937 resultados para Regular Linear System
H-infinity control design for time-delay linear systems: a rational transfer function based approach
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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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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Tuberculosis is a serious disease, but curable in practically 100% of new cases, since complied the principles of modern chemotherapy. Isoniazid (ISN), Rifampicin (RIF), Pyrazinamide (PYR) and Chloride Ethambutol (ETA) are considered first line drugs in the treatment of tuberculosis, by combining the highest level of efficiency with acceptable degree of toxicity. Concerning USP 33 - NF28 (2010) the chromatography analysis to 3 of 4 drugs (ISN, PYR and RIF) last in average 15 minutes and 10 minutes more to obtain the 4th drug (ETA) using a column and mobile phase mixture different, becoming its industrial application unfavorable. Thus, many studies have being carried out to minimize this problem. An alternative would use the UFLC, which is based with the same principles of HPLC, however it uses stationary phases with particles smaller than 2 μm. Therefore, this study goals to develop and validate new analytical methods to determine simultaneously the drugs by HPLC/DAD and UFLC/DAD. For this, a analytical screening was carried out, which verified that is necessary a gradient of mobile phase system A (acetate buffer:methanol 94:6 v/v) and B (acetate buffer:acetonitrile 55:45 v/v). Furthermore, to the development and optimization of the method in HPLC and UFLC, with achievement of the values of system suitability into the criteria limits required for both techniques, the validations have began. Standard solutions and tablets test solutions were prepared and injected into HPLC and UFLC, containing 0.008 mg/mL ISN, 0.043 mg/mL PYR, 0.030 mg.mL-1 ETA and 0.016 mg/mL RIF. The validation of analytical methods for HPLC and UFLC was carried out with the determination of specificity/selectivity, analytical curve, linearity, precision, limits of detection and quantification, accuracy and robustness. The methods were adequate for determination of 4 drugs separately without interfered with the others. Precise, due to the fact of the methods demonstrated since with the days variation, besides the repeatability, the values were into the level required by the regular agency. Linear (R> 0,99), once the methods were capable to demonstrate results directly proportional to the concentration of the analyte sample, within of specified range. Accurate, once the methods were capable to present values of variation coefficient and recovery percentage into the required limits (98 to 102%). The methods showed LOD and LOQ very low showing the high sensitivity of the methods for the four drugs. The robustness of the methods were evaluate, facing the temperature and flow changes, where they showed robustness just with the preview conditions established of temperature and flow, abrupt changes may influence with the results of methods
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The effect of nitrogen on the root system of the species Panicum maximum Jacq. cv. IPR-86 Mil (e) over cap nio, under grazing, was evaluated. The N rates were 0; 150; 300 and 450 kg/ha. year. The root density was evaluated during pregrazing at five years of successive N application, in three depths (0-10; 10-20 and 20-40 cm) and the root growth at 7, 14, 21, and 35 days after grazing. The grazing method adopted was rotational stocking. Root length and root mass densities in pre-and post-grazing presented maximum values at rates 204, 206, 192, and 197 kg/ha of N, respectively. The root growth (in root length density) increased, on average, until 29 days after grazing at rates 0, 150, and 300 kg/ha; at 450 kg/ha N rate, the increase was linear. Independently of N rates, around 60 and 25% of IPR-86 Mil (e) over cap nio cultivar root system was concentrated in 0-10 and 10-20 cm depth, respectively.
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This work presents the positional nonlinear geometric formulation for trusses using different strain measures. The positional formulation presents an alternative approach for nonlinear problems. This formulation considers nodal positions as variables of the nonlinear system instead of displacements (widely found in literature). The work also describes the arc-length method used for tracing equilibrium paths with snap-through and snap-back. Numerical applications for trusses already established in the literature and comparisons with other studies are provided to prove the accuracy of the proposed formulation
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In last decades, neural networks have been established as a major tool for the identification of nonlinear systems. Among the various types of networks used in identification, one that can be highlighted is the wavelet neural network (WNN). This network combines the characteristics of wavelet multiresolution theory with learning ability and generalization of neural networks usually, providing more accurate models than those ones obtained by traditional networks. An extension of WNN networks is to combine the neuro-fuzzy ANFIS (Adaptive Network Based Fuzzy Inference System) structure with wavelets, leading to generate the Fuzzy Wavelet Neural Network - FWNN structure. This network is very similar to ANFIS networks, with the difference that traditional polynomials present in consequent of this network are replaced by WNN networks. This paper proposes the identification of nonlinear dynamical systems from a network FWNN modified. In the proposed structure, functions only wavelets are used in the consequent. Thus, it is possible to obtain a simplification of the structure, reducing the number of adjustable parameters of the network. To evaluate the performance of network FWNN with this modification, an analysis of network performance is made, verifying advantages, disadvantages and cost effectiveness when compared to other existing FWNN structures in literature. The evaluations are carried out via the identification of two simulated systems traditionally found in the literature and a real nonlinear system, consisting of a nonlinear multi section tank. Finally, the network is used to infer values of temperature and humidity inside of a neonatal incubator. The execution of such analyzes is based on various criteria, like: mean squared error, number of training epochs, number of adjustable parameters, the variation of the mean square error, among others. The results found show the generalization ability of the modified structure, despite the simplification performed
