14 resultados para Sistemas dinâmico diferenciais
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
This work aims presenting the development of a model and computer simulation of a sucker rod pumping system. This system take into account the well geometry, the flow through the tubing, the dynamic behavior of the rod string and the use of a induction motor model. The rod string were modeled using concentrated parameters, allowing the use of ordinary differential equations systems to simulate it s behavior
Resumo:
We propose a new paradigm for collective learning in multi-agent systems (MAS) as a solution to the problem in which several agents acting over the same environment must learn how to perform tasks, simultaneously, based on feedbacks given by each one of the other agents. We introduce the proposed paradigm in the form of a reinforcement learning algorithm, nominating it as reinforcement learning with influence values. While learning by rewards, each agent evaluates the relation between the current state and/or action executed at this state (actual believe) together with the reward obtained after all agents that are interacting perform their actions. The reward is a result of the interference of others. The agent considers the opinions of all its colleagues in order to attempt to change the values of its states and/or actions. The idea is that the system, as a whole, must reach an equilibrium, where all agents get satisfied with the obtained results. This means that the values of the state/actions pairs match the reward obtained by each agent. This dynamical way of setting the values for states and/or actions makes this new reinforcement learning paradigm the first to include, naturally, the fact that the presence of other agents in the environment turns it a dynamical model. As a direct result, we implicitly include the internal state, the actions and the rewards obtained by all the other agents in the internal state of each agent. This makes our proposal the first complete solution to the conceptual problem that rises when applying reinforcement learning in multi-agent systems, which is caused by the difference existent between the environment and agent models. With basis on the proposed model, we create the IVQ-learning algorithm that is exhaustive tested in repetitive games with two, three and four agents and in stochastic games that need cooperation and in games that need collaboration. This algorithm shows to be a good option for obtaining solutions that guarantee convergence to the Nash optimum equilibrium in cooperative problems. Experiments performed clear shows that the proposed paradigm is theoretical and experimentally superior to the traditional approaches. Yet, with the creation of this new paradigm the set of reinforcement learning applications in MAS grows up. That is, besides the possibility of applying the algorithm in traditional learning problems in MAS, as for example coordination of tasks in multi-robot systems, it is possible to apply reinforcement learning in problems that are essentially collaborative
Resumo:
This work presents a theoretical, numerical and computation analysis of parameters of a rectangular microstrip antenna with metamaterial substrate, fin line as a coupler and also integrated devices like integrated filter antenna. It is applied theory to full-wave of Transverse Transmission Line - TTL method, to characterize the magnitude of the substrate and obtain the general equations of the electromagnetic fields. About the metamaterial, they are characterized by permittivity and permeability tensor, reaching to the general equations for the electromagnetic fields of the antenna. It is presented a study about main representation of PBG(Photonic Band Gap) material and its applied for a specific configuration. A few parameters are simulated some structures in order to reduce the physical dimensions and increase the bandwidth. The results are presented through graphs. The theoretical and computational analysis of this work have shown accurate and relatively concise. Conclusions are drawn and suggestions for future work
Resumo:
Equipment maintenance is the major cost factor in industrial plants, it is very important the development of fault predict techniques. Three-phase induction motors are key electrical equipments used in industrial applications mainly because presents low cost and large robustness, however, it isn t protected from other fault types such as shorted winding and broken bars. Several acquisition ways, processing and signal analysis are applied to improve its diagnosis. More efficient techniques use current sensors and its signature analysis. In this dissertation, starting of these sensors, it is to make signal analysis through Park s vector that provides a good visualization capability. Faults data acquisition is an arduous task; in this way, it is developed a methodology for data base construction. Park s transformer is applied into stationary reference for machine modeling of the machine s differential equations solution. Faults detection needs a detailed analysis