959 resultados para MODEL-PREDICTIVE CONTROL


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The power rating of wind turbines is constantly increasing; however, keeping the voltage rating at the low-voltage level results in high kilo-ampere currents. An alternative for increasing the power levels without raising the voltage level is provided by multiphase machines. Multiphase machines are used for instance in ship propulsion systems, aerospace applications, electric vehicles, and in other high-power applications including wind energy conversion systems. A machine model in an appropriate reference frame is required in order to design an efficient control for the electric drive. Modeling of multiphase machines poses a challenge because of the mutual couplings between the phases. Mutual couplings degrade the drive performance unless they are properly considered. In certain multiphase machines there is also a problem of high current harmonics, which are easily generated because of the small current path impedance of the harmonic components. However, multiphase machines provide special characteristics compared with the three-phase counterparts: Multiphase machines have a better fault tolerance, and are thus more robust. In addition, the controlled power can be divided among more inverter legs by increasing the number of phases. Moreover, the torque pulsation can be decreased and the harmonic frequency of the torque ripple increased by an appropriate multiphase configuration. By increasing the number of phases it is also possible to obtain more torque per RMS ampere for the same volume, and thus, increase the power density. In this doctoral thesis, a decoupled d–q model of double-star permanent-magnet (PM) synchronous machines is derived based on the inductance matrix diagonalization. The double-star machine is a special type of multiphase machines. Its armature consists of two three-phase winding sets, which are commonly displaced by 30 electrical degrees. In this study, the displacement angle between the sets is considered a parameter. The diagonalization of the inductance matrix results in a simplified model structure, in which the mutual couplings between the reference frames are eliminated. Moreover, the current harmonics are mapped into a reference frame, in which they can be easily controlled. The work also presents methods to determine the machine inductances by a finite-element analysis and by voltage-source inverters on-site. The derived model is validated by experimental results obtained with an example double-star interior PM (IPM) synchronous machine having the sets displaced by 30 electrical degrees. The derived transformation, and consequently, the decoupled d–q machine model, are shown to model the behavior of an actual machine with an acceptable accuracy. Thus, the proposed model is suitable to be used for the model-based control design of electric drives consisting of double-star IPM synchronous machines.

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Tutkimuksen tarkoituksena on tutkia globaalin konsernin yhden liiketoimintayksikön tuotekustannuslaskennan nykytilaa. Lisäksi tutkimuksessa selvitetään, miten tuotekohtaista kustannusseurantaa voidaan kehittää mallimoottoriajatuksen avulla. Tutkimus on toteutettu laadullisena case-tutkimuksena yhden organisaation tietojen pohjalta. Teoriaosuuden lähdeaineistot koostuvat pääosin kustannuslaskennan ja -johtamisen perusteoksista ja tieteellisistä artikkeleista. Empiriaosuuden tiedot pohjautuvat haastatteluihin, tietojärjestelmiin ja tutustumiseen organisaatioon. Tutkimuksessa selvisi, että liiketoimintayksikkö ei tällä hetkellä seuraa tuotekohtaisia kustannuksia yksittäisten tuotteiden tasolla. Kustannusseuranta tapahtuu sen sijaan suurempien kokonaisuuksien keskimääräisten kustannuksien tasolla. Tuotekustannuslaskenta on toteutettu perinteiseksi menetelmäksi luokiteltavalla laskentatavalla, jossa välilliset kustannukset kohdistetaan yleiskustannuslisäprosenttien avulla. Tutkimuksen perusteella yleiskustannuksien kohdistamisperusteissa on havaittavissa viitteitä kustannuksien vääristymisestä. Tuotetason kustannuksien seurantaan kehitettiin mallimoottoriajatukseen pohjautuva kustannusmalli, jonka avulla seurataan tarkasti valikoitujen tuotteiden kustannuksien kehittymistä sekä kustannusrakennetta. Mallin avulla voidaan lisätä tuotetason kustannustietoisuutta liiketoimintayksikössä sekä tehdä havaintoja tuotekohtaisten kustannuksien kehityssuunnasta. Mallin kustannustietona käytetään olemassa olevan kustannuslaskentajärjestelmän tietoja. Tästä johtuen mallin kustannustiedoissa on havaittavissa myös viitteitä kustannuksien vääristymisestä.

