Le processus de développement des systèmes avioniques suit des réglementations de sûreté de fonctionnement très strictes, incluant l'analyse du déterminisme et de la prédictibilité temporelle des systèmes. L'approche est basée sur la séparation des étapes de conception et d'implémentation. Une des plus grandes difficultés dans l'approche actuelle se trouve dans la détermination du WCET, qui est nécessaire pour prouver la satisfaction des contraintes de temps-réel dur du système. Dans cette thèse, une méthodologie de relâchement de contraintes temps-réels pour les systèmes de commandes digital est proposé. L'objectif est de réduire le conservatisme des approches traditionnelles basés sur le pire temps d'exécution, tout en préservant la stabilité et les performances de commandes. L'approche a été appliqué au système de commande de tangage d'un avion, ce qui a permi de montrer que le relâchement des contraintes temps réels améliore l'utilisation de la puissance de calcul disponible tout en préservant la stabilité et la qualité de commande du système. / The development process of critical avionics products are done under strict safety regulations. These regulations include determinism and predictability of the systems' timing. The overall approach is based on a separation of concerns between control design and implementation. One of the toughest challenges in the current approach is the determination of the WCET, in order to correctly size the system. In this thesis, a weakened implementation scheme for real-time feedback controllers is proposed to reduce the conservatism due to traditional worst-case considerations, while preserving the stability and control performance. The methodology is tested to the pitch control of an aircraft, showing that weakening the real-time constraints allows for saving computing power while preserving the system's stability and quality of control.

Orientador: Ricardo Tokio Higuti / Banca: Alexandre César Rodrigues da Silva / Banca: Flávio Buiochi / Resumo: A estimação do tempo de atraso entre dois sinais de ultra-som é uma tarefa muito comum e importante em diversas aplicações, como em sistemas de posicionamento para medição de distâncias, medidores de espessura em ensaios não-destrutivos, células de medição de propriedades de materiais, entre outros. Em algumas aplicações há necessidade de elevada acurácia e precisão na determinação do tempo de atraso, que dependem de diversos parâmetros do transdutor, de sua excitação e do meio em que a onda se propaga, além do método de estimação e representação numérica. Neste trabalho são avaliados três estimadores de tempo de atraso, com implementações em ponto-fixo e ponto-flutuante: correlação cruzada com interpolação parabólica, transformada de Hilbert da correlação e envoltória do sinal analítico. Os estimadores são avaliados em MATLAB, em ponto-flutuante, com sinais sintetizados e com sinais reais obtidos em laboratório, e em ponto-fixo, usando um processador digital de sinais TMS320VC5416, da Texas Instruments. São explorados parâmetros como freqüência central do transdutor, freqüência de amostragem, largura de banda, relação sinal-ruído e atenuação do meio. O desempenho dos métodos é comparado por meio dos erros médios e desvios-padrão das medidas / Abstract: Time-delay estimation between two ultrasonic signals is a very common and important task in several applications, such as distance measurement in positioning systems, thickness measurement in nondestructive testing, measurement cells of materials properties, among others. Some applications require high accuracy and precision on the determination of the time-delay, which depend on several transducer parameters, excitation and medium of propagation, as well as the estimation method and numerical representation. In this work, three time-delay estimators are evaluated, with fixed- and floating-point implementations: cross-correlation with parabolic interpolation, Hilbert transform of correlation and analytic signal envelope. The estimators are evaluated in MATLAB with floating-point representation, using synthesized signals and real signals acquired in laboratory, and in fixed-point using a Texas Instruments TMS320VC5416 digital signal processor. Parameters as transducer central frequency, sampling frequency, bandwidth, signal-to-noise ratio and medium attenuation are considered. The performances of the methods are compared by means of errors (or bias) and standard deviations / Mestre

In this work is presented stochastic model of binaural hearing in context of another alternative models. According to latest experimental data on mammals, inhibition plays a role in interaural time difference recognition, which is a key for low frequency sound source localization. The outputs of experiments may lead to the conclusion that the binaural hearing works differently in mammals compared to birds. Nowadays there are a few theoretical works addressing this new phenomena, but all of them are relaying on a very precise inhibition timing, which was never proved as physiologically valid. On the other hand, models described in this work are based on the fact, that every neuron has a random delay when reacting to an excitation. If this time jitter is taken into account and combined with inhibitory signal, delay in the neuronal circuit and coincidence detection, then the output firing rate corresponds to the azimuth of the sound source. In this work it is shown, that such a neuronal circuits are giving the same output results compared to experimental data. The models are supported by analytical computations and numerical simulations including simulation of cochlear implant.

