7 resultados para Sequential machine theory.

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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In our experiments, we studied the classical dynamic of a particle in vertical motion subject to a constant gravitational field and the partial shock with an elastic wall with oscillatory motion located below the particle. The motion of the particle was confined to the vertical direction by a glass guide tube, which was initially evacuated, allowing viscous drag forces to be disregarded. The time between impacts, as well as the time between the reference phase of the movement of the base and the moment of impact and the period of oscillation of the base will be acquired by a hardware and software to obtain the phases space to be compared later with the description of the system through mapping discrete variables via the 'particle velocity immediately after shock 'and' phase of the movement of the base at the instant of shock 'obtained by computer simulation. This requires developing an electronic analog system followed by Digital implemented in reconfigurable logic, more specifically a sequential machine able to discriminate the impact with the metal base from the impacts of the glass guide tube, based on the frequency spectrum of the response of the microphone to these different impacts

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This work presents a methodology to analyze electric power systems transient stability for first swing using a neural network based on adaptive resonance theory (ART) architecture, called Euclidean ARTMAP neural network. The ART architectures present plasticity and stability characteristics, which are very important for the training and to execute the analysis in a fast way. The Euclidean ARTMAP version provides more accurate and faster solutions, when compared to the fuzzy ARTMAP configuration. Three steps are necessary for the network working, training, analysis and continuous training. The training step requires much effort (processing) while the analysis is effectuated almost without computational effort. The proposed network allows approaching several topologies of the electric system at the same time; therefore it is an alternative for real time transient stability of electric power systems. To illustrate the proposed neural network an application is presented for a multi-machine electric power systems composed of 10 synchronous machines, 45 buses and 73 transmission lines. (C) 2010 Elsevier B.V. All rights reserved.

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This work will propose the control of an induction machine in field coordinates with imposed stator current based on theory of variable structure control and sliding mode. We describe the model of an induction machine in field coordinates with imposed stator current and we show the design of variable structure control and sliding mode to get a desirable dynamic performance of that plant. To estimate the inaccessible states we will use a state observer (estimator) based on field coordinates induction machine. We will present the results of simulations in any operation condition (start, speed reversal and load) and with parameters variation of the machine compared to a PI control scheme.

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The aim of this work is to propose a simple and efficient mechanism to deal with the problem of executing sequential code in a pure dataflow machine. Our results is obtained with a simulator of Wolf [4] architecture. The implemented mechanism improved the architecture performance when executing sequential code and we expect that this improvement could be better if we use some heuristics to deal with some special groups of instructions such as branch operations. Further research will show us if this is true.

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The behaviors of an arc-shaped stator induction machine (the sector-motor) and a disc-secondary linear induction motor are analyzed in this work for different values of the frequency. Variable frequency is produced by a voltage source controlled-current inverter which keeps constant the r.m.s. value of the phase current, also assuring a sinusoidal waveform. For the simulations of the machine developed thrust, an equivalent circuit is used. It is obtained through the application of the one-dimensional theory to the modeling. The circuit parameters take into account the end effects, always present is these kind of machines. The phase current waveforms are analyzed for their harmonic contents. Experimental measurements were carried out in laboratory and are presented with the simulations, for comparison.

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This work shows a computational methodology for the determination of synchronous machines parameters using load rejection test data. By machine modeling one can obtain the quadrature parameters through a load rejection under an arbitrary reference, reducing the present difficulties. The proposed method is applied to a real machine.

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This article describes the use of Artificial Intelligence (IA) techniques applied in cells of a manufacturing system. Machine Vision was used to identify pieces and their positions of two different products to be assembled in the same productive line. This information is given as input for an IA planner embedded in the manufacturing system. Therefore, initial and final states are sent automatically to the planner capable to generate assembly plans for a robotic cell, in real time.