921 resultados para Non-autonomous systems
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In this paper a method of solving certain third-order non-linear systems by using themethod of ultraspherical polynomial approximation is proposed. By using the method of variation of parameters the third-order equation is reduced to three partial differential equations. Instead of being averaged over a cycle, the non-linear functions are expanded in ultraspherical polynomials and with only the constant term retained, the equations are solved. The results of the procedure are compared with the numerical solutions obtained on a digital computer. A degenerate third-order system is also considered and results obtained for the above system are compared with numerical results obtained on the digital computer. There is good agreement between the results obtained by the proposed method and the numerical solution obtained on digital computer.
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The problem of updating the reliability of instrumented structures based on measured response under random dynamic loading is considered. A solution strategy within the framework of Monte Carlo simulation based dynamic state estimation method and Girsanov's transformation for variance reduction is developed. For linear Gaussian state space models, the solution is developed based on continuous version of the Kalman filter, while, for non-linear and (or) non-Gaussian state space models, bootstrap particle filters are adopted. The controls to implement the Girsanov transformation are developed by solving a constrained non-linear optimization problem. Numerical illustrations include studies on a multi degree of freedom linear system and non-linear systems with geometric and (or) hereditary non-linearities and non-stationary random excitations.
Resumo:
The problem of updating the reliability of instrumented structures based on measured response under random dynamic loading is considered. A solution strategy within the framework of Monte Carlo simulation based dynamic state estimation method and Girsanov’s transformation for variance reduction is developed. For linear Gaussian state space models, the solution is developed based on continuous version of the Kalman filter, while, for non-linear and (or) non-Gaussian state space models, bootstrap particle filters are adopted. The controls to implement the Girsanov transformation are developed by solving a constrained non-linear optimization problem. Numerical illustrations include studies on a multi degree of freedom linear system and non-linear systems with geometric and (or) hereditary non-linearities and non-stationary random excitations.
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The use of transmission matrices and lumped parameter models for describing continuous systems is the subject of this study. Non-uniform continuous systems which play important roles in practical vibration problems, e.g., torsional oscillations in bars, transverse bending vibrations of beams, etc., are of primary importance.
A new approach for deriving closed form transmission matrices is applied to several classes of non-uniform continuous segments of one dimensional and beam systems. A power series expansion method is presented for determining approximate transmission matrices of any order for segments of non-uniform systems whose solutions cannot be found in closed form. This direct series method is shown to give results comparable to those of the improved lumped parameter models for one dimensional systems.
Four types of lumped parameter models are evaluated on the basis of the uniform continuous one dimensional system by comparing the behavior of the frequency root errors. The lumped parameter models which are based upon a close fit to the low frequency approximation of the exact transmission matrix, at the segment level, are shown to be superior. On this basis an improved lumped parameter model is recommended for approximating non-uniform segments. This new model is compared to a uniform segment approximation and error curves are presented for systems whose areas very quadratically and linearly. The effect of varying segment lengths is investigated for one dimensional systems and results indicate very little improvement in comparison to the use of equal length segments. For purposes of completeness, a brief summary of various lumped parameter models and other techniques which have previously been used to approximate the uniform Bernoulli-Euler beam is a given.
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The feedback coding problem for Gaussian systems in which the noise is neither white nor statistically independent between channels is formulated in terms of arbitrary linear codes at the transmitter and at the receiver. This new formulation is used to determine a number of feedback communication systems. In particular, the optimum linear code that satisfies an average power constraint on the transmitted signals is derived for a system with noiseless feedback and forward noise of arbitrary covariance. The noisy feedback problem is considered and signal sets for the forward and feedback channels are obtained with an average power constraint on each. The general formulation and results are valid for non-Gaussian systems in which the second order statistics are known, the results being applicable to the determination of error bounds via the Chebychev inequality.