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El pronóstico de la Neumonía Adquirida en la Comunidad Severa (NAC-S) depende de decisiones terapéuticas instauradas tempranamente. Los cambios fisiológicos ocurridos en las primeras horas pueden ser difíciles de detectar. No existe ningún modelo para la determinación temprana del éxito de la terapia instaurada en NAC-S. Metodología: Descripción de la totalidad de los pacientes con NAC-S hospitalizados en la Unidad de Cuidado Intensivo de la Fundación Cardioinfantil entre los años 2008 y 2012 haciendo comparaciones entre grupos (muertos vs. supervivientes) y entre momentos (0, 24 y 48 horas desde el ingreso a la UCI) y realizando regresión logística binaria. Resultados: Entre los pacientes que fallecieron la necesidad de soporte vasoactivo fue mayor en todos los momentos evaluados (sig=0.001), en la línea de base tuvieron mayores requerimientos de la Fracción Inspirada de O2 (mediana 0.55% vs. 0.50%, sig=0.011), a las 24 horas tuvieron pH (mediana 7.345 vs.7.370, sig=0.025) y tensión arterial diastólica (mediana 58.5mmHg vs.61.0mmHg, sig =0.049) menores, y a las 48 horas glicemia (mediana 157mg/dL vs.142mg/dL, sig =0.026) creatinina (mediana 1.1mg/dL vs.0.7mg/dL, sig =0.062) y nitrógeno ureico (mediana 35mg/dL vs. 22mg/dL, sig =0.003) mayores comparados con los pacientes que sobrevivieron. Entre los pacientes supervivientes hubo una disminución de la frecuencia cardiaca entre las 0 y 24 horas (mediana 97lpm vs. 86lpm, sig =0.000) y entre las 0 y las 48 horas (mediana 97lpm vs. 81lpm, sig=0.000) y una disminución de los neutrófilos entre las 0 y las 48 horas (mediana 9838 vs. 8617, sig=0.062). Conclusiones: Nuestros hallazgos sugieren la existencia de una secuencia de fenómenos fisiopatológicos que al ser reconocida temprana y claramente permitiría establecer un plan de reanimación más especifico y eficaz. Estas diferencias se pueden plantear en el contexto de un modelo mixto predictivo

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In the continuing debate over the impact of genetically modified (GM) crops on farmers of developing countries, it is important to accurately measure magnitudes such as farm-level yield gains from GM crop adoption. Yet most farm-level studies in the literature do not control for farmer self-selection, a potentially important source of bias in such estimates. We use farm-level panel data from Indian cotton farmers to investigate the yield effect of GM insect-resistant cotton. We explicitly take into account the fact that the choice of crop variety is an endogenous variable which might lead to bias from self-selection. A production function is estimated using a fixed-effects model to control for selection bias. Our results show that efficient farmers adopt Bacillus thuringiensis (Bt) cotton at a higher rate than their less efficient peers. This suggests that cross-sectional estimates of the yield effect of Bt cotton, which do not control for self-selection effects, are likely to be biased upwards. However, after controlling for selection bias, we still find that there is a significant positive yield effect from adoption of Bt cotton that more than offsets the additional cost of Bt seed.

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In the continuing debate over the impact of genetically modified (GM) crops on farmers of developing countries, it is important to accurately measure magnitudes such as farm-level yield gains from GM crop adoption. Yet most farm-level studies in the literature do not control for farmer self-selection, a potentially important source of bias in such estimates. We use farm-level panel data from Indian cotton farmers to investigate the yield effect of GM insect-resistant cotton. We explicitly take into account the fact that the choice of crop variety is an endogenous variable which might lead to bias from self-selection. A production function is estimated using a fixed-effects model to control for selection bias. Our results show that efficient farmers adopt Bacillus thuringiensis (Bt) cotton at a higher rate than their less efficient peers. This suggests that cross-sectional estimates of the yield effect of Bt cotton, which do not control for self-selection effects, are likely to be biased upwards. However, after controlling for selection bias, we still find that there is a significant positive yield effect from adoption of Bt cotton that more than offsets the additional cost of Bt seed.

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A new self-tuning implicit pole-assignment algorithm is presented which, through the use of a pole compression factor and different RLS model and control structures, overcomes stability and convergence problems encountered in previously available algorithms. Computational requirements of the technique are much reduced when compared to explicit pole-assignment schemes, whereas the inherent robustness of the strategy is retained.

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Differential geometry is used to investigate the structure of neural-network-based control systems. The key aspect is relative order—an invariant property of dynamic systems. Finite relative order allows the specification of a minimal architecture for a recurrent network. Any system with finite relative order has a left inverse. It is shown that a recurrent network with finite relative order has a local inverse that is also a recurrent network with the same weights. The results have implications for the use of recurrent networks in the inverse-model-based control of nonlinear systems.

