A novel structural health assessment (SHA) technique is proposed. It is a finite element-based time domain nonlinear system identification technique. The procedure is developed in two stages to incorporate several desirable features and increase its implementation potential. First, a weighted global iteration with an objective function is introduced in the unscented Kalman filter (UKF) procedure in order to obtain stable, convergent, and optimal solution. Furthermore, it also improves the capability of the UKF procedure to identify a large structural system using only a short duration of responses measured at a limited number of dynamic degrees of freedom (DDOFs). The combined procedure is denoted as unscented Kalman filter with weighted global iteration (UKF-WGI). Then, UKF-WGI is integrated with iterative least-squares with unknown input (ILS-UI) in order to increase its implementation potential. The substructure concept is also incorporated in the procedure. The integrated procedure is denoted as unscented Kalman filter with unknown input and weighted global iteration (UKF-UI-WGI). The two most important features of the method are that it does not need information on input excitation and uses only limited number of noise-contaminated response information to identify structural systems. Also, the method is able to identify the defects at the local element level by tracking the changes in the stiffness of the structural elements in the finite element representation. The UKF-UI-WGI procedure is implemented in two stages. In Stage 1, based on the location of input excitation, the substructure is selected. Using only responses at all DDOFs in the substructure, ILS-UI can identify the input excitation time-histories, stiffness parameters of all the elements in the substructure, and two Rayleigh damping coefficients. The outcomes of the first stage are necessary to initiate UKF-WGI. Using the information from Stage 1, the stiffness parameters of all the elements in the structure are identified using UKF-WGI in Stage 2. To demonstrate the effectiveness of the procedure, health assessment of relatively large structural systems is presented. Small and relatively large defects are introduced at different locations in the structure and the capability of the method to detect the health of the structure is examined. The optimum number and location of measured responses are also investigated. It is demonstrated that the method is capable of identifying defect-free and defective states of the structures using minimum information. Furthermore, it can locate defect spot within a defective element accurately. The comparative studies are also conducted between the proposed methods and available methods in the literature. First, it is between the UKF-WGI and extended Kalman filter with weighted global iteration (EKF-WGI) procedure. Then, it is between UKF-UI-WGI and generalized iterative least-squares extended Kalman filter with unknown input (GILS-EKF-UI) procedure, developed earlier by the research team. It is demonstrated that the proposed UKF-based procedures are superior to the EKF-based procedures for SHA.

Networked control systems (NCSs) present many advantages such as easy installation and maintenance, flexible layouts and structures of components, and efficient allocation and distribution of resources. Consequently, they find potential applications in a variety of emerging industrial systems including multi-agent systems, power grids, tele-operations and cyber-physical systems. The study of NCSs with nonlinear dynamics (i.e., nonlinear NCSs) is a very significant yet challenging topic, and it not only widens application areas of NCSs in practice, but also extends the theoretical framework of NCSs with linear dynamics (i.e., linear NCSs). Numerous issues are required to be resolved towards a fully-fledged theory of industrial nonlinear NCS design. In this dissertation, three important problems of nonlinear NCSs are investigated: The robust filtering problem, the robust model predictive control (MPC) problem and the robust distributed MPC problem of large-scale nonlinear systems. In the robust filtering problem of nonlinear NCSs, the nonlinear system model is subject to uncertainties and external disturbances, and the measurements suffer from time delays governed by a Markov process. Utilizing the Lyapunov theory, the algebraic Hamilton-Jacobi inequality (HJI)-based sufficient conditions are established for designing the H_infty nonlinear filter. Moreover, the developed results are specialized for a special type of nonlinear systems, by presenting the HJI in terms of matrix inequalities. For the robust MPC problem of NCSs, three aspects are considered. Firstly, to reduce the computation and communication load, the networked MPC scheme with an efficient transmission and compensation strategy is proposed, for constrained nonlinear NCSs with disturbances and two-channel packet dropouts. A novel Lyapunov function is constructed to ensure the input-to-state practical stability (ISpS) of the closed-loop system. Secondly, to improve robustness, a networked min-max MPC scheme are developed, for constrained nonlinear NCSs subject to external disturbances, input and state constraints, and network-induced constraints. The ISpS of the resulting nonlinear NCS is established by constructing a new Lyapunov function. Finally, to deal with the issue of unavailability of system state, a robust output feedback MPC scheme is designed for constrained linear systems subject to periodical measurement losses and external disturbances. The rigorous feasibility and stability conditions are established. For the robust distributed MPC problem of large-scale nonlinear systems, three steps are taken to conduct the studies. In the first step, the issue of external disturbances is addressed. A robustness constraint is proposed to handle the external disturbances, based on which a novel robust distributed MPC algorithm is designed. The conditions for guaranteeing feasibility and stability are established, respectively. In the second step, the issue of communication delays are dealt with. By designing the waiting mechanism, a distributed MPC scheme is proposed, and the feasibility and stability conditions are established. In the third step, the robust distributed MPC problem for large-scale nonlinear systems subject to control input constraints, communication delays and external disturbances are studied. A dual-mode robust distributed MPC strategy is designed to deal with the communication delays and the external disturbances simultaneously, and the feasibility and the stability conditions are developed, accordingly. / Graduate / 0548 / 0544