of variables and its influences that becomes the diagnosis more complex. The tasks of pattern recognition allow that systems are automatically generated, based in patterns and data concepts, in the majority cases undetectable for specialists, helping decision tasks. Classifiers algorithms with diverse learning paradigms: k-Neighborhood, Neural Networks, Decision Trees and Naïves Bayes are used to patterns recognition of machines faults. Multi-classifier systems are used to improve classification errors. It inspected the algorithms homogeneous: Bagging and Boosting and heterogeneous: Vote, Stacking and Stacking C. Results present the effectiveness of constructed model to faults modeling, such as the possibility of using multi-classifiers algorithm on faults classification
Resumo:
Several mobile robots show non-linear behavior, mainly due friction phenomena between the mechanical parts of the robot or between the robot and the ground. Linear models are efficient in some cases, but it is necessary take the robot non-linearity in consideration when precise displacement and positioning are desired. In this work a parametric model identification procedure for a mobile robot with differential drive that considers the dead-zone in the robot actuators is proposed. The method consists in dividing the system into Hammerstein systems and then uses the key-term separation principle to present the input-output relations which shows the parameters from both linear and non-linear blocks. The parameters are then simultaneously estimated through a recursive least squares algorithm. The results shows that is possible to identify the dead-zone thresholds together with the linear parameters
Resumo:
This work addresses the dynamic control problem of two-wheeled differentially driven non-holonomic mobile robot. Strategies for robot positioning control and robot orientating control are presented. Such strategies just require information about the robot con¯guration (x, y and teta), which can be collected by an absolute positioning system. The strategies development is related to a change on the controlled variables for such systems, from x, y and teta to s (denoting the robot linear displacement) and teta, and makes use of the polar coordinates representation for the robot kinematic model. Thus, it is possible to obtain a linear representation for the mobile robot dynamic model and to develop such strategies. It is also presented that such strategies allow the use of linear controllers to solve the control problem. It is shown that there is flexibility to choice the linear controller (P, PI, PID, Model Matching techniques, others) to be implemented. This work presents an introduction to mobile robotics and their characteristics followed by the control strategies development and controllers design. Finally, simulated and experimental results are presented and commented
Resumo:
This work presents a modelling and identification method for a wheeled mobile robot, including the actuator dynamics. Instead of the classic modelling approach, where the robot position coordinates (x,y) are utilized as state variables (resulting in a non linear model), the proposed discrete model is based on the travelled distance increment Delta_l. Thus, the resulting model is linear and time invariant and it can be identified through classical methods such as Recursive Least Mean Squares. This approach has a problem: Delta_l can not be directly measured. In this paper, this problem is solved using an estimate of Delta_l based on a second order polynomial approximation. Experimental data were colected and the proposed method was used to identify the model of a real robot
Resumo:
Nowadays there has been a major breakthrough in the aerospace area, with regard to rocket launches to research, experiments, telemetry system, remote sensing, radar system (tracking and monitoring), satellite communications system and insertion of satellites in orbit. This work aims at the application of a circular cylindrical microstrip antenna, ring type, and other cylindrical rectangular in structure of a rocket or missile to obtain telemetry data, operating in the range of 2 to 4 GHz, in S-band. Throughout this was developed just the theoretical analysis of the Transverse transmission line method which is a method of rigorous analysis in spectral domain, for use in rockets and missiles. This analyzes the spread in the direction "ρ" , transverse to dielectric interfaces "z" and "φ", for cylindrical coordinates, thus taking the general equations of electromagnetic fields in function of e [1]. It is worth mentioning that in order to obtain results, simulations and analysis of the structure under study was used HFSS program (High Frequency Structural Simulator) that uses the finite element method. With the theory developed computational resources were used to obtain the numerical calculations, using Fortran Power Station, Scilab and Wolfram Mathematica ®. The prototype was built using, as a substrate, the ULTRALAM ® 3850, of Rogers Corporation, and an aluminum plate as a cylindrical structure used to support. The agreement between the measured and simulated results validate the established processes. Conclusions and suggestions are presented for continuing this work
