13 resultados para Non-Linear Dynamic System

em Universidade Federal do Rio Grande do Norte(UFRN)


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The present work presents the study and implementation of an adaptive bilinear compensated generalized predictive controller. This work uses conventional techniques of predictive control and includes techniques of adaptive control for better results. In order to solve control problems frequently found in the chemical industry, bilinear models are considered to represent the dynamics of the studied systems. Bilinear models are simpler than general nonlinear model, however it can to represent the intrinsic not-linearities of industrial processes. The linearization of the model, by the approach to time step quasilinear , is used to allow the application of the equations of the generalized predictive controller (GPC). Such linearization, however, generates an error of prediction, which is minimized through a compensation term. The term in study is implemented in an adaptive form, due to the nonlinear relationship between the input signal and the prediction error.Simulation results show the efficiency of adaptive predictive bilinear controller in comparison with the conventional.

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Slugging is a well-known slugging phenomenon in multiphase flow, which may cause problems such as vibration in pipeline and high liquid level in the separator. It can be classified according to the place of its occurrence. The most severe, known as slugging in the riser, occurs in the vertical pipe which feeds the platform. Also known as severe slugging, it is capable of causing severe pressure fluctuations in the flow of the process, excessive vibration, flooding in separator tanks, limited production, nonscheduled stop of production, among other negative aspects that motivated the production of this work . A feasible solution to deal with this problem would be to design an effective method for the removal or reduction of the system, a controller. According to the literature, a conventional PID controller did not produce good results due to the high degree of nonlinearity of the process, fueling the development of advanced control techniques. Among these, the model predictive controller (MPC), where the control action results from the solution of an optimization problem, it is robust, can incorporate physical and /or security constraints. The objective of this work is to apply a non-conventional non-linear model predictive control technique to severe slugging, where the amount of liquid mass in the riser is controlled by the production valve and, indirectly, the oscillation of flow and pressure is suppressed, while looking for environmental and economic benefits. The proposed strategy is based on the use of the model linear approximations and repeatedly solving of a quadratic optimization problem, providing solutions that improve at each iteration. In the event where the convergence of this algorithm is satisfied, the predicted values of the process variables are the same as to those obtained by the original nonlinear model, ensuring that the constraints are satisfied for them along the prediction horizon. A mathematical model recently published in the literature, capable of representing characteristics of severe slugging in a real oil well, is used both for simulation and for the project of the proposed controller, whose performance is compared to a linear MPC

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The Federal Institution for Education, Science and Technology, in its historical path, has been living different changes. The transformations occurred along the way have been determined by coercive forces from the institutional environment, which has became more and more broad and complex throughout the time, obtaining diverse characteristics and new elements such as non institutional factors1 which started to contribute with the other changes. In this context, this work aims to study the isomorphic practices of the managers in the institutional changes process of the IFRN in 1998 and 2008, as of a theoretical coevolutionary perspective (CHILD; RODRIGUES; LEWIN; CARROL; VOLBERDA, 2003). This theory brings a new point of view for the organization analysis to the organizational studies, since it offers a non deterministic and non linear lection of the evolution process, which means, a coevolution. Thus, the organizations and their institutional and non institutional environment auto evolve, auto organize and auto reproduce. Therefore, the institutional and non institutional factors of the macro environment keep a continuous interdependence relationship with the organizations. For the means of this study, it is important to understand that is impossible to comprehend the object, the isomorphic practices, without considering that the previous institutional changes and its evolutions, its continuations and discontinuations, important in the coevolution process. As such, to call upon the institutional historical track is a fundamental aspect to materialize this study, for the recursive movement is indeed present in the coevolution. Another important point to make this research effective is that it is not possible to abdicate from the hologramatic view2 of this study, which considers the object, the isomorphic practices, part of the whole and this whole is also in the parts, therefore it is impossible to comprehend the object of study outside the context where it belongs. With this, as of the objective previously proposed, it is necessary to describe the characteristics of coevolution of the institutional changes related in 1998 and 2008; analyze the dynamic of the isomorphic mechanisms in its respective institutional change process; and describe the lessons learned which the isomorphic practices left to the IFRN, regarding its benefits and difficulties. All these transformations happened through coercive forces3 of the institutional environment. As of the Nineties, these forces became stronger, the environment became broader and more complex, with the emergency of new environmental factors. This study proposed to study the managing process and its practices, related to the micro environment, although it is required to articulate these actions, the demands and requirements from the macro environment. To make this research effective, semi structured interviews have been conducted with the managers who participated in both institutional change processes. In the results analysis, it has been possible to verify the particularity of each change, the one from 1998 with a strong normative action of the managers against coercive forces from the government for the search of recognition and the institutional legitimation and the one in 2008, which has been characterized by the normative action by managers in agreement with the coercive forces from the government, in favor of the government policy for the technological professional education. However, the results analysis it is possible to notice the evidence of a belonging feeling from the interviewed managers

