912 resultados para Estabilidade e Robustez de Sistemas de Controle Neurais


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Este trabalho propõe uma estratégia fuzzy, do tipo Rede de Controladores Locais, aplicável à melhoria da estabilidade dinâmica em sistemas elétricos de potência, visando compensar possíveis perdas de sintonia devido à ocorrência de variações nas condições operacionais da planta. A adaptação dos ganhos do controlador fuzzy é efetuada on-line, interpolando-se os ganhos de um conjunto finito de controladores locais fixos. Ao ocorrer variações nas condições operacionais da planta, os ganhos da lei de controle são ajustados automaticamente de modo a manter satisfatório o desempenho do sistema de controle. O desempenho do controle foi avaliado através de estudos de simulação, utilizando-se um modelo dinâmico não-linear, do tipo máquina barra infinita. Os resultados mostram que o emprego da estratégia proposta permite obter melhorias no desempenho dinâmico do sistema.

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Nesta Dissertação são propostos dois esquemas de controle para sistemas não-lineares com atraso. No primeiro, o objetivo é controlar uma classe de sistemas incertos multivariáveis, de grau relativo unitário, com perturbações não-lineares descasadas dependentes do estado, e com atraso incerto e variante no tempo em relação ao estado. No segundo, deseja-se controlar uma classe de sistemas monovariáveis, com parâmetros conhecidos, grau relativo arbitrário, atraso arbitrário conhecido e constante na saída. Admitindo-se que o atraso na entrada pode ser deslocado para a saída, então, o segundo esquema de controle pode ser aplicado a sistemas com atraso na entrada. Os controladores desenvolvidos são baseados no controle por modo deslizante e realimentação de saída, com função de modulação para a amplitude do sinal de controle. Além disso, observadores estimam as variáveis de estado não-medidas. Em ambos os esquemas de controle propostos, garante-se propriedades de estabilidade globais do sistema em malha fechada. Simulações ilustram a eficácia dos controladores desenvolvidos.

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Neste trabalho apresentamos as etapas para a utilização do método da Programação Dinâmica, ou Princípio de Otimização de Bellman, para aplicações de controle ótimo. Investigamos a noção de funções de controle de Lyapunov (FCL) e sua relação com a estabilidade de sistemas autônomos com controle. Uma função de controle de Lyapunov deverá satisfazer a equação de Hamilton-Jacobi-Bellman (H-J-B). Usando esse fato, se uma função de controle de Lyapunov é conhecida, será então possível determinar a lei de realimentação ótima; isto é, a lei de controle que torna o sistema globalmente assintóticamente controlável a um estado de equilíbrio. Como aplicação, apresentamos uma modelagem matemática adequada a um problema de controle ótimo de certos sistemas biológicos. Este trabalho conta também com um breve histórico sobre o desenvolvimento da Teoria de Controle de forma a ilustrar a importância, o progresso e a aplicação das técnicas de controle em diferentes áreas ao longo do tempo.

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A presente dissertação tem como objetivo estudar e aprimorar métodos de projetos de controladores para sistemas de potência, sendo que esse trabalho trata da estabilidade dinâmica de sistemas de potência e, portanto, do projeto de controladores amortecedores de oscilações eletromecânicas para esses sistemas. A escolha dos métodos aqui estudados foi orientada pelos requisitos que um estabilizador de sistemas de potência (ESP) deve ter, que são robustez, descentralização e coordenação. Sendo que alguns deles tiveram suas características aprimoradas para atender a esses requisitos. A abordagem dos métodos estudados foi restringida à análise no domínio tempo, pois a abordagem temporal facilita a modelagem das incertezas paramétricas, para atender ao requisito da robustez, e também permite a formulação do controle descentralizado de maneira simples. Além disso, a abordagem temporal permite a formulação do problema de projeto utilizando desigualdades matriciais lineares (LMI’s), as quais possuem como vantagem o fato do conjunto solução ser sempre convexo e a existência de algoritmos eficientes para o cálculo de sua solução. De fato, existem diversos pacotes computacionais desenvolvidos no mercado para o cálculo da solução de um problema de inequações matriciais lineares. Por esse motivo, os métodos de projeto para controladores de saída buscam sempre colocar o problema na forma de LMI’s, tendo em vista que ela garante a obtenção de solução, caso essa solução exista.

