No description available.

La force de diélectrophorèse (DEP) est utilisée pour manipuler, séparer et positionner différent types des particules (cellules, bactéries, nanotubes de carbone). Dans le but d étudieret de simuler une loi de commande permettant le suivi de la trajectoire d une particule soumise à la force DEP un modèle est nécessaire. Les méthodes utilisées pour simuler la force DEP sont généralement basées soit sur des simulateurs à éléments finis (FEM), soit sur des équations analytiques. Les simulateurs FEM ne permettent pas la variation des paramètres (tensions électriques) lors du calcul de la trajectoire et les équations analytiques sont limitées à des géométries simples des électrodes. Dans ce manuscrit, une méthode hybride basée sur les calculs FEM et analytique est proposée. Cette méthode permet de simuler la trajectoire d une particule en utilisant des géométries complexes et en variant les tensions électriques lors de la simulation. Ce modèle est ensuite validé en le comparant à des relevés expérimentaux. Finalement, une loi de commande, basée sur la commande prédictive généralisée (GPC) est proposée dans le but de contrôler la trajectoire, en profitant de la grande dynamique du déplacement de la particule, et ce malgré les non-linéarités. Cette loi de commande a été validée par des résultats de simulations et une comparaison avec une loi de commande classique. / Micro and nano-particles can be trapped by a non uniform electric field through the effect of dielectrophoretic (DEP) principle. Dielectrophoresis is used to separate, manipulate and detect micro particles in several domains, such as in biological or Carbon Nano-Tubes (CNTs) manipulations. To study and simulate a vision based closed loop control law in order to control the trajectory of micro objects using DEP a numeric model is required. Current methods to simulate the trajectory of micro-particles under a DEP force field are based on finite element modeling (FEM) which requires new simulations when one of its parameters, like the electric voltage, is changed, or on analytic equations which is limited to very simple geometries. In the first section of this manuscript, we propose a hybrid method between analytic and numeric calculation able to simulate complex geometries and to easily change electrode voltage along the trajectory. This numeric model is, then, validated by comparing it with several experimental results. Finally, a control strategy based on the generalized predictive control method is proposed with the aim of controlling the trajectory, taking advantage of the high dynamics despite the non linearity. This control law has been validated by simulation and compared to classical control strategy.

Modern power networks are being driven ever closer to both their physical and operational limits. As a result, control systems are being increasingly relied on to assure satisfactory system performance. Power system stabilizers (PSSs) are one example of such controllers. Their purpose is to increase system damping and they are typically designed using a model of the network that is valid during nominal operating conditions. The limitation of this design approach is that during off-nominal operating conditions, such as those triggered by daily load fluctuations, performance of the controller can degrade. The research presented in this report attempts to evaluate the possibility of employing an adaptive PSS as a means of avoiding the performance degradation precipitated by off-nominal operation. Conceptually, an adaptive PSS would be capable of identifying changes in the network and then adjusting its parameters to ensure suitable damping of the identified network. This work begins with a detailed look at the identification algorithm employed followed by a similarly detailed examination of the control algorithm that was used. The results of these two investigations are then combined to allow for a preliminary assessment of the performance that could be expected from an adaptive PSS. The results of this research suggest that an adaptive PSS is a possibility but further work is needed to confirm this finding. Testing using more complex network models must be carried out, details pertaining to control parameter tuning must be resolved and closed-loop time domain simulations using the adaptive PSS design remain to be performed. / May 2007

This thesis proposes an adaptive control approach to regulate the hydrogen feed of a fuel cell. The goal of the controller is to maintain the so-called hydrogen excess ratio, defined as the ratio between the hydrogen fed to the cell stake and those consumed in the stake, at a desired level when the fuel cell is under load variation. Maintaining the hydrogen excess ratio at an appropriate level would avoid hydrogen starvation, which is crucial for slowing degeneration of the fuel cell membranes and prolonging the life of the cell stake. The control approach we propose is based on the receding horizon linear quadratic optimal control algorithm with an on-line turning scheme which updates the plant model according to real-time measurement. To ease the computational complexity and make real-time turning realizable, we adopt a simple autoregressive with external disturbance (ARX) model to approximate the complicate chemical/electrical process of the fuel cell. The proposed adaptive control approach is implemented on an experimental platform. The experimental results show that the proposed control works with reasonably good performance.

No description available.

