863 resultados para Interval Linear Systems


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The aim of this thesis is to narrow the gap between two different control techniques: the continuous control and the discrete event control techniques DES. This gap can be reduced by the study of Hybrid systems, and by interpreting as Hybrid systems the majority of large-scale systems. In particular, when looking deeply into a process, it is often possible to identify interaction between discrete and continuous signals. Hybrid systems are systems that have both continuous, and discrete signals. Continuous signals are generally supposed continuous and differentiable in time, since discrete signals are neither continuous nor differentiable in time due to their abrupt changes in time. Continuous signals often represent the measure of natural physical magnitudes such as temperature, pressure etc. The discrete signals are normally artificial signals, operated by human artefacts as current, voltage, light etc. Typical processes modelled as Hybrid systems are production systems, chemical process, or continuos production when time and continuous measures interacts with the transport, and stock inventory system. Complex systems as manufacturing lines are hybrid in a global sense. They can be decomposed into several subsystems, and their links. Another motivation for the study of Hybrid systems is the tools developed by other research domains. These tools benefit from the use of temporal logic for the analysis of several properties of Hybrid systems model, and use it to design systems and controllers, which satisfies physical or imposed restrictions. This thesis is focused in particular types of systems with discrete and continuous signals in interaction. That can be modelled hard non-linealities, such as hysteresis, jumps in the state, limit cycles, etc. and their possible non-deterministic future behaviour expressed by an interpretable model description. The Hybrid systems treated in this work are systems with several discrete states, always less than thirty states (it can arrive to NP hard problem), and continuous dynamics evolving with expression: with Ki ¡ Rn constant vectors or matrices for X components vector. In several states the continuous evolution can be several of them Ki = 0. In this formulation, the mathematics can express Time invariant linear system. By the use of this expression for a local part, the combination of several local linear models is possible to represent non-linear systems. And with the interaction with discrete events of the system the model can compose non-linear Hybrid systems. Especially multistage processes with high continuous dynamics are well represented by the proposed methodology. Sate vectors with more than two components, as third order models or higher is well approximated by the proposed approximation. Flexible belt transmission, chemical reactions with initial start-up and mobile robots with important friction are several physical systems, which profits from the benefits of proposed methodology (accuracy). The motivation of this thesis is to obtain a solution that can control and drive the Hybrid systems from the origin or starting point to the goal. How to obtain this solution, and which is the best solution in terms of one cost function subject to the physical restrictions and control actions is analysed. Hybrid systems that have several possible states, different ways to drive the system to the goal and different continuous control signals are problems that motivate this research. The requirements of the system on which we work is: a model that can represent the behaviour of the non-linear systems, and that possibilities the prediction of possible future behaviour for the model, in order to apply an supervisor which decides the optimal and secure action to drive the system toward the goal. Specific problems can be determined by the use of this kind of hybrid models are: - The unity of order. - Control the system along a reachable path. - Control the system in a safe path. - Optimise the cost function. - Modularity of control The proposed model solves the specified problems in the switching models problem, the initial condition calculus and the unity of the order models. Continuous and discrete phenomena are represented in Linear hybrid models, defined with defined eighth-tuple parameters to model different types of hybrid phenomena. Applying a transformation over the state vector : for LTI system we obtain from a two-dimensional SS a single parameter, alpha, which still maintains the dynamical information. Combining this parameter with the system output, a complete description of the system is obtained in a form of a graph in polar representation. Using Tagaki-Sugeno type III is a fuzzy model which include linear time invariant LTI models for each local model, the fuzzyfication of different LTI local model gives as a result a non-linear time invariant model. In our case the output and the alpha measure govern the membership function. Hybrid systems control is a huge task, the processes need to be guided from the Starting point to the desired End point, passing a through of different specific states and points in the trajectory. The system can be structured in different levels of abstraction and the control in three layers for the Hybrid systems from planning the process to produce the actions, these are the planning, the process and control layer. In this case the algorithms will be applied to robotics ¡V a domain where improvements are well accepted ¡V it is expected to find a simple repetitive processes for which the extra effort in complexity can be compensated by some cost reductions. It may be also interesting to implement some control optimisation to processes such as fuel injection, DC-DC converters etc. In order to apply the RW theory of discrete event systems on a Hybrid system, we must abstract the continuous signals and to project the events generated for these signals, to obtain new sets of observable and controllable events. Ramadge & Wonham¡¦s theory along with the TCT software give a Controllable Sublanguage of the legal language generated for a Discrete Event System (DES). Continuous abstraction transforms predicates over continuous variables into controllable or uncontrollable events, and modifies the set of uncontrollable, controllable observable and unobservable events. Continuous signals produce into the system virtual events, when this crosses the bound limits. If this event is deterministic, they can be projected. It is necessary to determine the controllability of this event, in order to assign this to the corresponding set, , controllable, uncontrollable, observable and unobservable set of events. Find optimal trajectories in order to minimise some cost function is the goal of the modelling procedure. Mathematical model for the system allows the user to apply mathematical techniques over this expression. These possibilities are, to minimise a specific cost function, to obtain optimal controllers and to approximate a specific trajectory. The combination of the Dynamic Programming with Bellman Principle of optimality, give us the procedure to solve the minimum time trajectory for Hybrid systems. The problem is greater when there exists interaction between adjacent states. In Hybrid systems the problem is to determine the partial set points to be applied at the local models. Optimal controller can be implemented in each local model in order to assure the minimisation of the local costs. The solution of this problem needs to give us the trajectory to follow the system. Trajectory marked by a set of set points to force the system to passing over them. Several ways are possible to drive the system from the Starting point Xi to the End point Xf. Different ways are interesting in: dynamic sense, minimum states, approximation at set points, etc. These ways need to be safe and viable and RchW. And only one of them must to be applied, normally the best, which minimises the proposed cost function. A Reachable Way, this means the controllable way and safe, will be evaluated in order to obtain which one minimises the cost function. Contribution of this work is a complete framework to work with the majority Hybrid systems, the procedures to model, control and supervise are defined and explained and its use is demonstrated. Also explained is the procedure to model the systems to be analysed for automatic verification. Great improvements were obtained by using this methodology in comparison to using other piecewise linear approximations. It is demonstrated in particular cases this methodology can provide best approximation. The most important contribution of this work, is the Alpha approximation for non-linear systems with high dynamics While this kind of process is not typical, but in this case the Alpha approximation is the best linear approximation to use, and give a compact representation.