Resumo:
The growing utilization of surfactants in several different areas of industry has led to an increase on the studies involving solutions containing this type of molecules. Due to its amphiphilic nature, its molecule presents one polar part and one nonpolar end, which easily interacts with other molecules, being able to modify the media properties. When the concentration in which its monomers are saturated, the airliquid system interface is reached, causing a decrease in interfacial tension. The surfactants from pure fatty acids containing C8, C12 and C16 carbonic chains were synthesized in an alcoholic media using sodium hydroxide. They were characterized via thermal analysis (DTA and DTG) and via infrared spectroscopy, with the intention of observing their purity. Physical and chemical properties such as superficial tension, critical micelle concentration (c.m.c), surfactant excess on surface and Gibbs free energy of micellization were determined in order to understand the behaviour of these molecules with an aqueous media. Pseudo-ternary phase diagrams were obtained aiming to limit the Windsor equilibria conditions so it could be possible to understand how the surfactants carbonic chain size contributes to the microemulsion region. Solutions with known concentrations were prepared to study how the surfactants can influence the dynamic light scattering spectroscopy (DLS) and how the diffusion coefficient is influenced when the media concentration is altered. The results showed the variation on the chain size of the studied surfactant lipophilic part allows the conception of surfactants with similar interfacial properties, but dependent on the size of the lipophilic part of the surfactant. This variation causes the surfactant to have less tendency of microemulsionate oil in water. Another observed result is that the n-alcanes molecule size promoted a decrease on the microemulsion region on the obtained phase diagrams
Resumo:
In this work we investigate the stochastic behavior of a large class of systems with variable damping which are described by a time-dependent Lagrangian. Our stochastic approach is based on the Langevin treatment describing the motion of a classical Brownian particle of mass m. Two situations of physical interest are considered. In the first one, we discuss in detail an application of the standard Langevin treatment (white noise) for the variable damping system. In the second one, a more general viewpoint is adopted by assuming a given expression to the so-called collored noise. For both cases, the basic diffententiaql equations are analytically solved and al the quantities physically relevant are explicitly determined. The results depend on an arbitrary q parameter measuring how the behavior of the system departs from the standard brownian particle with constant viscosity. Several types of sthocastic behavior (superdiffusive and subdiffusive) are obteinded when the free pamameter varies continuosly. However, all the results of the conventional Langevin approach with constant damping are recovered in the limit q = 1
Resumo:
Sustainable development is a major challenge in the oil industry and has aroused growing interest in research to obtain materials from renewable sources. Carboxymethylcellulose (CMC) is a polysaccharide derived from cellulose and becomes attractive because it is water-soluble, renewable, biodegradable and inexpensive, as well as may be chemically modified to gain new properties. Among the derivatives of carboxymethylcellulose, systems have been developed to induce stimuli-responsive properties and extend the applicability of multiple-responsive materials. Although these new materials have been the subject of study, understanding of their physicochemical properties, such as viscosity, solubility and particle size as a function of pH and temperature, is still very limited. This study describes systems of physical blends and copolymers based on carboxymethylcellulose and poly (N-isopropylacrylamide) (PNIPAM), with different feed percentage compositions of the reaction (25CMC, 50CMC e 75CMC), in aqueous solution. The chemical structure of the polymers was investigated by infrared and CHN elementary analysis. The physical blends were analyzed by rheology and the copolymers by UV-visible spectroscopy, small-angle X-ray scattering (SAXS), dynamic light scattering (DLS) and zeta potential. CMC and copolymer were assessed as scale inhibitors of calcium carbonate (CaCO3) using dynamic tube blocking tests and chemical compatibility tests, as well as scanning electron microscopy (SEM). Thermothickening behavior was observed for the 50 % CMC_50 % PNIPAM and 25 % CMC_75 % PNIPAM physical blends in aqueous solution at concentrations of 6 and 2 g/L, respectively, depending on polymer concentration and composition. For the copolymers, the increase in temperature and amount of PNIPAM favored polymer-polymer interactions