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O objetivo desta pesquisa foi analisar o desenho institucional do controle externo sobre os contratos de gestão no âmbito do Tribunal de Contas do estado de Pernambuco quanto a sua aderência aos conteúdos da lei estadual que disciplina as Organizações Sociais e quanto a sua observância por parte dos atores envolvidos: Administração Pública, técnicos do tribunal de contas e membros do seu corpo julgador. Foram assumidas as seguintes premissas: que os novos arranjos de prestação de serviços públicos, por meio de parcerias com as Organizações Sociais, demandam por parte dos Tribunais de Contas desenhos institucionais de fiscalização específicos, que a pesar de variáveis devem primar por sua capacidade de revelar informações; que o processo de formatação destes desenhos institucionais deve ser dinâmico, permitindo-se que as contigências experimentadas na sua implementação possam contribuir no seu aperfeiçoamento; e que esses desenhos institucionais geram impacto no comportamento dos atores envolvidos. O estudo foi realizado por meio de pesquisa documental. A metodologia qualitativa de análise de conteúdo foi escolhida para análise dos dados. Os resultados da pesquisa permitiram concluir que o desenho institucional de controle dos contratos de gestão no âmbito do TCE-PE caracteriza-se por sua fragilidade como mecanismo de revelação de informação e, consequentemente, não contribui para a redução da assimetria de informação que se estabelece com a implementação dos contratos de gestão. Adicionalmente, compromete e limita o desempenho do Tribunal de Contas no controle destes ajustes. Verificou-se, também, uma a baixa observância do desenho institucional identificado, em que pese sua fragilidade, por parte dos atores envolvidos no controle dos contratos de gestão, implicando em uma baixa institucionalização deste desenho. Os resultados devem proporcionar uma rediscussão acerca dos mecanismos de controle dos contratos de gestão por parte do TCE-PE, que poderá resultar em um novo desenho institucional com vistas a conferir maior transparência às parcerias com as Organizações Sociais.

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A pesquisa tem como objetivo desenvolver uma estrutura de controle preditivo neural, com o intuito de controlar um processo de pH, caracterizado por ser um sistema SISO (Single Input - Single Output). O controle de pH é um processo de grande importância na indústria petroquímica, onde se deseja manter constante o nível de acidez de um produto ou neutralizar o afluente de uma planta de tratamento de fluidos. O processo de controle de pH exige robustez do sistema de controle, pois este processo pode ter ganho estático e dinâmica nãolineares. O controlador preditivo neural envolve duas outras teorias para o seu desenvolvimento, a primeira referente ao controle preditivo e a outra a redes neurais artificiais (RNA s). Este controlador pode ser dividido em dois blocos, um responsável pela identificação e outro pelo o cálculo do sinal de controle. Para realizar a identificação neural é utilizada uma RNA com arquitetura feedforward multicamadas com aprendizagem baseada na metodologia da Propagação Retroativa do Erro (Error Back Propagation). A partir de dados de entrada e saída da planta é iniciado o treinamento offline da rede. Dessa forma, os pesos sinápticos são ajustados e a rede está apta para representar o sistema com a máxima precisão possível. O modelo neural gerado é usado para predizer as saídas futuras do sistema, com isso o otimizador calcula uma série de ações de controle, através da minimização de uma função objetivo quadrática, fazendo com que a saída do processo siga um sinal de referência desejado. Foram desenvolvidos dois aplicativos, ambos na plataforma Builder C++, o primeiro realiza a identificação, via redes neurais e o segundo é responsável pelo controle do processo. As ferramentas aqui implementadas e aplicadas são genéricas, ambas permitem a aplicação da estrutura de controle a qualquer novo processo

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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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The control, automation and optimization areas help to improve the processes used by industry. They contribute to a fast production line, improving the products quality and reducing the manufacturing costs. Didatic plants are good tools for research in these areas, providing a direct contact with some industrial equipaments. Given these capabilities, the main goal of this work is to model and control a didactic plant, which is a level and flow process control system with an industrial instrumentation. With a model it is possible to build a simulator for the plant that allows studies about its behaviour, without any of the real processes operational costs, like experiments with controllers. They can be tested several times before its application in a real process. Among the several types of controllers, it was used adaptive controllers, mainly the Direct Self-Tuning Regulators (DSTR) with Integral Action and the Gain Scheduling (GS). The DSTR was based on Pole-Placement design and use the Recursive Least Square to calculate the controller parameters. The characteristics of an adaptive system was very worth to guarantee a good performance when the controller was applied to the plant

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Includes bibliography

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The good efficiency in a sewage treatment plant (WWTP) is a great importance to the environment. The management of electromechanical equipment installed in these stations is a major challenge due to the fact that they are installed on areas of difficult access and maintenance unhealthy and making the time for the correction of any faults is extended. This paper proposes the development of a Wireless Sensor Network (WSN), in order to monitor electromechanical equipment, allowing the Concessionaire a predictive control in real time. The design of a wireless sensors network for monitoring equipment requires not only the development and assembly of the sensor modules, but must also include the development of software for managing the data collected. Thus, this work includes a Zigbee WSN, small, adapted for monitoring of electromechanical equipment and environmental conditions of a WWTP, type stabilization pond, installed in an area of approximately 0.15 km 2 and the average flow of 320 liters of treatment per second. The experimental results show that this monitoring system can perform with the collection of parameters of performance and quality assessment at the station.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)