981 resultados para Control applications


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Magnetorheological dampers are intrinsically nonlinear devices, which make the modeling and design of a suitable control algorithm an interesting and challenging task. To evaluate the potential of magnetorheological (MR) dampers in control applications and to take full advantages of its unique features, a mathematical model to accurately reproduce its dynamic behavior has to be developed and then a proper control strategy has to be taken that is implementable and can fully utilize their capabilities as a semi-active control device. The present paper focuses on both the aspects. First, the paper reports the testing of a magnetorheological damper with an universal testing machine, for a set of frequency, amplitude, and current. A modified Bouc-Wen model considering the amplitude and input current dependence of the damper parameters has been proposed. It has been shown that the damper response can be satisfactorily predicted with this model. Second, a backstepping based nonlinear current monitoring of magnetorheological dampers for semi-active control of structures under earthquakes has been developed. It provides a stable nonlinear magnetorheological damper current monitoring directly based on system feedback such that current change in magnetorheological damper is gradual. Unlike other MR damper control techniques available in literature, the main advantage of the proposed technique lies in its current input prediction directly based on system feedback and smooth update of input current. Furthermore, while developing the proposed semi-active algorithm, the dynamics of the supplied and commanded current to the damper has been considered. The efficiency of the proposed technique has been shown taking a base isolated three story building under a set of seismic excitation. Comparison with widely used clipped-optimal strategy has also been shown.

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Accurate mass flow measurement is very important in various monitoring and control applications. This paper proposes a novel method of fluid flow measurement by compensating the pressure drop across the ends of measuring unit using a compensating pump. The pressure drop due to the flow is balanced by a feedback control loop. This is a null-deflection type of measurement. As the insertion of such a measuring unit does not affect the functioning of the systems, this is also a non-disruptive flow measurement method. The implementation and design of such a unit are discussed. The system is modeled and simulated using the bond graph technique and it is experimentally validated. (C) 2009 Elsevier Ltd. All rights reserved.

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Diabetes is a serious disease during which the body's production and use of insulin is impaired, causing glucose concentration level toincrease in the bloodstream. Regulating blood glucose levels as close to normal as possible, leads to a substantial decrease in long term complications of diabetes. In this paper, an intelligent neural network on-line optimal feedback treatment strategy based on nonlinear optimal control theory is presented for the disease using subcutaneous treatment strategy. A simple mathematical model of the nonlinear dynamics of glucose and insulin interaction in the blood system is considered based on the Bergman's minimal model. A glucose infusion term representing the effect of glucose intake resulting from a meal is introduced into the model equations. The efficiency of the proposed controllers is shown taking random parameters and random initial conditions in presence of physical disturbances like food intake. A comparison study with linear quadratic regulator theory brings Out the advantages of the nonlinear control synthesis approach. Simulation results show that unlike linear optimal control, the proposed on-line continuous infusion strategy never leads to severe hypoglycemia problems.

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This paper presents an optimization algorithm for an ammonia reactor based on a regression model relating the yield to several parameters, control inputs and disturbances. This model is derived from the data generated by hybrid simulation of the steady-state equations describing the reactor behaviour. The simplicity of the optimization program along with its ability to take into account constraints on flow variables make it best suited in supervisory control applications.

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The controllability grammian is important in many control applications. Given a set of closed-loop eigenvalues the corresponding controllability grammian can be obtained by computing the controller which assigns the eigenvalues and then by solving the Lyapunov equation that defines the grammian. The relationship between the controllability grammian, resulting from state feedback, and the closed-loop eigenvalues of a single input linear time invariant (LTI) system is obtained. The proposed methodology does not require the computation of the controller that assigns the specified eigenvalues. The closed-loop system matrix is obtained from the knowledge of the open-loop system matrix, control influence matrix and the specified closed-loop eigenvalues. Knowing the closed-loop system matrix, the grammian is then obtained from the solution of the Lyapunov equation that defines it. Finally the proposed idea is extended to find the state covariance matrix for a specified set of closed-loop eigenvalues (without computing the controller), due to impulsive input in the disturbance channel and to solve the eigenvalue assignment problem for the single input case.