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Foi estudada a transferência de calor transiente na agitação linear e intermitente (ALI) de embalagens metálicas contendo simulantes de alimentos, objetivando-se sua aplicação em processos de pasteurização ou esterilização e conseqüentes tratamentos térmicos mais eficientes, homogêneos e com produto de melhor qualidade. Foram utilizados quatro meios fluidos simulantes de alimentos de diferentes viscosidades e massas específicas: três óleos e água. Foram combinados efeitos de cinco tratamentos, sendo: meio simulante (4 níveis), espaço livre (3 níveis), freqüência de agitação (4 níveis), amplitude de agitação (2 níveis) e posição das latas (4 níveis). Os ensaios de aquecimento e resfriamento foram feitos em tanque com água à temperatura de 98 °C e 17-20 °C, respectivamente. Com os dados de penetração de calor em cada experimento, foram calculados os parâmetros de penetração de calor fh, jh, fc e jc. Os resultados foram modelados utilizando-se grupos de números adimensionais e expressos em termos de Nusselt, Prandtl, Reynolds e funções trigonométricas (com medidas de amplitude e freqüência de agitação, espaço livre e dimensões da embalagem). Foram estabelecidas as duas Equações gerais para as fases de aquecimento e resfriamento: Nu = ReA 0,199.Pr 0,288.sen(xa/AM)0,406.cos(xf/FA) 1,039.cos((xf/FA).(EL/H).p) 4,556 Aquecimento Nu = 0,1295.ReA 0,047.Pr 0,193.sen(xa/AM)0,114.cos(xf/FA) 0,641.cos((xf/FA).(EL/H).p) 2,476 Resfriamento O processo de ALI pode ser aplicado em pasteurizadores ou autoclaves estáticas horizontais e verticais, com modificações simples. Concluiu-se que a ALI aumenta significativamente a taxa de transferência de calor, tanto no aquecimento como no resfriamento.
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Objetivou-se com este trabalho, desenvolver modelos de programação não-linear para sistematização de terras, aplicáveis para áreas com formato regular e que minimizem a movimentação de terra, utilizando o software GAMS para o cálculo. Esses modelos foram comparados com o Método dos Quadrados Mínimos Generalizado, desenvolvido por Scaloppi & Willardson (1986), sendo o parâmetro de avaliação o volume de terra movimentado. Concluiu-se que, ambos os modelos de programação não-linear desenvolvidos nesta pesquisa mostraram-se adequados para aplicação em áreas regulares e forneceram menores valores de movimentação de terra quando comparados com o método dos quadrados mínimos.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Slugging is a well-known slugging phenomenon in multiphase flow, which may cause problems such as vibration in pipeline and high liquid level in the separator. It can be classified according to the place of its occurrence. The most severe, known as slugging in the riser, occurs in the vertical pipe which feeds the platform. Also known as severe slugging, it is capable of causing severe pressure fluctuations in the flow of the process, excessive vibration, flooding in separator tanks, limited production, nonscheduled stop of production, among other negative aspects that motivated the production of this work . A feasible solution to deal with this problem would be to design an effective method for the removal or reduction of the system, a controller. According to the literature, a conventional PID controller did not produce good results due to the high degree of nonlinearity of the process, fueling the development of advanced control techniques. Among these, the model predictive controller (MPC), where the control action results from the solution of an optimization problem, it is robust, can incorporate physical and /or security constraints. The objective of this work is to apply a non-conventional non-linear model predictive control technique to severe slugging, where the amount of liquid mass in the riser is controlled by the production valve and, indirectly, the oscillation of flow and pressure is suppressed, while looking for environmental and economic benefits. The proposed strategy is based on the use of the model linear approximations and repeatedly solving of a quadratic optimization problem, providing solutions that improve at each iteration. In the event where the convergence of this algorithm is satisfied, the predicted values of the process variables are the same as to those obtained by the original nonlinear model, ensuring that the constraints are satisfied for them along the prediction horizon. A mathematical model recently published in the literature, capable of representing characteristics of severe slugging in a real oil well, is used both for simulation and for the project of the proposed controller, whose performance is compared to a linear MPC
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Stochastic stability for Markovian jump linear systems associated with a finite number of jump times
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This paper deals with a stochastic stability concept for discrete-time Markovian jump linear systems. The random jump parameter is associated to changes between the system operation modes due to failures or repairs, which can be well described by an underlying finite-state Markov chain. In the model studied, a fixed number of failures or repairs is allowed, after which, the system is brought to a halt for maintenance or for replacement. The usual concepts of stochastic stability are related to pure infinite horizon problems, and are not appropriate in this scenario. A new stability concept is introduced, named stochastic tau-stability that is tailored to the present setting. Necessary and sufficient conditions to ensure the stochastic tau-stability are provided, and the almost sure stability concept associated with this class of processes is also addressed. The paper also develops equivalences among second order concepts that parallels the results for infinite horizon problems. (C) 2003 Elsevier B.V. All rights reserved.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The accurate identification of the nitrogen content in plants is extremely important since it involves economic aspects and environmental impacts, Several experimental tests have been carried out to obtain characteristics and parameters associated with the health of plants and its growing. The nitrogen content identification in plants involves a lot of non-linear parameters and complexes mathematical models. This paper describes a novel approach for identification of nitrogen content thought SPAD index using artificial neural networks (ANN). The network acts as identifier of relationships among, crop varieties, fertilizer treatments, type of leaf and nitrogen content in the plants (target). So, nitrogen content can be generalized and estimated and from an input parameter set. This approach can form the basis for development of an accurate real time system to predict nitrogen content in plants.