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The present work is based on the applied bilinear predictive control applied to an induction motor. As in particular case of the technique based on predictive control in nonlinem systems, these have desperted great interest, a time that present the advantage of being simpler than the non linear in general and most representative one than the linear one. One of the methods, adopted here, uses the linear model "quasi linear for step of time" based in Generalized Predictive Control. The modeling of the induction motor is made by the Vectorial control with orientation given for the indirect rotor. The system is formed by an induction motor of 3 cv with rotor in squirregate, set in motion for a group of benches of tests developed for this work, presented resulted for a variation of +5% in the value of set-point and for a variation of +10% and -10% in the value of the applied nominal load to the motor. The results prove a good efficiency of the predictive bilinear controllers, then compared with the linear cases

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This work presents a diagnosis faults system (rotor, stator, and contamination) of three-phase induction motor through equivalent circuit parameters and using techniques patterns recognition. The technology fault diagnostics in engines are evolving and becoming increasingly important in the field of electrical machinery. The neural networks have the ability to classify non-linear relationships between signals through the patterns identification of signals related. It is carried out induction motor´s simulations through the program Matlab R & Simulink R , and produced some faults from modifications in the equivalent circuit parameters. A system is implemented with multiples classifying neural network two neural networks to receive these results and, after well-trained, to accomplish the identification of fault´s pattern

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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

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A hierarchical fuzzy control scheme is applied to improve vibration suppression by using an electro-mechanical system based on the lever principle. The hierarchical intelligent controller consists of a hierarchical fuzzy supervisor, one fuzzy controller and one robust controller. The supervisor combines controllers output signal to generate the control signal that will be applied on the plant. The objective is to improve the performance of the electromechanical system, considering that the supervisor could take advantage of the different techniques based controllers. The robust controller design is based on a linear mathematical model. Genetic algorithms are used on the fuzzy controller and the supervisor tuning, which are based on non-linear mathematical model. In order to attest the efficiency of the hierarchical fuzzy control scheme, digital simulations were employed. Some comparisons involving the optimized hierarchical controller and the non-optimized hierarchical controller will be made to prove the efficiency of the genetic algorithms and the advantages of its use

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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

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Composites based on PEEK + PTFE + CARBON FIBER + Graphite (G_CFRP) has increased application in the top industries, as Aerospace, Aeronautical, Petroleum, Biomedical, Mechanical and Electronics Engineering challenges. A commercially available G_CFRP was warmed up to three different levels of thermal energy to identify the main damage mechanisms and some evidences for their intrinsic transitions. An experimental test rig for systematize a heat flux was developed in this dissertation, based on the Joule Effect. It was built using an isothermal container, an internal heat source and a real-time measurement system for test a sample by time. A standard conical-cylindrical tip was inserted into a soldering iron, commercially available and identified by three different levels of nominal electrical power, 40W (manufacturer A), 40W (manufacturer B), 100W and 150W, selected after screening tests: these power levels for the heat source, after one hour of heating and one hour of cooling in situ, carried out three different zones of degradation in the composite surface. The bench was instrumented with twelve thermocouples, a wattmeter and a video camera. The twelve specimens tested suffered different degradation mechanisms, analyzed by DSC (Differential Scanning Calorimetry) and TG (Thermogravimetry) techniques, Scanning Electron Microscopy (SEM) and Energy-Dispersive X-Rays (EDX) Analysis. Before and after each testing, it was measured the hardness of the sample by HRM (Hardness Rockwell M). Excellent correlations (R2=1) were obtained in the plots of the evaporated area after one hour of heating and one hour of cooling in situ versus (1) the respective power of heat source and (2) the central temperature of the sample. However, as resulting of the differential degradation of G_CFRP and their anisotropy, confirmed by their variable thermal properties, viscoelastic and plastic properties, there were both linear and non-linear behaviour between the temperature field and Rockwell M hardness measured in the radial and circumferential directions of the samples. Some morphological features of the damaged zones are presented and discussed, as, for example, the crazing and skeletonization mechanism of G_CFRP

