976 resultados para Linear quadratic regulator controllers


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The purpose of this research was to combine the use of the component blend design to the response surface methodology, in order to foresee the effect of ternary apple juice blends (Catarina, Granny Smith and Pink Lady cultivars) on the physical-chemical characteristics of musts appointed to sparkling drink elaboration. Twelve mixes were made (three individual samples, three binary mixes and six ternary mixes), analyzed on the content of total reducing sugars, total titratable acidity and phenolic compounds; and adjusted, respectively, to the linear, quadratic and special cubic models. The results were organized in ternary charts of surface response and, from the overlap of these charts, it was determined a viable region which delimited the range of apple juice compositions that make musts physically and chemically suitable to sparkling drink elaboration. To represent the various possible combinations, the central point of the triangular area of the viable region was calculated and, this point, which represents the proportions of 23.22% of Catarina, 66.23% of Granny Smith and 10.55% of Pink Lady cultivars, was chosen to constitute the formulation of the must to be used in the elaboration of apple sparkling drinks.

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The objective of this study was to evaluate the effect of the addition of oatmeal and palm fat in the elaboration of biscuits with added L-leucine and calcium in order to develop a product for sarcopenia in the elderly. The biscuits, or cookies, were elaborated applying a central composite rotational design with surface response methodology, and the significant linear, quadratic and interaction terms were used in the second order mathematical model. Physical, physicochemical and sensory analyses were performed by a trained panel. Based on the best results obtained, three cookie formulations were selected for sensory evaluation by the target group and physicochemical determinations. The formulations with the highest sensory scores for appearance and texture and medium scores for color and expansion index were selected. The addition of calcium and leucine increased significantly the concentration of these components in the biscuits elaborated resulting in a cookie with more than 30% of DRI (Dietary Reference Intake) for calcium and leucine. The formulations selected showed high acceptance by the target group; therefore, they can be included in the diet of elderly with sarcopenia as a functional food.

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Un modèle de croissance et de réponse à la radiothérapie pour le glioblastome multiforme (GBM) basé le formalisme du modèle de prolifération-invasion (PI) et du modèle linéaire-quadratique a été développé et implémenté. La géométrie spécifique au patient est considérée en modélisant, d'une part, les voies d'invasion possibles des GBM avec l'imagerie du tenseur de diffusion (DTI) et, d'autre part, les barrières à la propagation à partir des images anatomiques disponibles. La distribution de dose réelle reçue par un patient donné est appliquée telle quelle dans les simulations, en respectant l'horaire de traitement. Les paramètres libres du modèle (taux de prolifération, coefficient de diffusion, paramètres radiobiologiques) sont choisis aléatoirement à partir de distributions de valeurs plausibles. Un total de 400 ensembles de valeurs pour les paramètres libres sont ainsi choisis pour tous les patients, et une simulation de la croissance et de la réponse au traitement est effectuée pour chaque patient et chaque ensemble de paramètres. Un critère de récidive est appliqué sur les résultats de chaque simulation pour identifier un lieu probable de récidive (SPR). La superposition de tous les SPR obtenus pour un patient donné permet de définir la probabilité d'occurrence (OP). Il est démontré qu'il existe des valeurs de OP élevées pour tous les patients, impliquant que les résultats du modèle PI ne sont pas très sensibles aux valeurs des paramètres utilisés. Il est également démontré comment le formalisme développé dans cet ouvrage pourrait permettre de définir un volume cible personnalisé pour les traitements de radiothérapie du GBM.

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The experimental variogram computed in the usual way by the method of moments and the Haar wavelet transform are similar in that they filter data and yield informative summaries that may be interpreted. The variogram filters out constant values; wavelets can filter variation at several spatial scales and thereby provide a richer repertoire for analysis and demand no assumptions other than that of finite variance. This paper compares the two functions, identifying that part of the Haar wavelet transform that gives it its advantages. It goes on to show that the generalized variogram of order k=1, 2, and 3 filters linear, quadratic, and cubic polynomials from the data, respectively, which correspond with more complex wavelets in Daubechies's family. The additional filter coefficients of the latter can reveal features of the data that are not evident in its usual form. Three examples in which data recorded at regular intervals on transects are analyzed illustrate the extended form of the variogram. The apparent periodicity of gilgais in Australia seems to be accentuated as filter coefficients are added, but otherwise the analysis provides no new insight. Analysis of hyerpsectral data with a strong linear trend showed that the wavelet-based variograms filtered it out. Adding filter coefficients in the analysis of the topsoil across the Jurassic scarplands of England changed the upper bound of the variogram; it then resembled the within-class variogram computed by the method of moments. To elucidate these results, we simulated several series of data to represent a random process with values fluctuating about a mean, data with long-range linear trend, data with local trend, and data with stepped transitions. The results suggest that the wavelet variogram can filter out the effects of long-range trend, but not local trend, and of transitions from one class to another, as across boundaries.