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We consider conjugate-gradient like methods for solving block symmetric indefinite linear systems that arise from saddle-point problems or, in particular, regularizations thereof. Such methods require preconditioners that preserve certain sub-blocks from the original systems but allow considerable flexibility for the remaining blocks. We construct a number of families of implicit factorizations that are capable of reproducing the required sub-blocks and (some) of the remainder. These generalize known implicit factorizations for the unregularized case. Improved eigenvalue clustering is possible if additionally some of the noncrucial blocks are reproduced. Numerical experiments confirm that these implicit-factorization preconditioners can be very effective in practice.

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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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With the prospect of exascale computing, computational methods requiring only local data become especially attractive. Consequently, the typical domain decomposition of atmospheric models means horizontally-explicit vertically-implicit (HEVI) time-stepping schemes warrant further attention. In this analysis, Runge-Kutta implicit-explicit schemes from the literature are analysed for their stability and accuracy using a von Neumann stability analysis of two linear systems. Attention is paid to the numerical phase to indicate the behaviour of phase and group velocities. Where the analysis is tractable, analytically derived expressions are considered. For more complicated cases, amplification factors have been numerically generated and the associated amplitudes and phase diagnosed. Analysis of a system describing acoustic waves has necessitated attributing the three resultant eigenvalues to the three physical modes of the system. To do so, a series of algorithms has been devised to track the eigenvalues across the frequency space. The result enables analysis of whether the schemes exactly preserve the non-divergent mode; and whether there is evidence of spurious reversal in the direction of group velocities or asymmetry in the damping for the pair of acoustic modes. Frequency ranges that span next-generation high-resolution weather models to coarse-resolution climate models are considered; and a comparison is made of errors accumulated from multiple stability-constrained shorter time-steps from the HEVI scheme with a single integration from a fully implicit scheme over the same time interval. Two schemes, “Trap2(2,3,2)” and “UJ3(1,3,2)”, both already used in atmospheric models, are identified as offering consistently good stability and representation of phase across all the analyses. Furthermore, according to a simple measure of computational cost, “Trap2(2,3,2)” is the least expensive.