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Este estudo teve como objetivo geral analisar a qualidade de vida e suas representações em momentos distintos de diagnóstico entre pessoas que vivem com o HIV/aids, no município de Rio das Ostras, Rio de Janeiro. O estudo foi apoiado na teoria das representações sociais associada ao constructo da qualidade de vida. Realizou-se estudo quali-quantitativo, desenvolvido no Programa de DST, AIDS e Hepatites Virais do município de Rio das Ostras, tendo como sujeitos e amostra 100 pessoas que viviam com HIV/aids. A amostra foi estratificada, contando com 50 pessoas com tempo de diagnóstico de até 6 meses e 50 superior a 6 meses. A coleta de dados se deu através da aplicação de um questionário de caracterização socioeconômica e clínica, instrumento WHOQOL-HIV-Bref e entrevistas semiestruturadas, durante o período compreendido entre os meses de maio de 2013 a janeiro de 2014. Todos os sujeitos responderam aos dois primeiros instrumentos, e para as entrevistas foi constituída uma subamostra de 40 pessoas, igualmente distribuídas em dois grupos de acordo com o tempo de diagnóstico. A análise dos dados foi realizada através de estatística descritiva e inferencial utilizando o software SPSS 17.0. A análise das representações sociais foi apoiada pelo software Alceste 4.10. O grupo estudado caracterizou-se igualitariamente entre os sexos, com orientação religiosa evangélica (36%), média de idade de 37,6 anos, residentes no município de tratamento (89%), escolaridade fundamental e média incompleta (48%), empregados (65%), com renda pessoal média de R$ 1.077,00, com tempo de diagnóstico menor que quatro anos (68%), em uso de terapia antirretroviral (74%) e tempo de uso de terapia antirretroviral menor que quatro anos (52%). Os resultados da análise da qualidade de vida demonstraram que os escores dos domínios espiritualidade/religião/crenças pessoais (14,61) e relações sociais (14,52) apresentaram as maiores médias brutas, dentre aquelas com tendência positiva de avaliação. As médias mais baixas recaíram nos domínios nível de independência (13,77) e meio ambiente (13,29). Observou-se que o tempo de diagnóstico não interferiu nos escores de qualidade de vida da amostra. A representação da qualidade de vida revelou-se constituída por conteúdos associados às expectativas futuras, qualidade de vida frente ao diagnóstico, enfrentamento, uso do antirretroviral, transmissão e prevenção. Nesses conteúdos observou-se que essa representação compartilha significados, apontando para a hipótese de representação não autônoma em relação a representação social da aids. Conclui-se que o grupo possui mecanismos de adaptação à situação vivenciada, revelando percepção da necessidade de autocuidado e manutenção de uma rede de apoio alicerçada na espiritualidade/religiosidade e nas relações sociais, o que faz crer existir um caminhar progressivo para novos sistemas de interpretação, regendo relações mais positivas e objetivadas na representação social da qualidade de vida.
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Pattison,T. and Wilson,M.S., 'Flocking in Simulation and Robots - A Review', Towards Intelligent Mobile Robots; Proceedings of the 4th annual British conference on autonomous mobile robotics and autonomous systems (TIMR'03), 2003, pp 90-99
Resumo:
M.H. Lee, Q. Meng and F. Chao, 'Developmental Learning for Autonomous Robots', Robotics and Autonomous Systems, 55(9), pp 750-759, 2007.
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The present study aimed to investigate interactions of components in the high solids systems during storage. The systems included (i) lactose–maltodextrin (MD) with various dextrose equivalents at different mixing ratios, (ii) whey protein isolate (WPI)–oil [olive oil (OO) or sunflower oil (SO)] at 75:25 ratio, and (iii) WPI–oil– {glucose (G)–fructose (F) 1:1 syrup [70% (w/w) total solids]} at a component ratio of 45:15:40. Crystallization of lactose was delayed and increasingly inhibited with increasing MD contents and higher DE values (small molecular size or low molecular weight), although all systems showed similar glass transition temperatures at each aw. The water sorption isotherms of non-crystalline lactose and lactose–MD (0.11 to 0.76 aw) could be derived from the sum of sorbed water contents of individual amorphous components. The GAB equation was fitted to data of all non-crystalline systems. The protein–oil and protein–oil–sugar materials showed maximum protein oxidation and disulfide bonding at 2 weeks of storage at 20 and 40°C. The WPI–OO showed denaturation and preaggregation of proteins during storage at both temperatures. The presence of G–F in WPI–oil increased Tonset and Tpeak of protein aggregation, and oxidative damage of the protein during storage, especially in systems with a higher level of unsaturated fatty acids. Lipid oxidation and glycation products in the systems containing sugar promoted oxidation of proteins, increased changes in protein conformation and aggregation of proteins, and resulted in insolubility of solids or increased hydrophobicity concomitantly with hardening of structure, covalent crosslinking of proteins, and formation of stable polymerized solids, especially after storage at 40°C. We found protein hydration transitions preceding denaturation transitions in all high protein systems and also the glass transition of confined water in protein systems using dynamic mechanical analysis.