MATTOS, C. L. C. Recurrent gaussian processes and robust dynamical modeling. 2017. 189 f. Tese (Doutorado em Engenharia de Teleinformática)–Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2017. / Submitted by Renato Vasconcelos (ppgeti@ufc.br) on 2017-09-09T02:26:38Z No. of bitstreams: 1 2017_tes_clcmattos.pdf: 5961013 bytes, checksum: fc44d8b852e28fa0e1ebe0c87389c0da (MD5) / Rejected by Marlene Sousa (mmarlene@ufc.br), reason: Prezado César; Prezado Pedro: Existe uma orientação para que normalizemos as dissertações e teses da UFC, em suas paginas pré-textuais e lista de referencias, pelas regras da ABNT. Por esse motivo, sugerimos consultar o modelo de template, para ajudá-lo nesta tarefa, disponível em: http://www.biblioteca.ufc.br/educacao-de-usuarios/templates/ Vamos agora as correções sempre de acordo com o template: 1. A partir da folha de aprovação as informações devem ser em língua inglesa. 2. A dedicatória deve ter a distancia até o final da folha observado. 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No. of bitstreams: 1 2017_tes_clcmattos.pdf: 6102699 bytes, checksum: 0a85b8841d77f0685b1153ee8ede0d85 (MD5) Previous issue date: 2017-08-25 / The study of dynamical systems is widespread across several areas of knowledge. Sequential data is generated constantly by different phenomena, most of them we cannot explain by equations derived from known physical laws and structures. In such context, this thesis aims to tackle the task of nonlinear system identification, which builds models directly from sequential measurements. More specifically, we approach challenging scenarios, such as learning temporal relations from noisy data, data containing discrepant values (outliers) and large datasets. In the interface between statistics, computer science, data analysis and engineering lies the machine learning community, which brings powerful tools to find patterns from data and make predictions. In that sense, we follow methods based on Gaussian Processes (GP), a principled, practical, probabilistic approach to learning in kernel machines. We aim to exploit recent advances in general GP modeling to bring new contributions to the dynamical modeling exercise. Thus, we propose the novel family of Recurrent Gaussian Processes (RGPs) models and extend their concept to handle outlier-robust requirements and scalable stochastic learning. The hierarchical latent (non-observed) structure of those models impose intractabilities in the form of non-analytical expressions, which are handled with the derivation of new variational algorithms to perform approximate deterministic inference as an optimization problem. The presented solutions enable uncertainty propagation on both training and testing, with focus on free simulation. We comprehensively evaluate the proposed methods with both artificial and real system identification benchmarks, as well as other related dynamical settings. The obtained results indicate that the proposed approaches are competitive when compared to the state of the art in the aforementioned complicated setups and that GP-based dynamical modeling is a promising area of research. / O estudo dos sistemas dinâmicos encontra-se disseminado em várias áreas do conhecimento. Dados sequenciais são gerados constantemente por diversos fenômenos, a maioria deles não passíveis de serem explicados por equações derivadas de leis físicas e estruturas conhecidas. Nesse contexto, esta tese tem como objetivo abordar a tarefa de identificação de sistemas não lineares, por meio da qual são obtidos modelos diretamente a partir de observações sequenciais. Mais especificamente, nós abordamos cenários desafiadores, tais como o aprendizado de relações temporais a partir de dados ruidosos, dados contendo valores discrepantes (outliers) e grandes conjuntos de dados. Na interface entre estatísticas, ciência da computação, análise de dados e engenharia encontra-se a comunidade de aprendizagem de máquina, que fornece ferramentas poderosas para encontrar padrões a partir de dados e fazer previsões. Nesse sentido, seguimos métodos baseados em Processos Gaussianos (PGs), uma abordagem probabilística prática para a aprendizagem de máquinas de kernel. A partir de avanços recentes em modelagem geral baseada em PGs, introduzimos novas contribuições para o exercício de modelagem dinâmica. Desse modo, propomos a nova família de modelos de Processos Gaussianos Recorrentes (RGPs, da sigla em inglês) e estendemos seu conceito para lidar com requisitos de robustez a outliers e aprendizagem estocástica escalável. A estrutura hierárquica e latente (não-observada) desses modelos impõe expressões não- analíticas, que são resolvidas com a derivação de novos algoritmos variacionais para realizar inferência determinista aproximada como um problema de otimização. As soluções apresentadas permitem a propagação da incerteza tanto no treinamento quanto no teste, com foco em realizar simulação livre. Nós avaliamos em detalhe os métodos propostos com benchmarks artificiais e reais da área de identificação de sistemas, assim como outras tarefas envolvendo dados dinâmicos. Os resultados obtidos indicam que nossas propostas são competitivas quando comparadas ao estado da arte, mesmo nos cenários que apresentam as complicações supracitadas, e que a modelagem dinâmica baseada em PGs é uma área de pesquisa promissora.