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The Predictive Controller has been receiving plenty attention in the last decades, because the need to understand, to analyze, to predict and to control real systems has been quickly growing with the technological and industrial progress. The objective of this thesis is to present a contribution for the development and implementation of Nonlinear Predictive Controllers based on Hammerstein model, as well as to its make properties evaluation. In this case, in the Nonlinear Predictive Controller development the time-step linearization method is used and a compensation term is introduced in order to improve the controller performance. The main motivation of this thesis is the study and stability guarantee for the Nonlinear Predictive Controller based on Hammerstein model. In this case, was used the concepts of sections and Popov Theorem. Simulation results with literature models shows that the proposed approaches are able to control with good performance and to guarantee the systems stability

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In this Thesis, the development of the dynamic model of multirotor unmanned aerial vehicle with vertical takeoff and landing characteristics, considering input nonlinearities and a full state robust backstepping controller are presented. The dynamic model is expressed using the Newton-Euler laws, aiming to obtain a better mathematical representation of the mechanical system for system analysis and control design, not only when it is hovering, but also when it is taking-off, or landing, or flying to perform a task. The input nonlinearities are the deadzone and saturation, where the gravitational effect and the inherent physical constrains of the rotors are related and addressed. The experimental multirotor aerial vehicle is equipped with an inertial measurement unit and a sonar sensor, which appropriately provides measurements of attitude and altitude. A real-time attitude estimation scheme based on the extended Kalman filter using quaternions was developed. Then, for robustness analysis, sensors were modeled as the ideal value with addition of an unknown bias and unknown white noise. The bounded robust attitude/altitude controller were derived based on globally uniformly practically asymptotically stable for real systems, that remains globally uniformly asymptotically stable if and only if their solutions are globally uniformly bounded, dealing with convergence and stability into a ball of the state space with non-null radius, under some assumptions. The Lyapunov analysis technique was used to prove the stability of the closed-loop system, compute bounds on control gains and guaranteeing desired bounds on attitude dynamics tracking errors in the presence of measurement disturbances. The controller laws were tested in numerical simulations and in an experimental hexarotor, developed at the UFRN Robotics Laboratory

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This work presents a description of models development at DigSILENT PowerFactoryT M program for the transient stability study in power systems with wind turbine. The main goal is to make available means to use a dynamic simulation program in power systems, widely published, and utilize it as a tool that helps in programs results evaluations used for this intent. The process of simulations and analyses results starts after the models setting description phase. The results obtained by the DigSILENT PowerFactoryT M and ATP, program chosen to the validation also international recognized, are compared during this phase. The main tools and guide lines of PowerFactoryT M program use are presented here, directing these elements to the solution of the approached problem. For the simulation it is used a real system which it will be connected a wind farm. Two different technologies of wind turbines were implemented: doublyfed induction generator with frequency converter, connecting the rotor to the stator and to the grid, and synchronous wind generator with frequency converter, interconnecting the generator to the grid. Besides presenting the basic conceptions of dynamic simulation, it is described the implemented control strategies and models of turbine and converters. The stability of the wind turbine interconnected to grid is analyzed in many operational conditions, resultant of diverse kinds of disturbances

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A neuro-fuzzy system consists of two or more control techniques in only one structure. The main characteristic of this structure is joining one or more good aspects from each technique to make a hybrid controller. This controller can be based in Fuzzy systems, artificial Neural Networks, Genetics Algorithms or rein forced learning techniques. Neuro-fuzzy systems have been shown as a promising technique in industrial applications. Two models of neuro-fuzzy systems were developed, an ANFIS model and a NEFCON model. Both models were applied to control a ball and beam system and they had their results and needed changes commented. Choose of inputs to controllers and the algorithms used to learning, among other information about the hybrid systems, were commented. The results show the changes in structure after learning and the conditions to use each one controller based on theirs characteristics

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This work presents a description of models development at DigSILENT PowerFactoryTM program for the transient stability study in power systems with wind turbine. The main goal is to make available means to use a dynamic simulation program in power systems, widely published, and utilize it as a tool that helps in programs results evaluations used for this intent. The process of simulations and analyses results starts after the models setting description phase. The results obtained by the DigSILENT PowerFactoryTM and ATP, program chosen to the validation also international recognized, are compared during this phase. The main tools and guide lines of PowerFactoryTM program use are presented here, directing these elements to the solution of the approached problem. For the simulation it is used a real system which it will be connected a wind farm. Two different technologies of wind turbines were implemented: doubly-fed induction generator with frequency converter, connecting the rotor to the stator and to the grid, and synchronous wind generator with frequency converter, interconnecting the generator to the grid. Besides presenting the basic conceptions of dynamic simulation, it is described the implemented control strategies and models of turbine and converters. The stability of the wind turbine interconnected to grid is analyzed in many operational conditions, resultant of diverse kinds of disturbances

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The stability of synchronous generators connected to power grid has been the object of study and research for years. The interest in this matter is justified by the fact that much of the electricity produced worldwide is obtained with the use of synchronous generators. In this respect, studies have been proposed using conventional and unconventional control techniques such as fuzzy logic, neural networks, and adaptive controllers to increase the stabilitymargin of the systemduring sudden failures and transient disturbances. Thismaster thesis presents a robust unconventional control strategy for maintaining the stability of power systems and regulation of output voltage of synchronous generators connected to the grid. The proposed control strategy comprises the integration of a sliding surface with a linear controller. This control structure is designed to prevent the power system losing synchronism after a sudden failure and regulation of the terminal voltage of the generator after the fault. The feasibility of the proposed control strategy was experimentally tested in a salient pole synchronous generator of 5 kVA in a laboratory structure

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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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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Engenharia Elétrica - FEIS

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)