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The development of non-linear controllers gained space in the theoretical ambit and of practical applications on the moment that the arising of digital computers enabled the implementation of these methodologies. In comparison with the linear controllers more utilized, the non -linear controllers present the advantage of not requiring the linearity of the system to determine the parameters of control, which permits a more efficient control especially when the system presents a high level of non-linearity. Another additional advantage is the reduction of costs, since to obtain the efficient control through linear controllers it is necessary the utilization of sensors and more refined actuators than when it is utilized a non-linear controller. Among the non-linear theories of control, the method of control by gliding ways is detached for being a method that presents more robustness, before uncertainties. It is already confirmed that the adoption of compensation on the region of residual error permits to improve better the performance of these controllers. So, in this work it is described the development of a non-linear controller that looks for an association of strategy of control by gliding ways, with the fuzzy compensation technique. Through the implementation of some strategies of fuzzy compensation, it was searched the one which provided the biggest efficiency before a system with high level of nonlinearities and uncertainties. The electrohydraulic actuator was utilized as an example of research, and the results appoint to two configurations of compensation that permit a bigger reduction of the residual error

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This dissertation aims the development of an experimental device to determine quantitatively the content of benzene, toluene and xylenes (BTX) in the atmosphere. BTX are extremely volatile solvents, and therefore play an important role in atmospheric chemistry, being precursors in the tropospheric ozone formation. In this work a BTX new standard gas was produced in nitrogen for stagnant systems. The aim of this dissertation is to develop a new method, simple and cheaper, to quantify and monitor BTX in air using solid phase microextraction/ gas chromatography/mass spectrometry (SPME/CG/MS). The features of the calibration method proposed are presented in this dissertation. SPME sampling was carried out under non-equilibrium conditions using a Carboxen/PDMS fiber exposed for 10 min standard gas mixtures. It is observed that the main parameters that affect the extraction process are sampling time and concentration. The results of the BTX multicomponent system studied have shown a linear and a nonlinear range. In the non-linear range, it is remarkable the effect of competition by selective adsorption with the following affinity order p-xylene > toluene > benzene. This behavior represents a limitation of the method, however being in accordance with the literature. Furthermore, this behavior does not prevent the application of the technique out of the non-linear region to quantify the BTX contents in the atmosphere.

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The ferromagnetic and antiferromagnetic Ising model on a two dimensional inhomogeneous lattice characterized by two exchange constants (J1 and J2) is investigated. The lattice allows, in a continuous manner, the interpolation between the uniforme square (J2 = 0) and triangular (J2 = J1) lattices. By performing Monte Carlo simulation using the sequential Metropolis algorithm, we calculate the magnetization and the magnetic susceptibility on lattices of differents sizes. Applying the finite size scaling method through a data colappse, we obtained the critical temperatures as well as the critical exponents of the model for several values of the parameter α = J2 J1 in the [0, 1] range. The ferromagnetic case shows a linear increasing behavior of the critical temperature Tc for increasing values of α. Inwhich concerns the antiferromagnetic system, we observe a linear (decreasing) behavior of Tc, only for small values of α; in the range [0.6, 1], where frustrations effects are more pronunciated, the critical temperature Tc decays more quickly, possibly in a non-linear way, to the limiting value Tc = 0, cor-responding to the homogeneous fully frustrated antiferromagnetic triangular case.

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This work an algorithm for fault location is proposed. It contains the following functions: fault detection, fault classification and fault location. Mathematical Morphology is used to process currents obtained in the monitored terminals. Unlike Fourier and Wavelet transforms that are usually applied to fault location, the Mathematical Morphology is a non-linear operation that uses only basic operation (sum, subtraction, maximum and minimum). Thus, Mathematical Morphology is computationally very efficient. For detection and classification functions, the Morphological Wavelet was used. On fault location module the Multiresolution Morphological Gradient was used to detect the traveling waves and their polarities. Hence, recorded the arrival in the two first traveling waves incident at the measured terminal and knowing the velocity of propagation, pinpoint the fault location can be estimated. The algorithm was applied in a 440 kV power transmission system, simulated on ATP. Several fault conditions where studied and the following parameters were evaluated: fault location, fault type, fault resistance, fault inception angle, noise level and sampling rate. The results show that the application of Mathematical Morphology in faults location is very promising