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Diabetes is a long-term disease during which the body's production and use of insulin are impaired, causing glucose concentration level to increase in the bloodstream. Regulating blood glucose levels as close to normal as possible leads to a substantial decrease in long-term complications of diabetes. In this paper, an intelligent online feedback-treatment strategy is presented for the control of blood glucose levels in diabetic patients using single network adaptive critic (SNAC) neural networks (which is based on nonlinear optimal control theory). A recently developed mathematical model of the nonlinear dynamics of glucose and insulin interaction in the blood system has been revised and considered for synthesizing the neural network for feedback control. The idea is to replicate the function of pancreatic insulin, i.e. to have a fairly continuous measurement of blood glucose and a situation-dependent insulin injection to the body using an external device. Detailed studies are carried out to analyze the effectiveness of this adaptive critic-based feedback medication strategy. A comparison study with linear quadratic regulator (LQR) theory shows that the proposed nonlinear approach offers some important advantages such as quicker response, avoidance of hypoglycemia problems, etc. Robustness of the proposed approach is also demonstrated from a large number of simulations considering random initial conditions and parametric uncertainties. Copyright (C) 2009 John Wiley & Sons, Ltd.

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To combine the advantages of both stability and optimality-based designs, a single network adaptive critic (SNAC) aided nonlinear dynamic inversion approach is presented in this paper. Here, the gains of a dynamic inversion controller are selected in such a way that the resulting controller behaves very close to a pre-synthesized SNAC controller in the output regulation sense. Because SNAC is based on optimal control theory, it makes the dynamic inversion controller operate nearly optimal. More important, it retains the two major benefits of dynamic inversion, namely (i) a closed-form expression of the controller and (ii) easy scalability to command tracking applications without knowing the reference commands a priori. An extended architecture is also presented in this paper that adapts online to system modeling and inversion errors, as well as reduced control effectiveness, thereby leading to enhanced robustness. The strengths of this hybrid method of applying SNAC to optimize an nonlinear dynamic inversion controller is demonstrated by considering a benchmark problem in robotics, that is, a two-link robotic manipulator system. Copyright (C) 2013 John Wiley & Sons, Ltd.

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This thesis presents a concept for ultra-lightweight deformable mirrors based on a thin substrate of optical surface quality coated with continuous active piezopolymer layers that provide modes of actuation and shape correction. This concept eliminates any kind of stiff backing structure for the mirror surface and exploits micro-fabrication technologies to provide a tight integration of the active materials into the mirror structure, to avoid actuator print-through effects. Proof-of-concept, 10-cm-diameter mirrors with a low areal density of about 0.5 kg/m² have been designed, built and tested to measure their shape-correction performance and verify the models used for design. The low cost manufacturing scheme uses replication techniques, and strives for minimizing residual stresses that deviate the optical figure from the master mandrel. It does not require precision tolerancing, is lightweight, and is therefore potentially scalable to larger diameters for use in large, modular space telescopes. Other potential applications for such a laminate could include ground-based mirrors for solar energy collection, adaptive optics for atmospheric turbulence, laser communications, and other shape control applications.

The immediate application for these mirrors is for the Autonomous Assembly and Reconfiguration of a Space Telescope (AAReST) mission, which is a university mission under development by Caltech, the University of Surrey, and JPL. The design concept, fabrication methodology, material behaviors and measurements, mirror modeling, mounting and control electronics design, shape control experiments, predictive performance analysis, and remaining challenges are presented herein. The experiments have validated numerical models of the mirror, and the mirror models have been used within a model of the telescope in order to predict the optical performance. A demonstration of this mirror concept, along with other new telescope technologies, is planned to take place during the AAReST mission.