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This work deals with a mathematical fundament for digital signal processing under point view of interval mathematics. Intend treat the open problem of precision and repesention of data in digital systems, with a intertval version of signals representation. Signals processing is a rich and complex area, therefore, this work makes a cutting with focus in systems linear invariant in the time. A vast literature in the area exists, but, some concepts in interval mathematics need to be redefined or to be elaborated for the construction of a solid theory of interval signal processing. We will construct a basic fundaments for signal processing in the interval version, such as basic properties linearity, stability, causality, a version to intervalar of linear systems e its properties. They will be presented interval versions of the convolution and the Z-transform. Will be made analysis of convergences of systems using interval Z-transform , a essentially interval distance, interval complex numbers , application in a interval filter.

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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

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

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

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Em geral, a função de um modelo de impedância para processos de eletrodo simples é deduzida de um modelo elétrico equivalente, denominado circuito de Randles. Neste trabalho estudou-se a generalização dessa função, mediante a introdução de um parâmetro não-elétrico, relacionado com a flexibilidade do ângulo de fase e da magnitude. A função foi ajustada às medidas experimentais de impedância obtidas de um sistema constituído de uma liga Ti-10%Al (m/m) em solução de cloreto de sódio 0,9%, variando-se a amplitude de perturbação. Verificou-se que a função generalizada foi adequada para descrever a impedância do sistema analisado, reduzindo as distorções entre a curva experimental e a curva teórica. Além disso, os melhores resultados foram obtidos para sinais de perturbação do sistema com amplitude igual a 10 mV.

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In this paper, short term hydroelectric scheduling is formulated as a network flow optimization model and solved by interior point methods. The primal-dual and predictor-corrector versions of such interior point methods are developed and the resulting matrix structure is explored. This structure leads to very fast iterations since it avoids computation and factorization of impedance matrices. For each time interval, the linear algebra reduces to the solution of two linear systems, either to the number of buses or to the number of independent loops. Either matrix is invariant and can be factored off-line. As a consequence of such matrix manipulations, a linear system which changes at each iteration has to be solved, although its size is reduced to the number of generating units and is not a function of time intervals. These methods were applied to IEEE and Brazilian power systems, and numerical results were obtained using a MATLAB implementation. Both interior point methods proved to be robust and achieved fast convergence for all instances tested. (C) 2004 Elsevier Ltd. All rights reserved.

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This paper presents necessary and sufficient conditions for the following problem: given a linear time invariant plant G(s) = N(s)D(s)-1 = C(sI - A]-1B, with m inputs, p outputs, p > m, rank(C) = p, rank(B) = rank(CB) = m, £nd a tandem dynamic controller Gc(s) = D c(s)-1Nc(s) = Cc(sI - A c)-1Bc + Dc, with p inputs and m outputs and a constant output feedback matrix Ko ε ℝm×p such that the feedback system is Strictly Positive Real (SPR). It is shown that this problem has solution if and only if all transmission zeros of the plant have negative real parts. When there exists solution, the proposed method firstly obtains Gc(s) in order to all transmission zeros of Gc(s)G(s) present negative real parts and then Ko is found as the solution of some Linear Matrix Inequalities (LMIs). Then, taking into account this result, a new LMI based design for output Variable Structure Control (VSC) of uncertain dynamic plants is presented. The method can consider the following design specifications: matched disturbances or nonlinearities of the plant, output constraints, decay rate and matched and nonmatched plant uncertainties. © 2006 IEEE.

