946 resultados para Discrete dynamical systems
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Due of industrial informatics several attempts have been done to develop notations and semantics, which are used for classifying and describing different kind of system behavior, particularly in the modeling phase. Such attempts provide the infrastructure to resolve some real problems of engineering and construct practical systems that aim at, mainly, to increase the productivity, quality, and security of the process. Despite the many studies that have attempted to develop friendly methods for industrial controller programming, they are still programmed by conventional trial-and-error methods and, in practice, there is little written documentation on these systems. The ideal solution would be to use a computational environment that allows industrial engineers to implement the system using high-level language and that follows international standards. Accordingly, this work proposes a methodology for plant and control modelling of the discrete event systems that include sequential, parallel and timed operations, using a formalism based on Statecharts, denominated Basic Statechart (BSC). The methodology also permits automatic procedures to validate and implement these systems. To validate our methodology, we presented two case studies with typical examples of the manufacturing sector. The first example shows a sequential control for a tagged machine, which is used to illustrated dependences between the devices of the plant. In the second example, we discuss more than one strategy for controlling a manufacturing cell. The model with no control has 72 states (distinct configurations) and, the model with sequential control generated 20 different states, but they only act in 8 distinct configurations. The model with parallel control generated 210 different states, but these 210 configurations act only in 26 distinct configurations, therefore, one strategy control less restrictive than previous. Lastly, we presented one example for highlight the modular characteristic of our methodology, which it is very important to maintenance of applications. In this example, the sensors for identifying pieces in the plant were removed. So, changes in the control model are needed to transmit the information of the input buffer sensor to the others positions of the cell
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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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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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Relaxed conditions for stability of nonlinear, continuous and discrete-time systems given by fuzzy models are presented. A theoretical analysis shows that the proposed methods provide better or at least the same results of the methods presented in the literature. Numerical results exemplify this fact. These results are also used for fuzzy regulators and observers designs. The nonlinear systems are represented by fuzzy models proposed by Takagi and Sugeno. The stability analysis and the design of controllers are described by linear matrix inequalities, that can be solved efficiently using convex programming techniques. The specification of the decay rate, constrains on control input and output are also discussed.
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Difusive processes are extremely common in Nature. Many complex systems, such as microbial colonies, colloidal aggregates, difusion of fluids, and migration of populations, involve a large number of similar units that form fractal structures. A new model of difusive agregation was proposed recently by Filoche and Sapoval [68]. Based on their work, we develop a model called Difusion with Aggregation and Spontaneous Reorganization . This model consists of a set of particles with excluded volume interactions, which perform random walks on a square lattice. Initially, the lattice is occupied with a density p = N/L2 of particles occupying distinct, randomly chosen positions. One of the particles is selected at random as the active particle. This particle executes a random walk until it visits a site occupied by another particle, j. When this happens, the active particle is rejected back to its previous position (neighboring particle j), and a new active particle is selected at random from the set of N particles. Following an initial transient, the system attains a stationary regime. In this work we study the stationary regime, focusing on scaling properties of the particle distribution, as characterized by the pair correlation function ø(r). The latter is calculated by averaging over a long sequence of configurations generated in the stationary regime, using systems of size 50, 75, 100, 150, . . . , 700. The pair correlation function exhibits distinct behaviors in three diferent density ranges, which we term subcritical, critical, and supercritical. We show that in the subcritical regime, the particle distribution is characterized by a fractal dimension. We also analyze the decay of temporal correlations
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The minority game (MG) model introduced recently provides promising insights into the understanding of the evolution of prices, indices and rates in the financial markets. In this paper we perform a time series analysis of the model employing tools from statistics, dynamical systems theory and stochastic processes. Using benchmark systems and a financial index for comparison, several conclusions are obtained about the generating mechanism for this kind of evolution. The motion is deterministic, driven by occasional random external perturbation. When the interval between two successive perturbations is sufficiently large, one can find low dimensional chaos in this regime. However, the full motion of the MG model is found to be similar to that of the first differences of the SP500 index: stochastic, nonlinear and (unit root) stationary. (C) 2002 Elsevier B.V. B.V. All rights reserved.
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In this study we simulate numerically the Reynolds' experiment for the transition from laminar to turbulent flow in a pipe. We present a discussion of the results from a dynamical systems perspective when a control parameter, the Reynolds number, is increased. The Landau scenario, where the transition is described by the excitation of infinite oscillatory modes within the fluid, is not observed. Instead what happens is best explained by the Ruelle-Takens scenario in terms of strange attractors. The Lyapunov exponent and fractal dimension for the attractor are calculated together with a measure of complex behaviour called the Lempel-Ziv complexity. (C) 2001 Elsevier B.V. B.V. All rights reserved.
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We investigate an alternative compactification of extra dimensions using local cosmic string in the Brans-Dicke gravity framework. In the context of dynamical systems it is possible to show that there exist a stable field configuration for the Einstein-Brans-Dicke equations. We explore the analogies between this particular model and the Randall-Sundrum scenario.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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We analyze the dynamical coupling between energy sources and structural response that must not be ignored in real engineering problems, since real motors have limited output power. We present models of certain problems that render descriptions that are closer to real situations encountered in practice.
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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)