Made available in DSpace on 2014-06-12T15:58:28Z (GMT). No. of bitstreams: 2 arquivo4572_1.pdf: 1149011 bytes, checksum: 92aae8f6f9b5145bfcecb94d96dbbc0b (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2004 / Instituto Federal de Educação, Ciência e Tecnologia de Pernambuco / Um nariz artificial é um sistema modular composto de duas partes principais: um sistema sensor, formado de elementos que detectam odores e um sistema de reconhecimento de padrões que classifica os odores detectados. Redes neurais artificiais têm sido utilizadas como sistema de reconhecimento de padrões para narizes artificiais e vêm apresentando resultados promissores. Desde os anos 80, pesquisas para criação de narizes artificiais, que permitam detectar e classificar odores, vapores e gases automaticamente, têm tido avanços significativos. Esses equipamentos podem ser utilizados no monitoramento ambiental para controlar a qualidade do ar, na área de saúde para realizar diagnóstico de doenças e nas indústrias de alimentos para o controle de qualidade e o monitoramento de processos de produção. Esta dissertação investiga a utilização de quatro técnicas diferentes de redes neurais para criação de sistemas de reconhecimento de padrões em narizes artificiais. O trabalho está dividido em quatro partes principais: (1) introdução aos narizes artificiais, (2) redes neurais artificiais para sistema de reconhecimento de padrões, (3) métodos para medir o desempenho de sistemas de reconhecimento de padrões e comparar os resultados e (4) estudo de caso. Os dados utilizados para o estudo de caso, foram obtidos por um protótipo de nariz artificial composto por um arranjo de oito sensores de polímeros condutores, expostos a nove tipos diferentes de aguarrás. Foram adotadas as técnicas Multi-Layer Perceptron (MLP), Radial Base Function (RBF), Probabilistic Neural Network (PNN) e Time Delay Neural Network (TDNN) para criar os sistemas de reconhecimento de padrões. A técnica PNN foi investigada em detalhes, por dois motivos principais: esta técnica é indicada para realização de tarefas de classificação e seu treinamento é feito em apenas um passo, o que torna a etapa de criação dessas redes muito rápida. Os resultados foram comparados através dos valores dos erros médios de classificação utilizando o método estatístico de Teste de Hipóteses. As redes PNN correspondem a uma nova abordagem para criação de sistemas de reconhecimento de padrões de odor. Estas redes tiveram um erro médio de classificação de 1.1574% no conjunto de teste. Este foi o menor erro obtido entre todos os sistemas criados, entretanto mesmo com o menor erro médio de classificação, os testes de hipóteses mostraram que os classificadores criados com PNN não eram melhores do que os classificadores criados com a arquitetura RBF, que obtiveram um erro médio de classificação de 1.3889%. A grande vantagem de criar classificadores com a arquitetura PNN foi o pequeno tempo de treinamento dos mesmos, chegando a ser quase imediato. Porém a quantidade de nodos na camada escondida foi muito grande, o que pode ser um problema, caso o sistema criado deva ser utilizado em equipamentos com poucos recursos computacionais. Outra vantagem de criar classificadores com redes PNN é relativa à quantidade reduzida de parâmetros que devem ser analisados, neste caso apenas o parâmetro relativo à largura da função Gaussiana precisou ser investigado

Cette thèse étudie la compensation robuste d'un retard de commande affectant un système dynamique. Pour répondre aux besoins du domaine applicatif du contrôle moteur, nous étudions d'un point de vue théorique des lois de contrôle par prédiction, dans les cas de retards incertains et de retards variables, et présentons des résultats de convergence asymptotique. Dans une première partie, nous proposons une méthodologie générale d'adaptation du retard, à même de traiter également d'autres incertitudes par une analyse de Lyapunov-Krasovskii. Cette analyse est obtenue grâce à une technique d'ajout de dérivateur récemment proposée dans la littérature et exploitant une modélisation du retard sous forme d'une équation à paramètres distribués. Dans une seconde partie, nous établissons des conditions sur les variations admissibles du retard assurant la stabilité du système boucle fermée. Nous nous intéressons tout particulièrement à une famille de retards dépendant de la commande (retard de transport). Des résultats de stabilité inspirés de l'ingalité Halanay sont utilisés pour formuler une condition de petit gain permettant une compensation robuste. Des