9 resultados para State-derivative feedback control
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Digital Microfluidics (DMF) is a second generation technique, derived from the conventional microfluidics that instead of using continuous liquid fluxes, it uses only individual droplets driven by external electric signals. In this thesis a new DMF control/sensing system for visualization, droplet control (movement, dispensing, merging and splitting) and real time impedance measurement have been developed. The software for the proposed system was implemented in MATLAB with a graphical user interface. An Arduino was used as control board and dedicated circuits for voltage switching and contacts were designed and implemented in printed circuit boards. A high resolution camera was integrated for visualization. In our new approach, the DMF chips are driven by a dual-tone signal where the sum of two independent ac signals (one for droplet operations and the other for impedance sensing) is applied to the electrodes, and afterwards independently evaluated by a lock-in amplifier. With this new approach we were able to choose the appropriated amplitudes and frequencies for the different proposes (actuation and sensing). The measurements made were used to evaluate the real time droplet impedance enabling the knowledge of its position and velocity. This new approach opens new possibilities for impedance sensing and feedback control in DMF devices.
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MSC Dissertation in Computer Engineering
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Dissertação apresentada para obtenção do grau de Doutor em Matemática na especialidade de Equações Diferenciais, pela Universidade Nova de Lisboa,Faculdade de Ciências e Tecnologia
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IEEE International Symposium on Circuits and Systems, pp. 2258 – 2261, Seattle, EUA
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The aim of this contribution is to extend the techniques of composite materials design to non-linear material behaviour and apply it for design of new materials for passive vibration control. As a first step a computational tool allowing determination of macroscopic optimized one-dimensional isolator behaviour was developed. Voigt, Maxwell, standard and more complex material models can be implemented. Objective function considers minimization of the initial reaction and/or displacement peak as well as minimization of the steady-state amplitude of reaction and/or displacement. The complex stiffness approach is used to formulate the governing equations in an efficient way. Material stiffness parameters are assumed as non-linear functions of the displacement. The numerical solution is performed in the complex space. The steady-state solution in the complex space is obtained by an iterative process based on the shooting method which imposes the conditions of periodicity with respect to the known value of the period. Extension of the shooting method to the complex space is presented and verified. Non-linear behaviour of material parameters is then optimized by generic probabilistic meta-algorithm, simulated annealing. Dependence of the global optimum on several combinations of leading parameters of the simulated annealing procedure, like neighbourhood definition and annealing schedule, is also studied and analyzed. Procedure is programmed in MATLAB environment.
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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Madine Darby Canine Kidney (MDCK) cell lines have been extensively evaluated for their potential as host cells for influenza vaccine production. Recent studies allowed the cultivation of these cells in a fully defined medium and in suspension. However, reaching high cell densities in animal cell cultures still remains a challenge. To address this shortcoming, a combined methodology allied with knowledge from systems biology was reported to study the impact of the cell environment on the flux distribution. An optimization of the medium composition was proposed for both a batch and a continuous system in order to reach higher cell densities. To obtain insight into the metabolic activity of these cells, a detailed metabolic model previously developed by Wahl A. et. al was used. The experimental data of four cultivations of MDCK suspension cells, grown under different conditions and used in this work came from the Max Planck Institute, Magdeburg, Germany. Classical metabolic flux analysis (MFA) was used to estimate the intracellular flux distribution of each cultivation and then combined with partial least squares (PLS) method to establish a link between the estimated metabolic state and the cell environment. The validation of the MFA model was made and its consistency checked. The resulted PLS model explained almost 70% of the variance present in the flux distribution. The medium optimization for the continuous system and for the batch system resulted in higher biomass growth rates than the ones obtained experimentally, 0.034 h-1 and 0.030 h-1, respectively, thus reducing in almost 10 hours the duplication time. Additionally, the optimal medium obtained for the continuous system almost did not consider pyruvate. Overall the proposed methodology seems to be effective and both proposed medium optimizations seem to be promising to reach high cell densities.