1238 and 850 cm-1 which are attributed to sulfate. The fraction F1 showed antioxidant activities in vitro. For analysis of inflammatory parameters chosen the polysaccharide was administered in different doses (25, 50 and 75 mg / kg ip, per body weight) and diclofenac sodium (5 mg / kg ip) and L-NAME (25 mg / kg ip) in groups of animals (n = 6). After 6 h, were analyzed for cellular influx and levels of nitrite. In experiment five days, were made analysis of swelling and serum TNF-α. Histopathological analysis were performed for confirmation of results. The fraction F1 (25, 50 and 75 mg / kg ip) reduced the cellular influx (52.1 to 96.7%) and nitric oxide levels (27.2 - 39%) compared to control group. The reduction of edema (63.4 - 100%) and serum TNF-α (p <0.001) were observed when the polysaccharide F1 administered at a dose (50 mg / kg) These results suggest that these heterofucanas of Lobophora variegata have besides the activity antioxidant and potential anti-inflammatory activity in arthritis induced by zymosan

Identificação e comparação entre controle preditivo com modelo não linear e PI sintonizados com PSO em sistema de separação gravitacional de águia-óleo

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

Dinâmica e estrutura de redes complexas no modelo de afinidade

In this work we elaborate and discuss a Complex Network model which presents connectivity scale free probability distribution (power-law degree distribution). In order to do that, we modify the rule of the preferential attachment of the Bianconi-Barabasi model, including a factor which represents the similarity of the sites. The term that corresponds to this similarity is called the affinity, and is obtained by the modulus of the difference between the fitness (or quality) of the sites. This variation in the preferential attachment generates very interesting results, by instance the time evolution of the connectivity, which follows a power-law distribution ki / ( t t0 )fi, where fi indicates the rate to the site gain connections. Certainly this depends on the affinity with other sites. Besides, we will show by numerical simulations results for the average path length and for the clustering coefficient

Alterações dos parâmetros climáticos no município de Apodi-RN, antes e após a construção da barragem Santa Cruz do Apodi, e formação do lago

Este trabalho teve como objetivo principal analisar as mudanças ocorridas no clima local onde o município de Apodi/RN está inserido, em virtude da construção da Barragem Santa Cruz do Apodi. Foram utilizadas para o tratamento dos dados climáticos precipitação pluviométrica, umidade relativa do ar e temperatura técnicas estatísticas como Desvio Padrão, Teste T, Coeficiente de Variação e Média aritmética, além do modelo matemático. Para o balanço hídrico foi aplicado o método de Thornthwait (1948), considerando dois períodos em análise: o anterior e posterior a construção da Barragem Santa Cruz do Apodi, respectivamente 1995 e 2005. os resultados obtidos permitiram inferir que a hipótese inicial levantada se confirma, ou seja, a construção da Barragem Santa Cruz do Apodi, está influenciando diretamente numa alteração no que concerne à condição atmosférica local, especialmente no parâmetro umidade relativa do ar. Quanto ao balanço hídrico, observou-se a predominância do déficit hídrico especialmente entre os meses de junho a janeiro, período de estiagem; um excedente ocorrente entre os meses de maio e junho, conseqüente do período chuvoso; e uma reposição hídrica antecedendo e sucedendo este período, chuvoso, ou seja, compreendendo os meses de fevereiro a junho. Todas as considerações e análises poderão contribuir para o planejamento de abastecimento d´água, a irrigação, auxílio na previsão de enchentes e estiagens, bem como o manejo do uso da água subterrânea