Modern power networks are being driven ever closer to both their physical and operational limits. As a result, control systems are being increasingly relied on to assure satisfactory system performance. Power system stabilizers (PSSs) are one example of such controllers. Their purpose is to increase system damping and they are typically designed using a model of the network that is valid during nominal operating conditions. The limitation of this design approach is that during off-nominal operating conditions, such as those triggered by daily load fluctuations, performance of the controller can degrade. The research presented in this report attempts to evaluate the possibility of employing an adaptive PSS as a means of avoiding the performance degradation precipitated by off-nominal operation. Conceptually, an adaptive PSS would be capable of identifying changes in the network and then adjusting its parameters to ensure suitable damping of the identified network. This work begins with a detailed look at the identification algorithm employed followed by a similarly detailed examination of the control algorithm that was used. The results of these two investigations are then combined to allow for a preliminary assessment of the performance that could be expected from an adaptive PSS. The results of this research suggest that an adaptive PSS is a possibility but further work is needed to confirm this finding. Testing using more complex network models must be carried out, details pertaining to control parameter tuning must be resolved and closed-loop time domain simulations using the adaptive PSS design remain to be performed.

Modern power networks are being driven ever closer to both their physical and operational limits. As a result, control systems are being increasingly relied on to assure satisfactory system performance. Power system stabilizers (PSSs) are one example of such controllers. Their purpose is to increase system damping and they are typically designed using a model of the network that is valid during nominal operating conditions. The limitation of this design approach is that during off-nominal operating conditions, such as those triggered by daily load fluctuations, performance of the controller can degrade. The research presented in this report attempts to evaluate the possibility of employing an adaptive PSS as a means of avoiding the performance degradation precipitated by off-nominal operation. Conceptually, an adaptive PSS would be capable of identifying changes in the network and then adjusting its parameters to ensure suitable damping of the identified network. This work begins with a detailed look at the identification algorithm employed followed by a similarly detailed examination of the control algorithm that was used. The results of these two investigations are then combined to allow for a preliminary assessment of the performance that could be expected from an adaptive PSS. The results of this research suggest that an adaptive PSS is a possibility but further work is needed to confirm this finding. Testing using more complex network models must be carried out, details pertaining to control parameter tuning must be resolved and closed-loop time domain simulations using the adaptive PSS design remain to be performed.

A method to adapt the Generalized Predictive Control parameters to improve broadband disturbance rejection was developed and tested. The effect of the parameters on disturbance rejection has previously been poorly understood and a trial and error method was used to achieve adequate results. This dissertation provides insight on the effect of the parameters, as well as an adaptive tuning method to adjust them. The study begins by showing the effect of the four GPC parameters, the control and prediction horizons, control weighting &lambda , and order, on the disturbance rejection and control effort of a vibrating plate. It is shown that the effect of increases in the control and prediction horizon becomes negligible after a certain point. This occurs at nearly the same point for a variety of &lambda 's and orders, and hence they can be eliminated from the tuning space. The control effort and closed-loop disturbance rejection are shown to be highly dependant on &lambda and order, thereby becoming the parameters that need to be tuned. The behavior is categorized into various groups and further investigated. The pole and zero locations of the closed-loop system are examined to reveal how GPC gains control and how it can fail for non-minimum phase plants. A set of fuzzy logic modules is developed to adapt &lambda with order fixed, and conversely to adapt order with &lambda fixed. The effectiveness of the method is demonstrated in both numerical simulations and laboratory experiments. / Ph. D.

CoordenaÃÃo de AperfeÃoamento de Pessoal de NÃvel Superior / O Motor de RelutÃncia VariÃvel (MRV) vem cada vez mais chamando a atenÃÃo da indÃstria e da comunidade acadÃmica. Isso se deve ao crescente desenvolvimento da eletrÃnica de potÃncia e na Ãrea de microprocessadores nos Ãltimos anos, o que permitiu o avanÃo de outros sistemas de acionamentos tais como com MRV. A competitividade do MRV se justifica por seu baixo custo de produÃÃo e manutenÃÃo, uma elevada densidade de potÃncia, robustez e resistÃncia a faltas. O presente trabalho propÃe um esquema de controle robusto baseado em um Controlador Preditivo Generalizado (GPC) pertencente a famÃlia de Controladores Preditivos Baseados em Modelo (MPC) aplicados a malha de corrente e velocidade de um sistema de acionamento com MRV. O controlador proposto, assim como controladores tradicionais aplicados neste tipo de sistema tais como o controlador por Histerese e o controlador PID sÃo tambÃm aplicados com o objetivo de proporcionar meios de comparaÃÃo dos resultados experimentais obtidos. A estrutura do controlador à baseada no projeto de um filtro de modo a permitir uma resposta rÃpida, rejeiÃÃo a distÃrbios, atenuaÃÃo de ruÃdos e robustez com um baixo custo computacional. O controlador proposto foi implementado e os resultados comparados com controladores tradicionais e analisados quantitativamente por meio de Ãndices de desempenho. Para execuÃÃo das rotinas de controle foi utilizado um DSP das Texas Instruments (TMS320F28335), sendo suas caracterÃsticas principais apontadas. O algoritmo do software de controle à esquematizado. O trabalho fez uso da bancada de pesquisa em MRV do laboratÃrio do Grupo de Pesquisa em AutomaÃÃo e RobÃtica (GPAR) da Universidade Federal do Cearà (UFC).