Este trabalho tem o intuito, de apresentar alguns conceitos, relativos à identifi cação de sistemás, tanto lineares quanto não linearep, além da ideia de referência virtual para, em conjunto com a teoria de projeto "de controladores baseados em dados, propor uma forrha de projeto de controladores não lineares baseados em identificação de sistemas. A utilização de referência virtual para a obtenção dos sinais necessários para a caracterização do controlador ótimo de um sistema e utilizado no método VRFT (Virtual Reference Feedback Tuning). Este método serve como base para o desenvolvimento da proposta deste trabalho que, em conjunto com a teoria de identificação de sistemas não lineares, permite a obteriçãci do controlador ótimo que leva o sistema a se comportar como especificado em malha fechada. Em especial optou-se pela caracterização do controlador utilizando estrutura de modelos racional, por esta ser uma classe bastante abrangente no que - diz respeito à quantidade de sistemas reais que ela é capaz de descrever. Fara demonstrar o potencial do método proposto para projeto de controladores, são apresentados ecemplos ilustrativos em situações onde o controlador ideal consegue ser representado pela classe de modelos, e quando isso não é possível. / This work aims to present some concepts related to linear and nonlinear system identification, as well as the •concept of virtual reference that, together with data based controller design's theory, provides design framework for nonlinear controllers. The Virtual Reference Feedback Tuning method (VRFT) is used as a basis for the current proposal, where we propose to unite nonlinear system identification algorithms and virtual reference to obtain the ideal controller: the one which makes the system behave as desired in closed loop. It was choosen to model the controller as a rational model due the wide variety of practical systems that can be represented by this model structure. For rational system identification we used an iterative algorithm which, based on the signal from input and output of the pIant, allows to identify the parameters of the pre defined controller structure with the signals obtained by virtual reference. To demonstrate the operation of the proposed identification controller methodology, illustrative examples are presented in situations where the ideal controller can be represented by the class of modeIs, and also when it is not possible.

Submitted by DIOGO BATISTA FERNANDES null (engenheiromecanicodiogofernandes@hotmail.com) on 2016-08-04T19:52:54Z No. of bitstreams: 1 Diogo Batista Fernandes.pdf: 2792299 bytes, checksum: 5116207f259278f6ab47f3ab60f0c3e3 (MD5) / Approved for entry into archive by Ana Paula Grisoto (grisotoana@reitoria.unesp.br) on 2016-08-09T14:25:45Z (GMT) No. of bitstreams: 1 fernandes_db_me_ilha.pdf: 2792299 bytes, checksum: 5116207f259278f6ab47f3ab60f0c3e3 (MD5) / Made available in DSpace on 2016-08-09T14:25:45Z (GMT). No. of bitstreams: 1 fernandes_db_me_ilha.pdf: 2792299 bytes, checksum: 5116207f259278f6ab47f3ab60f0c3e3 (MD5) Previous issue date: 2016-07-08 / Uma das formas de eliminar as vibrações excessivas em uma estrutura é através de um controle passivo com o uso de amortecedores de massas sintonizados (AMS), ou também denominados, absorvedores dinâmicos. Um sistema passivo típico não tem suas propriedades mecânicas modificadas, em função da excitação de entrada. O sistema passivo utiliza o movimento da estrutura para produzir um movimento relativo nos dispositivos de amortecimento, pelo qual a energia é dissipada. Neste trabalho, destaca-se que o dispositivo considerado apresenta dependência cúbica do deslocamento proporcional à sua rigidez. O problema é modelado através de equações diferenciais ordinárias não lineares que são linearizadas em torno de seu ponto de equilíbrio. Mediante simulação numérica, utilizando o software Octave, demonstra-se a eficiência de um AMS aplicado a uma estrutura sob influência de oscilações sísmicas inseridas através do modelo de Kanai-Tajimi, que simulam uma situação real, em que as propriedades de solos são introduzidas. Estas oscilações promovem alterações nas propriedades dinâmicas, causando assim uma instabilidade na estrutura, em que foram utilizados parâmetros para encontrar o comportamento caótico no sistema. Como forma de minimizar as vibrações causadas pela excitação sísmica foi proposto um controle híbrido estrutural. Basicamente o controle estrutural se dá pela adição de dispositivos e/ou forças externas que promovem alterações nas propriedades de rigidez e amortecimento da estrutura. Com o objetivo de minimizar as vibrações e reduzir o movimento caótico do sistema a um ponto estável, foi empregada a técnica de controle semiativo com o amortecedor magneto reológico acoplado ao AMS. Comprovou-se que a estratégia de controle híbrido adotado demonstra eficiência para este tipo de situação e pode ser utilizada como forma de auxiliar na atenuação de danos provocados à estruturas, evitando prejuízos econômicos, perdas biológicas e materiais. / One of the ways to eliminate excessive vibrations in a structure is through a passive control with the use of shock absorbers tuned mass (ATM) or also called, dynamic absorbers. A typical passive system does not have its mechanical properties modified in function