exemples illustratifs ainsi que des résultats expérimentaux au banc moteur soulignent la compatibilité de ces lois de contrôle avec les impératifs du temps réel ainsi que les mérites de cette approche. / This thesis addresses the general problem of robust compensation of input delays. Motivated by engine applications, we theoretically study prediction-based control laws for uncertain delays and time-varying delays. Results of asymptotic convergence are obtained. In a first part, a general delay-adaptive scheme is proposed to handle uncertainties, through a Lyapunov-Krasovskii analysis induced by a backstepping transformation (applied to a transport equation) recently introduced in the literature.In a second part, conditions to handle delay variability are established. A particular class of input-dependent delay is considered (transport). Halanay-like stability results serve to formulate a small-gain condition guaranteeing robust compensation. Illustrative examples and experimental results obtained on a test bench assess the implementability of the proposed control laws and highlight the merits of the approach.

Dans le domaine de l’ingénierie (par exemple l’aéronautique, l’automobile, la biologie, les circuits), les systèmes dynamiques sont le cadre de base utilisé pour modéliser, contrôler et analyser une grande variété de systèmes et de phénomènes. En raison de l’utilisation croissante de logiciels dédiés de modélisation par ordinateur, la simulation numérique devient de plus en plus utilisée pour simuler un système ou un phénomène complexe et raccourcir le temps de développement et le coût. Cependant, le besoin d’une précision de modèle améliorée conduit inévitablement à un nombre croissant de variables et de ressources à gérer au prix d’un coût numérique élevé. Cette contrepartie justifie la réduction du modèle. Pour les systèmes linéaires invariant dans le temps, plusieurs approches de réduction de modèle ont été effectivement développées depuis les années 60. Parmi celles-ci, les méthodes basées sur l’interpolation se distinguent par leur souplesse et leur faible coût de calcul, ce qui en fait un candidat prédestiné à la réduction de systèmes véritablement à grande échelle. Les progrès récents démontrent des façons de trouver des paramètres de réduction qui minimisent localement la norme H2 de l’erreur d’incompatibilité. En général, une approximation d’ordre réduit est considérée comme un modèle de dimension finie. Cette représentation est assez générale et une large gamme de systèmes dynamiques linéaires peut être convertie sous cette forme, du moins en principe. Cependant, dans certains cas, il peut être plus pertinent de trouver des modèles à ordre réduit ayant des structures plus complexes. A titre d’exemple, certains systèmes de phénomènes de transport ont leurs valeurs singulières Hankel qui se décomposent très lentement et ne sont pas facilement approchées par un modèle de dimension finie. En outre, pour certaines applications, il est intéressant de disposer d’un modèle structuré d’ordre réduit qui reproduit les comportements physiques. C’est pourquoi, dans cette thèse, les modèles à ordre réduit ayant des structures de retard ont été plus précisément considérés. Ce travail a consisté, d’une part, à développer de nouvelles techniques de réduction de modèle pour des modèles à ordre réduit avec des structures de retard et, d’autre part, à trouver de nouvelles applications d’approximation de modèle. La contribution majeure de cette thèse couvre les sujets d’approximation et inclut plusieurs contributions au domaine de la réduction de modèle. Une attention particulière a été accordée au problème de l’approximation du modèle optimale pour les modèles structurés retardés. À cette fin, de nouveaux résultats théoriques et méthodologiques ont été obtenus et appliqués avec succès aux repères académiques et industriels. De plus, la dernière partie de ce manuscrit est consacrée à l’analyse de la stabilité des systèmes retardés par des méthodes interpolatoires. Certaines déclarations théoriques ainsi qu’une heuristique sont développées permettant d’estimer de manière rapide et précise les diagrammes de stabilité de ces systèmes. / In the engineering area (e.g. aerospace, automotive, biology, circuits), dynamical systems are the basic framework used for modeling, controlling and analyzing a large variety of systems and phenomena. Due to the increasing use of dedicated computer-based modeling design software, numerical simulation turns to be more and more used to simulate a complex system or phenomenon