483 resultados para Controlador MRAC


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The predictive control technique has gotten, on the last years, greater number of adepts in reason of the easiness of adjustment of its parameters, of the exceeding of its concepts for multi-input/multi-output (MIMO) systems, of nonlinear models of processes could be linearised around a operating point, so can clearly be used in the controller, and mainly, as being the only methodology that can take into consideration, during the project of the controller, the limitations of the control signals and output of the process. The time varying weighting generalized predictive control (TGPC), studied in this work, is one more an alternative to the several existing predictive controls, characterizing itself as an modification of the generalized predictive control (GPC), where it is used a reference model, calculated in accordance with parameters of project previously established by the designer, and the application of a new function criterion, that when minimized offers the best parameters to the controller. It is used technique of the genetic algorithms to minimize of the function criterion proposed and searches to demonstrate the robustness of the TGPC through the application of performance, stability and robustness criterions. To compare achieves results of the TGPC controller, the GCP and proportional, integral and derivative (PID) controllers are used, where whole the techniques applied to stable, unstable and of non-minimum phase plants. The simulated examples become fulfilled with the use of MATLAB tool. It is verified that, the alterations implemented in TGPC, allow the evidence of the efficiency of this algorithm

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Postsurgical complication of hypertension may occur in cardiac patients. To decrease the chances of complication it is necessary to reduce elevated blood pressure as soon as possible. Continuous infusion of vasodilator drugs, such as sodium nitroprusside (Nipride), would quickly lower the blood pressure in most patients. However, each patient has a different sensitivity to infusion of Nipride. The parameters and the time delays of the system are initially unknown. Moreover, the parameters of the transfer function associated with a particular patient are time varying. the objective of the study is to develop a procedure for blood pressure control i the presence of uncertainty of parameters and considerable time delays. So, a methodology was developed multi-model, and for each such model a Preditive Controller can be a priori designed. An adaptive mechanism is then needed for deciding which controller should be dominant for a given plant

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This work shows a study about the Generalized Predictive Controllers with Restrictions and their implementation in physical plants. Three types of restrictions will be discussed: restrictions in the variation rate of the signal control, restrictions in the amplitude of the signal control and restrictions in the amplitude of the Out signal (plant response). At the predictive control, the control law is obtained by the minimization of an objective function. To consider the restrictions, this minimization of the objective function is done by the use of a method to solve optimizing problems with restrictions. The chosen method was the Rosen Algorithm (based on the Gradient-projection). The physical plants in this study are two didactical systems of water level control. The first order one (a simple tank) and another of second order, which is formed by two tanks connected in cascade. The codes are implemented in C++ language and the communication with the system to be done through using a data acquisition panel offered by the system producer

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This work presents an analysis of the control law based on an indirect hybrid scheme using neural network, initially proposed for O. Adetona, S. Sathanathan and L. H. Keel. Implementations of this control law, for a level plant of second order, was resulted an oscillatory behavior, even if the neural identifier has converged. Such results had motivated the investigation of the applicability of that law. Starting from that, had been made stability mathematical analysis and several implementations, with simulated plants and with real plants, for analyze the problem. The analysis has been showed the law was designed being despised some components of dynamic of the plant to be controlled. Thus, for plants that these components have a significant influence in its dynamic, the law tends to fail

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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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In the last decade, the renewable energy sources have present a major propulsion in the world due to several factors: political, environmental, financial and others. Within this context, we have in particular the energy obtained through wind, wind energy - that has highlighted with rapid growth in recent years, including in Brazil, mostly in the Northeast, due to it s benefit-cost between the clean energies. In this context, we propose to compare the variable structure adaptive pole placement control (VS-APPC) with a traditional control technique proportional integral controller (PI), applied to set the control of machine side in a conversion system using a wind generator based on Double-Fed Induction Generator (DFIG). Robustness and performance tests were carried out to the uncertainties of the internal parameters of the machine and variations of speed reference.