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This paper discusses the dynamic behaviour of a nonlinear two degree-of-freedom system consisting of a harmonically excited linear oscillator weakly connected to a nonlinear attachment that behaves as a hardening Duffing oscillator. A system which behaves in this way could be a shaker (linear system) driving a nonlinear isolator. The mass of the nonlinear system is taken to be much less than that in the linear system and thus the nonlinear system has little effect on the dynamics of the linear system. Of particular interest is the situation when the linear natural frequency of the nonlinear system is less than the natural frequency of the linear system such that the frequency response curve of the nonlinear system bends to higher frequencies and thus interacts with the resonance frequency of the linear system. It is shown that for some values of the system parameters a complicated frequency response curve for the nonlinear system can occur; closed detached curves can appear as a part of the overall amplitude-frequency response. The reason why these detached curves appear is presented and approximate analytical expressions for the jump-up and jump-down frequencies of the system under investigation are given.

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O objetivo deste estudo foi estimar a entropia conjunta do sistema visual humano no domínio do espaço e no domínio das freqüências espaciais através de funções psicométricas. Estas foram obtidas com testes de discriminação de estímulos com luminância ou cromaticidade moduladas por funções de Gábor. A essência do método consistiu em avaliar a entropia no domínio do espaço, testando-se a capacidade do sujeito em discriminar estímulos que diferiam apenas em extensão espacial, e avaliar a entropia no domínio das freqüências espaciais, testando-se a capacidade do sujeito em discriminar estímulos que diferiam apenas em freqüência espacial. A entropia conjunta foi calculada, então, a partir desses dois valores individuais de entropia. Três condições visuais foram estudadas: acromática, cromática sem correção fina para eqüiluminância e cromática com correção para eqüiluminância através de fotometria com flicker heterocromático. Quatro sujeitos foram testados nas três condições, dois sujeitos adicionais foram testados na condição cromática sem eqüiluminância fina e um sétimo sujeito também fez o teste acromático. Todos os sujeitos foram examinados por oftalmologista e considerados normais do ponto de vista oftálmico, não apresentando relato, sintomas ou sinais de disfunções visuais ou de moléstias potencialmente capazes de afetar o sistema visual. Eles tinham acuidade visual normal ou corrigida de no mínimo 20/30. O trabalho foi aprovado pela Comissão de Ética em Pesquisa do Núcleo de Medicina Tropical da UFPA e obedeceu às recomendações da Declaração de Helsinki. As funções de Gábor usadas para modulação de luminância ou cromaticidade compreenderam redes senoidais unidimensionais horizontais, moduladas na direção vertical, dentro de envelopes gaussianos bidimensionais cuja extensão espacial era medida pelo desvio padrão da gaussiana. Os estímulos foram gerados usando-se uma rotina escrita em Pascal num ambiente Delphi 7 Enterprise. Foi utilizado um microcomputador Dell Precision 390 Workstation e um gerador de estímulos CRS VSG ViSaGe para exibir os estímulos num CRT de 20”, 800 x 600 pixels, 120 Hz, padrão RGB, Mitsubishi Diamond Pro 2070SB. Nos experimentos acromáticos, os estímulos foram gerados pela modulação de luminância de uma cor branca correspondente à cromaticidade CIE1931 (x = 0,270; y = 0,280) ou CIE1976 (u’ = 0,186; v’= 0,433) e tinha luminância média de 44,5 cd/m2. Nos experimentos cromáticos, a luminância média foi mantida em 15 cd/m2 e foram usadas duas series de estímulos verde-vermelhos. Os estímulos de uma série foram formados por duas cromaticidades definidas no eixo M-L do Espaço de Cores DKL (CIE1976: verde, u’=0,131, v’=0,380; vermelho, u’=0,216, v’=0,371). Os estímulos da outra série foram formados por duas cromaticidades definidas ao longo de um eixo horizontal verde-vermelho definido no Espaço de Cores CIE1976 (verde, u’=0,150, v’=0,480; vermelho, u’=0,255, v’=0,480). Os estímulos de referência eram compostos por redes de três freqüências espaciais diferentes (0,4, 2 e 10 ciclos por grau) e envelope gaussiano com desvio padrão de 1 