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An algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimization and Parameter Estimation (DISOPE), which achieves the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimization procedure. A version of the algorithm with a linear-quadratic model-based problem, implemented in the C+ + programming language, is developed and applied to illustrative simulation examples. An analysis of the optimality and convergence properties of the algorithm is also presented.

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In this paper, a discrete time dynamic integrated system optimisation and parameter estimation algorithm is applied to the solution of the nonlinear tracking optimal control problem. A version of the algorithm with a linear-quadratic model-based problem is developed and implemented in software. The algorithm implemented is tested with simulation examples.

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Based on integrated system optimisation and parameter estimation a method is described for on-line steady state optimisation which compensates for model-plant mismatch and solves a non-linear optimisation problem by iterating on a linear - quadratic representation. The method requires real process derivatives which are estimated using a dynamic identification technique. The utility of the method is demonstrated using a simulation of the Tennessee Eastman benchmark chemical process.

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A novel iterative procedure is described for solving nonlinear optimal control problems subject to differential algebraic equations. The procedure iterates on an integrated modified linear quadratic model based problem with parameter updating in such a manner that the correct solution of the original non-linear problem is achieved. The resulting algorithm has a particular advantage in that the solution is achieved without the need to solve the differential algebraic equations . Convergence aspects are discussed and a simulation example is described which illustrates the performance of the technique. 1. Introduction When modelling industrial processes often the resulting equations consist of coupled differential and algebraic equations (DAEs). In many situations these equations are nonlinear and cannot readily be directly reduced to ordinary differential equations.

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This paper presents the mathematical development of a body-centric nonlinear dynamic model of a quadrotor UAV that is suitable for the development of biologically inspired navigation strategies. Analytical approximations are used to find an initial guess of the parameters of the nonlinear model, then parameter estimation methods are used to refine the model parameters using the data obtained from onboard sensors during flight. Due to the unstable nature of the quadrotor model, the identification process is performed with the system in closed-loop control of attitude angles. The obtained model parameters are validated using real unseen experimental data. Based on the identified model, a Linear-Quadratic (LQ) optimal tracker is designed to stabilize the quadrotor and facilitate its translational control by tracking body accelerations. The LQ tracker is tested on an experimental quadrotor UAV and the obtained results are a further means to validate the quality of the estimated model. The unique formulation of the control problem in the body frame makes the controller better suited for bio-inspired navigation and guidance strategies than conventional attitude or position based control systems that can be found in the existing literature.

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This study aimed to optimize the rheological properties of probiotic yoghurts supplemented with skimmed milk powder (SMP) whey protein concentrate (WPC) and sodium caseinate (Na-Cn) by using an experimental design type simplex-centroid for mixture modeling It Included seven batches/trials three were supplemented with each type of the dairy protein used three corresponding to the binary mixtures and one to the ternary one in order to increase protein concentration in 1 g 100 g(-1) of final product A control experiment was prepared without supplementing the milk base Processed milk bases were fermented at 42 C until pH 4 5 by using a starter culture blend that consisted of Streptococcus thermophilus Lactobacillus delbrueckii subsp bulgaricus and Bifidobacterium (Humans subsp lactis The kinetics of acidification was followed during the fermentation period as well the physico-chemical analyses enumeration of viable bacteria and theological characteristics of the yoghurts Models were adjusted to the results (kinetic responses counts of viable bacteria and theological parameters) through three regression models (linear quadratic and cubic special) applied to mixtures The results showed that the addition of milk proteins affected slightly acidification profile and counts of S thermophilus and B animal`s subsp lactis but it was significant for L delbrueckii subsp bulgaricus Partially-replacing SMP (45 g/100 g) with WPC or Na-Cn simultaneously enhanced the theological properties of probiotic yoghurts taking into account the kinetics of acidification and enumeration of viable bacteria (C) 2010 Elsevier Ltd All rights reserved

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Anaerobic threshold (AT) is usually estimated as a change point problem by visual analysis of the cardiorespiratory response to incremental dynamic exercise. In this study, two phase linear (TPL) models of the linear-linear and linear-quadratic type were used for the estimation of AT. The correlation coefficient between the classical and statistical approaches was 0.88, and 0.89 after outlier exclusion. The TPL models provide a simple method for estimating AT that can be easily implemented using a digital computer for the automatic pattern recognition of AT.