of an excitation input. The passive system uses the movement of the structure to produce a relative movement in the absorbers device, where by the energy is dissipated. In this work, it is noteworthy that the considered device introduces a cubic dependence of the proportional displacement to its rigidity. The problem is modeled through out nonlinear ordinary differential equations that are linearized around their equilibrium point. By numerical simulations, using Octave software, it demonstrates the efficiency of a ATM applied to a structure under the influence of seismic oscillations inserted over Kanai-Tajimi’s model, that simulates a real situation in which the properties of the soils are introduced. These oscillations promote changes in the dynamic properties, thus causing an instability in the structure where there were used parameters to find chaotic behavior in the system. In order to minimize the vibrations caused by seismic excitation it is proposed a hybrid structural control. Basically structural control takes place by addition devices and/or external forces that promote alterations in the stiffness properties and the structure absorber. For minimize vibrations and reduce the chaotic motion of the system to a stable point, it was used a technique of semiactive control, the magneto rheological absorber coupled to the ATM. It has been shown that the strategy of hybrid control adopted demonstrates efficiency for this kind of situation and can be used as a way in attenuating damage caused for the structures, avoiding economic, biological and material losses.

Orientador: Fábio Roberto Chavarette / Resumo: Uma das formas de eliminar as vibrações excessivas em uma estrutura é através de um controle passivo com o uso de amortecedores de massas sintonizados (AMS), ou também denominados, absorvedores dinâmicos. Um sistema passivo típico não tem suas propriedades mecânicas modificadas, em função da excitação de entrada. O sistema passivo utiliza o movimento da estrutura para produzir um movimento relativo nos dispositivos de amortecimento, pelo qual a energia é dissipada. Neste trabalho, destaca-se que o dispositivo considerado apresenta dependência cúbica do deslocamento proporcional à sua rigidez. O problema é modelado através de equações diferenciais ordinárias não lineares que são linearizadas em torno de seu ponto de equilíbrio. Mediante simulação numérica, utilizando o software Octave, demonstra-se a eficiência de um AMS aplicado a uma estrutura sob influência de oscilações sísmicas inseridas através do modelo de Kanai-Tajimi, que simulam uma situação real, em que as propriedades de solos são introduzidas. Estas oscilações promovem alterações nas propriedades dinâmicas, causando assim uma instabilidade na estrutura, em que foram utilizados parâmetros para encontrar o comportamento caótico no sistema. Como forma de minimizar as vibrações causadas pela excitação sísmica foi proposto um controle híbrido estrutural. Basicamente o controle estrutural se dá pela adição de dispositivos e/ou forças externas que promovem alterações nas propriedades de rigidez e amortecimento da estrutu... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: One of the ways to eliminate excessive vibrations in a structure is through a passive control with the use of shock absorbers tuned mass (ATM) or also called, dynamic absorbers. A typical passive system does not have its mechanical properties modified in function of an excitation input. The passive system uses the movement of the structure to produce a relative movement in the absorbers device, where by the energy is dissipated. In this work, it is noteworthy that the considered device introduces a cubic dependence of the proportional displacement to its rigidity. The problem is modeled through out nonlinear ordinary differential equations that are linearized around their equilibrium point. By numerical simulations, using Octave software, it demonstrates the efficiency of a ATM applied to a structure under the influence of seismic oscillations inserted over Kanai-Tajimi’s model, that simulates a real situation in which the properties of the soils are introduced. These oscillations promote changes in the dynamic properties, thus causing an instability in the structure where there were used parameters to find chaotic behavior in the system. In order to minimize the vibrations caused by seismic excitation it is proposed a hybrid structural control. Basically structural control takes place by addition devices and/or external forces that promote alterations in the stiffness properties and the structure absorber. For minimize vibrations and reduce the chaotic motion of the system t... (Complete abstract click electronic access below) / Mestre