grau. Os estímulos de testes eram compostos por uma entre 19 freqüências espaciais diferentes em torno da freqüência espacial de referência e um entre 21 envelopes gaussianos diferentes com desvio padrão em torno de 1 grau. Na condição acromática, foram estudados quatro níveis de contraste de Michelson: 2%, 5%, 10% e 100%. Nas duas condições cromáticas foi usado o nível mais alto de contraste agregado de cones permitidos pelo gamut do monitor, 17%. O experimento consistiu numa escolha forçada de dois intervalos, cujo procedimento de testagem compreendeu a seguinte seqüência: i) apresentação de um estímulo de referência por 1 s; ii) substituição do estímulo de referência por um fundo eqüiluminante de mesma cromaticidade por 1 s; iii) apresentação do estímulo de teste também por 1 s, diferindo em relação ao estímulo de referência seja em freqüência espacial, seja em extensão espacial, com um estímulo sonoro sinalizando ao sujeito que era necessário responder se o estímulo de teste era igual ou diferente do estímulo de referência; iv) substituição do estímulo de teste pelo fundo. A extensão espacial ou a freqüência espacial do estímulo de teste foi mudada aleatoriamente de tentativa para tentativa usando o método dos estímulos constantes. Numa série de 300 tentativas, a freqüencia espacial foi variada, noutra série também de 300 tentativas, a extensão espacial foi variada, sendo que cada estímulo de teste em cada série foi apresentado pelo menos 10 vezes. A resposta do indivíduo em cada tentativa era guardada como correta ou errada para posterior construção das curvas psicométricas. Os pontos experimentais das funções psicométricas para espaço e freqüência espacial em cada nível de contraste, correspondentes aos percentuais de acertos, foram ajustados com funções gaussianas usando-se o método dos mínimos quadrados. Para cada nível de contraste, as entropias para espaço e freqüência espacial foram estimadas pelos desvios padrões dessas funções gaussianas e a entropia conjunta foi obtida multiplicando-se a raiz quadrada da entropia para espaço pela entropia para freqüência espacial. Os valores de entropia conjunta foram comparados com o mínimo teórico para sistemas lineares, 1/4π ou 0,0796. Para freqüências espaciais baixas e intermediárias, a entropia conjunta atingiu níveis abaixo do mínimo teórico em contrastes altos, sugerindo interações não lineares entre dois ou mais mecanismos visuais. Este fenômeno occorreu em todas as condições (acromática, cromática e cromática eqüiluminante) e foi mais acentuado para a frequência espacial de 0,4 ciclos / grau. Uma possível explicação para este fenômeno é a interação não linear entre as vias visuais retino-genículo-estriadas, tais como as vias K, M e P, na área visual primária ou em níveis mais altos de processamento neural.

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

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The education designed and planned in a clear and objective manner is of paramount importance for universities to prepare competent professionals for the labor market, and above all can serve the population with an efficient work. Specifically, in relation to engineering, conducting classes in the laboratories it is very important for the application of theory and development of the practical part of the student. The planning and preparation of laboratories, as well as laboratory equipment and activities should be developed in a succinct and clear way, showing to students how to apply in practice what has been learned in theory and often shows them why and where it can be used when they become engineers. This work uses the MATLAB together with the System Identification Toolbox and Arduino for the identification of linear systems in Linear Control Lab. MATLAB is a widely used program in the engineering area for numerical computation, signal processing, graphing, system identification, among other functions. Thus the introduction to MATLAB and consequently the identification of systems using the System Identification Toolbox becomes relevant in the formation of students to thereafter when necessary to identify a system the base and the concept has been seen. For this procedure the open source platform Arduino was used as a data acquisition board being the same also introduced to the student, offering them a range of software and hardware for learning, giving you every day more luggage to their training