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Sufficient conditions for the exponential stability of a class ofnonlinear, non-autonomous stochastic differential equations in infinitedimensions are studied. The analysis consists of introducing a suitableapproximating solution systems and using a limiting argument to pass onstability of strong solutions to mild ones. As a consequence, the classicalcriteriaof stability in A. Ichikawa [8] are improved and extended to cover a class ofnon-autonomous stochastic evolution equations.Two examples are investigated to illustrate our theory.
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A combination of scientific, economic, technological and policy drivers is behind a recent upsurge in the use of marine autonomous systems (and accompanying miniaturized sensors) for environmental mapping and monitoring. Increased spatial–temporal resolution and coverage of data, at reduced cost, is particularly vital for effective spatial management of highly dynamic and heterogeneous shelf environments. This proof-of-concept study involves integration of a novel combination of sensors onto buoyancy-driven submarine gliders, in order to assess their suitability for ecosystem monitoring in shelf waters at a variety of trophic levels. Two shallow-water Slocum gliders were equipped with CTD and fluorometer to measure physical properties and chlorophyll, respectively. One glider was also equipped with a single-frequency echosounder to collect information on zooplankton and fish distribution. The other glider carried a Passive Acoustic Monitoring system to detect and record cetacean vocalizations, and a passive sampler to detect chemical contaminants in the water column. The two gliders were deployed together off southwest UK in autumn 2013, and targeted a known tidal-mixing front west of the Isles of Scilly. The gliders’ mission took about 40 days, with each glider travelling distances of >1000 km and undertaking >2500 dives to depths of up to 100 m. Controlling glider flight and alignment of the two glider trajectories proved to be particularly challenging due to strong tidal flows. However, the gliders continued to collect data in poor weather when an accompanying research vessel was unable to operate. In addition, all glider sensors generated useful data, with particularly interesting initial results relating to subsurface chlorophyll maxima and numerous fish/cetacean detections within the water column. The broader implications of this study for marine ecosystem monitoring with submarine gliders are discussed.
Resumo:
A combination of scientific, economic, technological and policy drivers is behind a recent upsurge in the use of marine autonomous systems (and accompanying miniaturized sensors) for environmental mapping and monitoring. Increased spatial–temporal resolution and coverage of data, at reduced cost, is particularly vital for effective spatial management of highly dynamic and heterogeneous shelf environments. This proof-of-concept study involves integration of a novel combination of sensors onto buoyancy-driven submarine gliders, in order to assess their suitability for ecosystem monitoring in shelf waters at a variety of trophic levels. Two shallow-water Slocum gliders were equipped with CTD and fluorometer to measure physical properties and chlorophyll, respectively. One glider was also equipped with a single-frequency echosounder to collect information on zooplankton and fish distribution. The other glider carried a Passive Acoustic Monitoring system to detect and record cetacean vocalizations, and a passive sampler to detect chemical contaminants in the water column. The two gliders were deployed together off southwest UK in autumn 2013, and targeted a known tidal-mixing front west of the Isles of Scilly. The gliders’ mission took about 40 days, with each glider travelling distances of >1000 km and undertaking >2500 dives to depths of up to 100 m. Controlling glider flight and alignment of the two glider trajectories proved to be particularly challenging due to strong tidal flows. However, the gliders continued to collect data in poor weather when an accompanying research vessel was unable to operate. In addition, all glider sensors generated useful data, with particularly interesting initial results relating to subsurface chlorophyll maxima and numerous fish/cetacean detections within the water column. The broader implications of this study for marine ecosystem monitoring with submarine gliders are discussed.
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The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.