and shorten both development time and cost. However, the need of an enhanced model accuracy inevitably leads to an increasing number of variables and resources to manage at the price of a high numerical cost. This counterpart is the justification for model reduction. For linear time-invariant systems, several model reduction approaches have been effectively developed since the 60’s. Among these, interpolation-based methods stand out due to their flexibility and low computational cost, making them a predestined candidate in the reduction of truly large-scale systems. Recent advances demonstrate ways to find reduction parameters that locally minimize the H2 norm of the mismatch error. In general, a reduced-order approximation is considered to be a finite dimensional model. This representation is quite general and a wide range of linear dynamical systems can be converted in this form, at least in principle. However, in some cases, it may be more relevant to find reduced-order models having some more complex structures. As an example, some transport phenomena systems have their Hankel singular values which decay very slowly and are not easily approximated by a finite dimensional model. In addition, for some applications, it is valuable to have a structured reduced-order model which reproduces the physical behaviors. That is why, in this thesis, reduced-order models having delay structures have been more specifically considered. This work has focused, on the one hand, in developing new model reduction techniques for reduced order models having delay structures, and, on the other hand, in finding new applications of model approximation. The major contribution of this thesis covers approximation topics and includes several contributions to the area of model reduction. A special attention was given to the H2 optimal model approximation problem for delayed structured models. For this purpose, some new theoretical and methodological results were derived and successfully applied to both academic and industrial benchmarks. In addition, the last part of this manuscript is dedicated to the analysis of time-delayed systems stability using interpolatory methods. Some theoretical statements as well as an heuristic are developed enabling to estimate in a fast and accurate way the stability charts of those systems.

In recent years, the security of networked control systems (NCSs) has been an important challenge for many researchers. Although the security schemes for networked control systems have advanced in the past several years, there have been many acknowledged cyber attacks. As a result, this dissertation proposes the use of a novel time-delay switch (TDS) attack by introducing time delays into the dynamics of NCSs. Such an attack has devastating effects on NCSs if prevention techniques and countermeasures are not considered in the design of these systems. To overcome the stability issue caused by TDS attacks, this dissertation proposes a new detector to track TDS attacks in real time. This method relies on an estimator that will estimate and track time delays introduced by a hacker. Once a detector obtains the maximum tolerable time delay of a plant’s optimal controller (for which the plant remains secure and stable), it issues an alarm signal and directs the system to its alarm state. In the alarm state, the plant operates under the control of an emergency controller that can be local or networked to the plant and remains in this stable mode until the networked control system state is restored. In another effort, this dissertation evaluates different control methods to find out which one is more stable when under a TDS attack than others. Also, a novel, simple and effective controller is proposed to thwart TDS attacks on the sensing loop (SL). The modified controller controls the system under a TDS attack. Also, the time-delay estimator will track time delays introduced by a hacker using a modified model reference-based control with an indirect supervisor and a modified least mean square (LMS) minimization technique. Furthermore, here, the demonstration proves that the cryptographic solutions are ineffective in the recovery from TDS attacks. A cryptography-free TDS recovery (CF-TDSR) communication protocol enhancement is introduced to leverage the adaptive channel redundancy techniques, along with a novel state estimator to detect and assist in the recovery of the destabilizing effects of TDS attacks. The conclusion shows how the CF-TDSR ensures the control stability of linear time invariant systems.