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A acústica submarina vem sendo estudada por décadas, mas redes submarinas com transmissão acústica e protocolos específicos para a comunicação neste meio são campos de pesquisa que estão iniciando. Recentemente alguns simuladores, baseados no NS-2, foram desenvolvidos para o estudo destas redes. Este trabalho avalia através de simulações a viabilidade de aplicações genéricas de monitoramento e controle em redes acústicas submarinas. São propostas e utilizadas três topologias básicas para redes acústicas submarinas: linha, quadro e cubo e dois protocolos MAC: Broadcast e R-MAC. Em nossas análises comparamos esses dois protocolos em relação ao consumo total de energia e o atraso total na rede. Os resultados mostram que essas topologias associadas aos protocolos MAC atendem as necessidades e as peculiaridades da grande maioria das aplicações de monitoramento e controle que utilizam redes acústicas submarinas. O objetivo deste estudo não foi determinar qual a melhor topologia ou o melhor tipo de protocolo de acesso ao meio, mais sim determinar qual a configuração de rede mais indicada para determinada aplicação levando em consideração as características da cada uma delas.

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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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Este trabalho investiga a implementação de sistemas fuzzy com circuitos eletrônicos. Tais sistemas têm demonstrado sua capacidade de resolver diversos tipos de problemas em várias aplicações de engenharia, em especial nas relacionadas com controle de processos. Para processos mais complexos, o raciocínio aproximado da lógica fuzzy fornece uma maneira de compreender o comportamento do sistema, permitindo a interpolação aproximada entre situações observadas de entrada e saída. A implementação de um sistema fuzzy pode ser baseada em hardware, em software ou em ambos. Tipicamente, as implementações em software utilizam ambientes de programação integrados com simulação, de modo a facilitar o trabalho do projetista. As implementações em hardware, tradicionais ou evolutivas, podem ser analógicas ou digitais e viabilizam sistemas de maior desempenho. Este trabalho tem por objetivo pesquisar a implementação eletrônica de sistemas fuzzy, a fim de viabilizar a criação de sistemas reais capazes de realizar o mapeamento de entrada e saída adequado. O foco é a utilização de uma plataforma com uma arquitetura analógico-digital baseada em uma tabela de mapeamento armazenada em uma memória de alta capacidade. Memórias do tipo SD (Secure Digital) foram estudadas e utilizadas na construção do protótipo eletrônico da plataforma. Também foram desenvolvidos estudos sobre a quantização, especificamente sobre a possibilidade de redução do número de bits. Com a implementação realizada é possível desenvolver um sistema fuzzy num ambiente simulado (Matlab), configurar a plataforma e executar o sistema fuzzy diretamente na plataforma eletrônica. Os testes com o protótipo construído comprovaram seu bom funcionamento.

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Computer Aided Control Engineering involves three parallel streams: Simulation and modelling, Control system design (off-line), and Controller implementation. In industry the bottleneck problem has always been modelling, and this remains the case - that is where control (and other) engineers put most of their technical effort. Although great advances in software tools have been made, the cost of modelling remains very high - too high for some sectors. Object-oriented modelling, enabling truly re-usable models, seems to be the key enabling technology here. Software tools to support control systems design have two aspects to them: aiding and managing the work-flow in particular projects (whether of a single engineer or of a team), and provision of numerical algorithms to support control-theoretic and systems-theoretic analysis and design. The numerical problems associated with linear systems have been largely overcome, so that most problems can be tackled routinely without difficulty - though problems remain with (some) systems of extremely large dimensions. Recent emphasis on control of hybrid and/or constrained systems is leading to the emerging importance of geometric algorithms (ellipsoidal approximation, polytope projection, etc). Constantly increasing computational power is leading to renewed interest in design by optimisation, an example of which is MPC. The explosion of embedded control systems has highlighted the importance of autocode generation, directly from modelling/simulation products to target processors. This is the 'new kid on the block', and again much of the focus of commercial tools is on this part of the control engineer's job. Here the control engineer can no longer ignore computer science (at least, for the time being). © 2006 IEEE.