Este trabalho tem o intuito, de apresentar alguns conceitos, relativos à identifi cação de sistemás, tanto lineares quanto não linearep, além da ideia de referência virtual para, em conjunto com a teoria de projeto "de controladores baseados em dados, propor uma forrha de projeto de controladores não lineares baseados em identificação de sistemas. A utilização de referência virtual para a obtenção dos sinais necessários para a caracterização do controlador ótimo de um sistema e utilizado no método VRFT (Virtual Reference Feedback Tuning). Este método serve como base para o desenvolvimento da proposta deste trabalho que, em conjunto com a teoria de identificação de sistemas não lineares, permite a obteriçãci do controlador ótimo que leva o sistema a se comportar como especificado em malha fechada. Em especial optou-se pela caracterização do controlador utilizando estrutura de modelos racional, por esta ser uma classe bastante abrangente no que - diz respeito à quantidade de sistemas reais que ela é capaz de descrever. Fara demonstrar o potencial do método proposto para projeto de controladores, são apresentados ecemplos ilustrativos em situações onde o controlador ideal consegue ser representado pela classe de modelos, e quando isso não é possível. / This work aims to present some concepts related to linear and nonlinear system identification, as well as the •concept of virtual reference that, together with data based controller design's theory, provides design framework for nonlinear controllers. The Virtual Reference Feedback Tuning method (VRFT) is used as a basis for the current proposal, where we propose to unite nonlinear system identification algorithms and virtual reference to obtain the ideal controller: the one which makes the system behave as desired in closed loop. It was choosen to model the controller as a rational model due the wide variety of practical systems that can be represented by this model structure. For rational system identification we used an iterative algorithm which, based on the signal from input and output of the pIant, allows to identify the parameters of the pre defined controller structure with the signals obtained by virtual reference. To demonstrate the operation of the proposed identification controller methodology, illustrative examples are presented in situations where the ideal controller can be represented by the class of modeIs, and also when it is not possible.

Ce rapport porte sur le sujet de recherche de l'identification boîte noire du système non linéaire. En effet, parmi toutes les techniques nombreuses et variées développées dans ce domaine de la recherche ces dernières décennies, il semble toujours intéressant d'étudier l'approche réseau de neurones dans l'estimation de modèle de système complexe. Même si des modèles précis ont été obtenus, les principaux inconvénients de ces techniques restent le grand nombre de paramètres nécessaires et, en conséquence, le coût important de calcul nécessaire pour obtenir le niveau de pratique de la précision du modèle désiré. Par conséquent, motivés pour remédier à ces inconvénients, nous avons atteint une méthodologie complète et efficace du système d'identification offrant une précision équilibrée, la complexité et les modèles de coûts en proposant, d'une part, de nouvelles structures de réseaux de neurones particulièrement adapté à une utilisation très large en matière de modélisation système pratique non linéaire, d'autre part, un simple et efficace technique de réduction de modèle, et, troisièmement, une procédure de réduction de coût de calcul. Il est important de noter que ces deux dernières techniques de réduction peut être appliquée à une très large gamme d'architectures de réseaux de neurones sous deux simples hypothèses spécifiques qui ne sont pas du tout contraignant. Enfin, la dernière contribution importante de ce travail est d'avoir montré que cette phase d'estimation peut être obtenue dans un cadre robuste si la qualité des données d'identification qu'il oblige. Afin de valider la procédure d'identification système proposé, des exemples d'applications entraînées en simulation et sur un procédé réel, de manière satisfaisante validé toutes les contributions de cette thèse, confirmant tout l'intérêt de ce travail. / This report concerns the research topic of black box nonlinear system identification. In effect, among all the various and numerous techniques developed in this field of research these last decades, it seems still interesting to investigate the neural network approach in complex system model estimation. Even if accurate models have been derived, the main drawbacks of these techniques remain the large number of parameters required and, as a consequence, the important computational cost necessary to obtain the convenient level of the model accuracy desired. Hence, motivated to address these drawbacks, we achieved a complete and efficient system identification methodology providing balanced accuracy, complexity and cost models by proposing, firstly, new neural network structures particularly adapted to a very wide use in practical nonlinear system modeling, secondly, a simple and efficient model reduction technique, and, thirdly, a computational cost reduction procedure. It is important to notice that these last two reduction techniques can be applied to a very large range of neural network architectures under two simple specific assumptions which are not at all restricting. Finally, the last important contribution of this work is to have shown that this estimation phase can be achieved in a robust framework if the quality of identification data compels it. In order to validate the proposed system identification procedure, application examples driven in simulation and on a real process, satisfactorily validated all the contributions of this thesis, confirming all the interest of this work.