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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 use of Field Programmable Gate Array (FPGA) for development of digital control strategies for power electronics applications has aroused a growing interest of many researchers. This interest is due to the great advantages offered by FPGA, which include: lower design effort, high performance and highly flexible prototyping. This work proposes the development and implementation of an unified one-cycle controller for boost CFP rectifier based on FPGA. This controller can be applied to a total of twelve converters, six inverters and six rectifiers defined by four single phase VSI topologies and three voltage modulation types. The topologies considered in this work are: full-bridge, interleaved full-bridge, half-bridge and interleaved half-bridge. While modulations are classified in bipolar voltage modulation (BVM), unipolar voltage modulation (UVM) and clamped voltage modulation (CVM). The proposed project is developed and prototyped using tools Matlab/Simulink® together with the DSP Builder library provided by Altera®. The proposed controller was validated with simulation and experimental results

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Neste trabalho, um controlador adaptativo backstepping a estrutura variável (Variable Structure Adaptive Backstepping Controller, VS-ABC) é apresentado para plantas monovariáveis, lineares e invariantes no tempo com grau relativo unitário. Ao invés das tradicionais leis integrais para estimação dos parâmetros da planta, leis chaveadas são utilizadas com o objetivo de aumentar a robustez em relação a incertezas paramétricas e distúrbios externos, bem como melhorar o desempenho transitório do sistema. Adicionalmente, o projeto do novo controlador é mais intuitivo quando comparado ao controlador backstepping original, uma vez que os relés introduzidos apresentam amplitudes diretamente relacionadas com os parâmetros nominais da planta. Esta nova abordagem, com uso de estrutura variável, também reduz a complexidade das implementações práticas, motivando a utilização de componentes industriais, tais como, FPGAs (Field Programmable Gate Arrays ), MCUs (Microcontrollers) e DSPs (Digital Signal Processors). Simulações preliminares para um sistema instável de primeira e segunda ordem são apresentadas de modo a corroborar os estudos. Um dos exemplos de Rohrs é ainda abordado através de simulações, para os dois cenários adaptativos: o controlador backstepping adaptativo original e o VS-ABC

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

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This research aims at developing a variable structure adaptive backstepping controller (VS-ABC) by using state observers for SISO (Single Input Single Output), linear and time invariant systems with relative degree one. Therefore, the lters were replaced by a Luenberger Adaptive Observer and the control algorithm uses switching laws. The presented simulations compare the controller performance, considering when the state variables are estimated by an observer, with the case that the variables are available for measurement. Even with numerous performance advantages, adaptive backstepping controllers still have very complex algorithms, especially when the system state variables are not measured, since the use of lters on the plant input and output is not something trivial. As an attempt to make the controller design more intuitive, an adaptive observer as an alternative to commonly used K lters can be used. Furthermore, since the states variables are considered known, the controller has a reduction on the dependence of the unknown plant parameters on the design. Also, switching laws could be used in the controller instead of the traditional integral adaptive laws because they improve the system transient performance and increase the robustness against external disturbances in the plant input

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With the technology progess, embedded systems using adaptive techniques are being used frequently. One of these techniques is the Variable Structure Model- Reference Adaptive Control (VS-MRAC). The implementation of this technique in embedded systems, requires consideration of a sampling period which if not taken into consideration, can adversely affect system performance and even takes the system to instability. This work proposes a stability analysis of a discrete-time VS-MRAC accomplished for SISO linear time-invariant plants with relative degree one. The aim is to analyse the in uence of the sampling period in the system performance and the relation of this period with the chattering and system instability

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Na aplicação de produtos fitossanitários, a utilização de equipamentos que controlam automaticamente as seções da barra e a pulverização já é realidade; entretanto, ainda não há resultados que demonstrem a sua eficácia. Por esse motivo, este trabalho teve por finalidade desenvolver uma metodologia para a avaliação de um equipamento que controla automaticamente as seções e a pulverização. Avaliou-se um controlador automático de seções e pulverização de mercado, e, para tanto, foram utilizados três níveis de acurácia do sinal de GPS (algoritmo interno, SBAS e RTK), três ângulos para a simulação de entrada e saída da barra de pulverização em relação à borda do talhão (0; 45 e 60º ) e três velocidades de trabalho (1,66; 5,00 e 8,33 m s-1). A metodologia proposta possibilitou a determinação dos tempos e distâncias de abertura e fechamento das seções. Os coeficientes de variação para os tempos e distâncias de abertura e fechamento das seções indicaram uma variação considerável. Houve interações significativas em função do tipo de sinal de GPS. A configuração recomendada pelo fabricante e adotada para a avaliação do controlador automático de seções e pulverização não atende a todas as situações simuladas.

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A branch and bound algorithm is proposed to solve the H2-norm model reduction problem and the H2-norm controller reduction problem, with conditions assuring convergence to the global optimum in finite time. The lower and upper bounds used in the optimization procedure are obtained through linear matrix inequalities formulations. Examples illustrate the results.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)