Since their discovery in 1978 by Hill et al. and the development of the transverse holographic technique for their fabrication by Meltz et al. in 1989, fiber Bragg gratings (FBG) have become an important device for applications in optical communications, optical signal processing and fiber-optical sensors. A superstructured fiber Bragg grating (SFBG), also called a sampled fiber Bragg grating, is a special FBG that consists of a several small FBGs placed in close proximity to one another. SFBGs have attracted much attention in recent years with the discovery of techniques allowing the creation of equivalent chirp or equivalent phase shifts. The biggest advantage of an SFBG with equivalent chirp or equivalent phase shifts is the possibility to design and fabricate gratings with greatly varying phase and amplitude responses by adjusting the spatial profile of the superstructure. The realization of SFBGs with equivalent chirp or equivalent phase shifts requires only sub-millimeter precision. This is a relief from the sub-micron precision required by traditional approaches. In this thesis, the mathematical modeling of FBGs and SFBGs is reviewed. The use of SFBGs for various applications in photonic microwave signal processing is considered. Four main topics are presented in this thesis. The first topic is the use of SFBG as a photonic true-time delay (TTD) beamformer for phased array antennas (PAAs). The second topic addresses non-linearities in the group delay response of an SFBG with equivalent chirp in its sampling period. An SFBG with an equivalent chirp using only a linear chirp coefficient may yield a group delay response that deviates from the linear response required by a TTD beamformer. In the thesis, a technique to improve the linearity of the group delay response is proposed and an adaptive algorithm to find the optimal linear and non-linear chirp coefficients to produce the best linear group delay response is described. Since no closed-form solution exists to represent the amplitude and phase responses of an SFBG, we rely on a Fourier transform analogy under a weak grating approximation as a starting point in the design of an SFBG. Simulations are then used to refine the response of the SFBG. The algorithm proposed provides an optimal set of chirp coefficients that minimizes the error in the group delay response. Four gratings are fabricated using the optimized chirp coefficients and their application in a TTD PAA system is discussed. The third topic discusses the use of an SFBG with equivalent phase shifts in its sampling period as a means to realize optical single sideband (SSB) modulation. SSB modulation eliminates the power penalty caused by chromatic dispersion experienced by an optical signal traveling through a long length of optical fiber. By introducing two π phase shifts through equivalent sampling to the SFBG, two ultra-narrow transmission bands are created in the grating stop band of the +/- 1st spectral orders. In the proposed system, a double-sideband plus carrier (DSB+C) modulated optical signal is sent to the input of an optical SSB filter based on the equivalent phase-shift SFBG in order to select the optical carrier and a single sideband, effectively blocking one sideband from propagating. Finally, the fourth topic focuses on the implementation of a photonic microwave bandpass filter based on an SFBG with equivalent chirp. Photonic microwave filters are used to process microwave signals in the optical domain. By using a technique called phase-modulation to intensity-modulation (PM-IM) conversion, a two-tap delay line filter is created with one negative tap. A single SFBG with a chirp in its sampling period is used as a means to achieve the PM-IM conversion for the two taps. Two phase modulated optical carriers are used to generate the two taps, each entering a different port of the SFBG and thus experiencing an opposite dispersion value. The two optical signals are then recombined before being sent to a photodetector (PD) where the filtered microwave signal is recovered.

This final thesis deals with the approximation of time delay in time invariant systems. First, the generalized Laguerre functions and their characteristics are presented. After this, the approximation of the Dirac delta function with the help of these functions is shown. Also, the choice of the free parameters is discussed and the results are evaluated with the help of energy. In the final part of the thesis, the approximations of systems with generalized and simple Laguerre functions are compared.