No / Extrusion is one of the major methods for processing polymeric materials and the thermal homogeneity of the process output is a major concern for manufacture of high quality extruded products. Therefore, accurate process thermal monitoring and control are important for product quality control. However, most industrial extruders use single point thermocouples for the temperature monitoring/control although their measurements are highly affected by the barrel metal wall temperature. Currently, no industrially established thermal profile measurement technique is available. Furthermore, it has been shown that the melt temperature changes considerably with the die radial position and hence point/bulk measurements are not sufficient for monitoring and control of the temperature across the melt flow. The majority of process thermal control methods are based on linear models which are not capable of dealing with process nonlinearities. In this work, the die melt temperature profile of a single screw extruder was monitored by a thermocouple mesh technique. The data obtained was used to develop a novel approach of modelling the extruder die melt temperature profile under dynamic conditions (i.e. for predicting the die melt temperature profile in real-time). These newly proposed models were in good agreement with the measured unseen data. They were then used to explore the effects of process settings, material and screw geometry on the die melt temperature profile. The results showed that the process thermal homogeneity was affected in a complex manner by changing the process settings, screw geometry and material. (C) 2013 Elsevier Inc. All rights reserved.

Dans cette thèse, nous nous intéressons aux équations aux dérivées fractionnaires et leurs applications au traitement d'images. Une attention particulière a été apportée à un système non linéaire d'équations différentielles fractionnaires. En particulier, nous avons étudié les propriétés qualitatives des solutions d'un système non linéaire d'équations différentielles fractionnaires qui explosent en temps fini. L'existence des solutions locales pour le système, le profil des solutions qui explosent en temps fini sont présentés. Nous étudierons le problème inverse pour l'équation de diffusion linéaire en une dimension et en deux dimensions. Nous sommes intéressés par trouver un terme source inconnu d'une équation de diffusion non locale. Les conditions aux limites considérées sont non locales et le problème spectral est non auto-adjoint. L'existence et l'unicité de la solution du problème inverse sont présentées.D'autre part, nous proposons un modèle basé sur l'équation de la chaleur linéaire avec une dérivée fractionnaire en temps pour le débruitage d'images numériques. L'approche utilise une technique de pixel par pixel, ce qui détermine la nature du filtre. En contraste avec certain modèles basés sur les équations aux dérivées partielles pour le débruitage de l'image, le modèle proposé est bien posé et le schéma numérique est convergent. Une amélioration de notre modèle proposé est suggéré. / In this thesis we study a nonlinear system of fractional differential equations with power nonlinearities; the solution of the system blows up in a finite time. We provide the profile of the blowing-up solutions of the system by finding upper and lower estimates of the solution. Moreover, bilateral bounds on the blow-up time are given.We consider the inverse problem concerning a linear time fractional diffusion equation for the determination of the source term (supposed to be independent of the time variable) and temperature distribution from initial and final temperature data. The uniqueness and existence of the continuous solution of the inverse problem is proved. We also consider the inverse source problem for a two dimensional fractional diffusion equation. The results about the existence, uniqueness and continuous dependence of the solution of the inverse problem on the data are presented.We apply the linear heat equation involving a fractional derivative in time for denoising (simplification, smoothing, restoration or enhancement) of digital images. The order of the fractional derivative has been used for controling the diffusion process, which in result preserves the fine structures in the image during denoising process. Furthermore, an improvement in the proposed model is suggested by using the structure tensor of the images.