through hydrophobic groups, resulting in increased turbidity of polymer solutions. Particle size decreased with the rise in copolymer PNIPAM content as a function of pH (3-12), at 25 °C. Larger amounts of CMC result in a stronger effect of pH on particle size, indicating pH-responsive behavior. Thus, 25CMC was not affected by the change in pH, exhibiting similar behavior to PNIPAM. In addition, the presence of acidic or basic additives influenced particle size, which was smaller in the presence of the additives than in distilled water. The results of zeta potential also showed greater variation for polymers in distilled water than in the presence of acids and bases. The lower critical solution temperature (LCST) of PNIPAM determined by DLS corroborated the value obtained by UV-visible spectroscopy. SAXS data for PNIPAM and 50CMC indicated phase transition when the temperature increased from 32 to 34 °C. A reduction in or absence of electrostatic properties was observed as a function of increased PNIPAM in copolymer composition. Assessment of samples as scale inhibitors showed that CMC performed better than the copolymers. This was attributed to the higher charge density present in CMC. The SEM micrographs confirmed morphological changes in the CaCO3 crystals, demonstrating the scale inhibiting potential of these polymers
Resumo:
Due to the constantly increasing use of wireless networks in domestic, business and industrial environments, new challenges have emerged. The prototyping of new protocols in these environments is typically restricted to simulation environments, where there is the need of double implementation, one in the simulation environment where an initial proof of concept is performed and the other one in a real environment. Also, if real environments are used, it is not trivial to create a testbed for high density wireless networks given the need to use various real equipment as well as attenuators and power reducers to try to reduce the physical space required to create these laboratories. In this context, LVWNet (Linux Virtual Wireless Network) project was originally designed to create completely virtual testbeds for IEEE 802.11 networks on the Linux operating system. This paper aims to extend the current project LVWNet, adding to it the features like the ability to interact with real wireless hardware, provides a initial mobility ability using the positioning of the nodes in a space coordinates environment based on meters, with loss calculations due to attenuation in free space, enables some scalability increase by creating an own protocol that allows the communication between nodes without an intermediate host and dynamic registration of nodes, allowing new nodes to be inserted into in already in operation network
Resumo:
The great interest in nonlinear system identification is mainly due to the fact that a large amount of real systems are complex and need to have their nonlinearities considered so that their models can be successfully used in applications of control, prediction, inference, among others. This work evaluates the application of Fuzzy Wavelet Neural Networks (FWNN) to identify nonlinear dynamical systems subjected to noise and outliers. Generally, these elements cause negative effects on the identification procedure, resulting in erroneous interpretations regarding the dynamical behavior of the system. The FWNN combines in a single structure the ability to deal with uncertainties of fuzzy logic, the multiresolution characteristics of wavelet theory and learning and generalization abilities of the artificial neural networks. Usually, the learning procedure of these neural networks is realized by a gradient based method, which uses the mean squared error as its cost function. This work proposes the replacement of this traditional function by an Information Theoretic Learning similarity measure, called correntropy. With the use of this similarity measure, higher order statistics can be considered during the FWNN training process. For this reason, this measure is more suitable for non-Gaussian error distributions and makes the training less sensitive to the presence of outliers. In order to evaluate this replacement, FWNN models are obtained in two identification case studies: a real nonlinear system, consisting of a multisection tank, and a simulated system based on a model of the human knee joint. The results demonstrate that the application of correntropy as the error backpropagation algorithm cost function makes the identification procedure using FWNN models more robust to outliers. However, this is only achieved if the gaussian kernel width of correntropy is properly adjusted.
Resumo:
This work aims presenting the development of a model and computer simulation of a sucker rod pumping system. This system take into account the well geometry, the flow through the tubing, the dynamic behavior of the rod string and the use of a induction motor model. The rod string were modeled using concentrated parameters, allowing the use of ordinary differential equations systems to simulate it s behavior