Cette thèse porte sur la modélisation et l’analyse de stabilité de certains mécanismes biologiques complexes en rapport avec le cancer. Un intérêt particulier est porté au cas de l’hématopoïèse et de la leucémie aiguë myéloblastique (LAM). Les modèles utilisés et/ou introduits dans cette thèse se décrivent par des équations aux dérivées partielles structurées en âge, qui se réduisent à des systèmes à retards de plusieurs types (retards ponctuels ou distribués, à support fini ou infini). Ces modèles à retards sont parfois couplés à des équations aux différences, et possiblement avec des paramètres variant dans le temps. Un des principaux challenges dans ce travail consiste à développer des méthodes temporelles, qui se basent sur la construction de fonctionnelles de Lyapunov-Krasovskii strictes, pour les systèmes non-linéaires à retards étudiés. Les principales notions abordées dans ces travaux incluent : l’analyse de stabilité/stabilisation et de robustesse, l’emploi de techniques de modélisation des populations cellulaires saines et malades, l’étude de différentes classes de systèmes dynamiques, (possiblement à temps variant ou à commutation), et également l’introduction de quelques outils issus de l’intelligence artificielle (planification et recherche de solution) dans un contexte de modèles biologiques. Ainsi, les méthodes de modélisation et d’analyse employées dans ce travail ont permis d’une part d’étendre les résultats de stabilité de cette classe de systèmes biologiques, et d’autre part de mieux comprendre certains mécanismes biologiques liés au cancer et sa thérapie. Plus précisément, certains concepts récemment établis en biologie et en médecine sont mis en évidence dans ce travail pour la première fois dans cette classe de systèmes, telles que : la dédifférenciation des cellules (plasticité), ou encore la dormance des cellules cancéreuses dans des modèles tenant compte de la cohabitation entre cellules saines et mutées. Les résultats obtenus sont interprétés dans le cas de l’hématopoïèse et de la LAM, mais ce travail s’applique également à d’autres types de tissus où le cycle cellulaire se produit de façon similaire. / Medical research is looking for new combined targeted therapies against cancer. Our research project -which involves intensive collaboration with hematologists from Saint-Antoine Hospital in Paris- is imbued within a similar spirit and fits the expectations of a better understanding of the behavior of blood cell dynamics. In fact, hematopoiesis provides a paradigm for studying all the mammalian stem cells, as well as all the mechanisms involved in the cell cycle. We address multiple issues related to the modeling and analysis of the cell cycle, with particular insights into the hematopoietic systems. Stability features of the models are highlighted, since systems trajectories reflect the most prominent healthy or unhealthy behaviors of the biological process under study. We indeed perform stability analysis of systems describing healthy and unhealthy situations, with a particular interest in the case of acute myeloblastic leukemia (AML). Thus, we pursue the objectives of understanding the interactions between the various parameters and functions involved in the mechanisms of interest. For that purpose, an advanced stability analysis of the cell fate evolution in treated or untreated leukemia is performed in several modeling frameworks, and our study suggests new anti-leukemic combined chemotherapy. Throughout the thesis, we cover many biological evidences that are currently undergoing intensive biological research, such as: cell plasticity, mutations accumulation, cohabitation between ordinary and mutated cells, control or eradication of cancer cells, cancer dormancy, etc.Among the contributions of Part I of the thesis, we can mention the extension of both modeling and analysis aspects in order to take into account a proliferating phase in which most of the cells may divide, or die, while few of them may be arrested during their cycle for unlimited time. We also introduce for the first time cell-plasticity features to the class of systems that we are focusing on.Next, in Part II, stability analyses of some differential-difference cell population models are performed through several time-domain techniques, including tools of Comparative and Positive Systems approaches. Then, a new age-structured model describing the coexistence between cancer and ordinary stem cells is introduced. This model is transformed into a nonlinear time-delay system that describes the dynamics of healthy cells, coupled to a nonlinear differential-difference system governing the dynamics of unhealthy cells. The main features of the coupled system are highlighted and an advanced stability analysis of several coexisting steady states is performed through a Lyapunov-like approach for descriptor-type systems. We pursue an analysis that provides a theoretical treatment framework following different medical orientations, among which: i) the case where therapy aims to eradicate cancer cells while preserving healthy ones, and ii) a less demanding, more realistic, scenario that consists in maintaining healthy and unhealthy cells in a controlled stable dormancy steady-state. Mainly, sufficient conditions for the regional exponential stability, estimate of the decay rate of the solutions, and subsets of the basins of attraction of the steady states of interest are provided. Biological interpretations and therapeutic strategies in light of emerging AML-drugs are discussed according to our findings.Finally, in Part III, an original formulation of what can be interpreted as a stabilization issue of population cell dynamics through artificial intelligence planning tools is provided. In that framework, an optimal solution is discovered via planning and scheduling algorithms. For unhealthy hematopoiesis, we address the treatment issue through multiple drug infusions. In that case, we determine the best therapeutic strategy that restores normal blood count as in an ordinary hematopoietic system.