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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Diferencialinio uždavinio su kintamais koeficientais tyrimas / Investigation of differential problem with variable coefficients

Rapalytė, Svajūnė 20 June 2012 (has links)
Magistro baigiamajame darbe nagrinėjamas diferencialinis operatorius su kintamais koeficientais ir viena klasikine, o kita nelokaliąja Samarskio ir Bitsadzės kraštine sąlyga. Šis uždavinys suvedamas į kanoninį pavidalą. Tiriamos kintamo koeficiento savybės, kaip jos keičiasi suvedant uždavinį į kanoninį pavidalą, taip pat tiriama šio uždavinio spektro priklausomybė nuo nelokaliosios kraštinės sąlygos parametrų. / In the Master's Thesis there is investigated a differential operator with variable coefficients, one classical and other nonlocal Samarskii-Bitsadze type boundary condition. There is written the canonical form of this problem. In the thesis there is analyzed the properties of variable coefficients, how they are changing when differential problem is written in the canonical form. Also the dependence of this problem spectrum on nonlocal boundary condition parameters is investigated.
2

Finita differensapproximationer av tvådimensionella vågekvationen med variabla koefficienter / Finite Difference Approximations of the Two-Dimensional Wave Equation with Variable Coefficients

Bergkvist, Herman January 2023 (has links)
I [Mattson, Journal of Scientific Computing 51.3 (2012), s. 650–682] konstruerades partialsummeringsoperatorer för finita differensapproximationer av andraderivator med variabla koefficienter. Vi tillämpar framgångsrikt dessa operatorer på vågekvationen i två dimensioner med diskontinuerliga koefficienter, utan särskild behandling av diskontinuiteten. Närmare bestämt undersöks (i) operatorernas fel och konvergensordning relativt ”korrekt” hantering av diskontinuiteter genom blockuppdelning med kopplingstermer; (ii) ifall mycket komplicerade koefficienter orsakar instabilitet eller icke-fysikaliska fel. Vi visar att hoppet i våghastighet i simuleringen sker ett antal punkter ifrån hoppet i koefficienter, där antalet punkter beror på operatorernas ordning och storleken av hoppet i koefficienter. I (i) får dessa två faktorer plus blockets form och antalet punkter en stor påverkan på både storleken av felet, samt metodens konvergensordning som varierar från ca 1–2,5. Annars sker i både (i) och (ii) inget större icke-fysikaliskt fel eller instabilitet, vilket gör denna relativt enkla metod tillämpningsbar på komplexa verklighetsbaserade problem.
3

[en] NEURO-FUZZY MODELLING AND CONTROL OF DYNAMIC SISTEMS / [pt] MODELAGEM E CONTROLE NEURO-FUZZY DE SISTEMAS DINÂMICOS

GIOVANE QUADRELLI 19 June 2002 (has links)
[pt] Este trabalho apresenta procedimentos de modelagem e controle neuro-fuzzy de sistemas dinâmicos. Neste contexto, é proposta e avaliada a utilização simultânea da abordagem neuro-fuzzy em todo o sistema de malha fechada controlador-planta.Na modelagem da planta, o espaço de entrada do sistema dinâmico é inicialmente dividido em um número de regiões de operação fuzzy onde modelos de ordem reduzida (ARMAX) representam o comportamento do sistema dinâmico. A saída completa do sistema - modelo global - é obtida através da conjunção das saídas dos modelos locais usando uma rede neuro-fuzzy.No controle da planta, é proposto um novo controlador neuro-fuzzy chamado Controlador Neuro-fuzzy de Coeficientes Variáveis (CNFCV), que tem como objetivos melhorar a robustez do sistema de controle a perturbações e a geração automática da variável manipulada, que é uma dificuldade normalmente encontrada em controladores neurais ou neuro-fuzzy. Esse controlador é originado dos modelos de redes neurais de Mellem (1997) e Velloso (1999), e utiliza redes neuro-fuzzy para a geração dos coeficientes variáveis de um modelo ARMA da variável manipulada. Apesar de juntar modelos de séries temporais com a abordagem neuro-fuzzy, o CNFCV tem como função não a previsão, mas sim o controle de uma planta ou processo.Para avaliar o desempenho do CNFCV são utilizados, como meios de comparação,controladores neuro- fuzzy conhecidos - FALCON-H Fuzzy Adaptive Learning Control Network with Hybrid Learning e NEFCON Neuro-Fuzzy Controller - e o tradicional controlador PID Proporcional- Integral-Derivativo.As plantas utilizadas são uma planta linear Bobinador, uma planta linearizada Pêndulo Invertido e uma planta não linear %CO2. A escolha de tais plantas deve-se ao fato de serem utilizadas e modeladas em aplicações práticas e em trabalhos acadêmicos. Os resultados obtidos com o CNFCV são analisados e comparados aos proporcionados pelas outras estruturas.Ao final são apresentadas conclusões e sugestões para trabalhos futuros. / [en] In this work procedures for neuro-fuzzy modelling and control of dynamic systems are reviewed and a new structure is proposed. In this, modelling and closed-loop control are performed simultaneously by using a neuro-fuzzy approach. In the modelling stage the input space of a dynamic system (plant) is initially divided into a number of fuzzy operating regions within which reduced order models are able to represent the system. The complete system model output - the global model - is obtained through the conjunction of the outputs of the local models. A new structure, called Neuro-Fuzzy Controller with Variable Coefficients (NFCVC) is proposed and evaluated. Its main objectives are to improve the system s robustness and to provide automatic generation of the manipulated variable in order to overcome a difficulty of neural and neuro-fuzzy controllers in general. The NFCVC is originated from models proposed by Mellem (1997) and Velloso (1999) and makes use of neuro-fuzzy networks to generate variable coefficients of an ARMA model. Despite combining times series models with a neuro-fuzzy approach, the main function of NFCVC is to perform the control of the plant.In order to evaluate the performance of NFCVC two well-known neuro-fuzzy controllers - FALCON-H (Fuzzy Adaptive Learning Control Network with Hybrid Learning) and the NEFCON (Neuro-Fuzzy Controller) - as well as the traditional PID controller are used as means of comparison.A linear plant (Rotor Winder), a linearized plant (Inverted Pendulum) and a nonlinear plant (%CO2) are used in the experiments. These plants are well-known and generally used in practical applications and/or academic works. The results for the NFCVC are analyzed and compared to those obtained with the others structures. Finally, conclusions and suggestions for future work are presented.
4

Adungované soustavy diferenciálních rovnic / Adjoint Differential Equations

Kmenta, Karel January 2007 (has links)
This project deals with solving differential equations. The aim is find the correct algorithm transforming differential equations of higher order with time variable coefficients to equivalent systems of differential equations of first order. Subsequently verify its functionality for equations containing the involutioin goniometrical functions and finally implement this algorithm. The reason for this transformation is requirement to solve these differential equations by programme TKSL (Taylor Kunovský simulation language).

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