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In this paper we introduce a formation control loop that maximizes the performance of the cooperative perception of a tracked target by a team of mobile robots, while maintaining the team in formation, with a dynamically adjustable geometry which is a function of the quality of the target perception by the team. In the formation control loop, the controller module is a distributed non-linear model predictive controller and the estimator module fuses local estimates of the target state, obtained by a particle filter at each robot. The two modules and their integration are described in detail, including a real-time database associated to a wireless communication protocol that facilitates the exchange of state data while reducing collisions among team members. Simulation and real robot results for indoor and outdoor teams of different robots are presented. The results highlight how our method successfully enables a team of homogeneous robots to minimize the total uncertainty of the tracked target cooperative estimate while complying with performance criteria such as keeping a pre-set distance between the teammates and the target, avoiding collisions with teammates and/or surrounding obstacles.
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L'objectif du présent mémoire vise à présenter des modèles de séries chronologiques multivariés impliquant des vecteurs aléatoires dont chaque composante est non-négative. Nous considérons les modèles vMEM (modèles vectoriels et multiplicatifs avec erreurs non-négatives) présentés par Cipollini, Engle et Gallo (2006) et Cipollini et Gallo (2010). Ces modèles représentent une généralisation au cas multivarié des modèles MEM introduits par Engle (2002). Ces modèles trouvent notamment des applications avec les séries chronologiques financières. Les modèles vMEM permettent de modéliser des séries chronologiques impliquant des volumes d'actif, des durées, des variances conditionnelles, pour ne citer que ces applications. Il est également possible de faire une modélisation conjointe et d'étudier les dynamiques présentes entre les séries chronologiques formant le système étudié. Afin de modéliser des séries chronologiques multivariées à composantes non-négatives, plusieurs spécifications du terme d'erreur vectoriel ont été proposées dans la littérature. Une première approche consiste à considérer l'utilisation de vecteurs aléatoires dont la distribution du terme d'erreur est telle que chaque composante est non-négative. Cependant, trouver une distribution multivariée suffisamment souple définie sur le support positif est plutôt difficile, au moins avec les applications citées précédemment. Comme indiqué par Cipollini, Engle et Gallo (2006), un candidat possible est une distribution gamma multivariée, qui impose cependant des restrictions sévères sur les corrélations contemporaines entre les variables. Compte tenu que les possibilités sont limitées, une approche possible est d'utiliser la théorie des copules. Ainsi, selon cette approche, des distributions marginales (ou marges) peuvent être spécifiées, dont les distributions en cause ont des supports non-négatifs, et une fonction de copule permet de tenir compte de la dépendance entre les composantes. Une technique d'estimation possible est la méthode du maximum de vraisemblance. Une approche alternative est la méthode des moments généralisés (GMM). Cette dernière méthode présente l'avantage d'être semi-paramétrique dans le sens que contrairement à l'approche imposant une loi multivariée, il n'est pas nécessaire de spécifier une distribution multivariée pour le terme d'erreur. De manière générale, l'estimation des modèles vMEM est compliquée. Les algorithmes existants doivent tenir compte du grand nombre de paramètres et de la nature élaborée de la fonction de vraisemblance. Dans le cas de l'estimation par la méthode GMM, le système à résoudre nécessite également l'utilisation de solveurs pour systèmes non-linéaires. Dans ce mémoire, beaucoup d'énergies ont été consacrées à l'élaboration de code informatique (dans le langage R) pour estimer les différents paramètres du modèle. Dans le premier chapitre, nous définissons les processus stationnaires, les processus autorégressifs, les processus autorégressifs conditionnellement hétéroscédastiques (ARCH) et les processus ARCH généralisés (GARCH). Nous présentons aussi les modèles de durées ACD et les modèles MEM. Dans le deuxième chapitre, nous présentons la théorie des copules nécessaire pour notre travail, dans le cadre des modèles vectoriels et multiplicatifs avec erreurs non-négatives vMEM. Nous discutons également des méthodes possibles d'estimation. Dans le troisième chapitre, nous discutons les résultats des simulations pour plusieurs méthodes d'estimation. Dans le dernier chapitre, des applications sur des séries financières sont présentées. Le code R est fourni dans une annexe. Une conclusion complète ce mémoire.