Este trabalho tem como objetivo principal o desenvolvimento de uma estratégia de integração da otimização com o controle preditivo multivariável em uma camada. Os problemas de controle e otimização econômica são resolvidos simultaneamente em um mesmo algoritmo. A função objetivo econômica foi inserida no controlador na sua forma diferencial, ou seja, o gradiente da função objetivo econômica. O método foi testado por simulação para o caso do sistema reator regenerador da UFCC (Unit of Fluid Catalytic Cracker). Esta dissertação descreve a estratégia de otimização integrada ao controlador preditivo cuja função objetivo incorpora componentes dinâmicos e estáticos. Para a determinação das condições ótimas do processo no estado estacionário do conversor (unidade de craqueamento catalítico) foi utilizado um modelo empírico do processo. A melhor trajetória para conduzir o processo para o seu ponto ótimo de operação, maximizando lucro ou produto de maior valor agregado, desde que não sejam violadas as restrições de processo, é predita utilizando um modelo dinâmico, obtido através de dados de testes em degrau em um modelo rigoroso. Este modelo linear possibilitou a obtenção das funções de transferência do processo e o modelo em variáveis de estado. O ponto ótimo que é obtido na execução deste algoritmo, leva em consideração a não violação das restrições das variáveis manipuladas e controladas do processo, tanto para o estado estacionário como para o transiente do problema. O problema de otimização não linear resultante é resolvido através de uma rotina de programação quadrática da biblioteca do Matlab. Uma segunda alternativa apresentada para a estratégia de otimização deste trabalho, é a inclusão do gradiente reduzido na função objetivo do controlador quando são observadas violações das restrições das variáveis controladas. Os resultados simulados através de um modelo não linear rigoroso (Moro&Odloak,1995) mostram um bom desempenho dos algoritmos aqui desenvolvidos tanto com relação aos benefícios econômicos como na estabilização da unidade. / This dissertation aims to develop a strategy to integrate the optimization problem of the plant into the model predictive controller in a one layer strategy, for the real time optimization or online optimization. The control and the optimization of the process are computed simultaneously in the same algorithm. The gradient of the economic objective function is included in the cost function of the controller instead of in its regular form. Thereby, this work describes a predictive control strategy, which can be classified as a one layer strategy and whose objective function has to be optimized obeying constraints, which incorporates dynamic and static components. The optimal conditions of the process in the steady state are defined through the use of an empirical process model. Furthermore, the best trajectory to be followed in order to reach the optimal conditions, without violating the constraints, maximizing profit or the production of its more valuable product, is predicted through the use of the dynamic model, that can be obtained through a plant step test. As a result transfer function and state space models are obtained. The optimal operation point is achieved through the execution of the proposed algorithm. Therefore, the solution to the optimization/control problem will always be in a feasible region, in other words, without violating the process manipulated or controlled variable constraints for both stationary and transient states of the problem. The non-linear optimization problem resulted from the implementation of the proposed algorithm is solved through the quadratic programming routine from the Matlab library. The second online optimization strategy proposed in this work is one that considers the reduced gradient method algorithm modified to evaluate the predicted trajectory. As a result, any violation of the manipulated or controlled variable constraints is prevented and this variable is not considered in the next step of the calculation of the predicted trajectory or even in the search direction of the optimization. Finally the simulations results obtained through the use of a nonlinear rigorous model (Moro&Odloak,1995) presents good performance for the algorithms here proposed, not only related to economic benefits, but also in order to stabilize the unit.

Neste trabalho foram desenvolvidas duas técnicas de sintonia para controladores preditivos por modelo. Ambas visam minimizar a soma do erro quadrático entre respostas do sistema em malha fechada e trajetórias de referência pré-definidas; a primeira resolve um problema de otimização lexicográfica enquanto a segunda resolve um problema de otimização de compromisso. As vantagens dos métodos apresentados são: maior automatização, definição de objetivos de sintonia intuitiva que considera especificações na dinâmica do processo, uma métrica no domínio do tempo e é capaz de incluir o conhecimento do engenheiro de controle em uma técnica de sintonia confiável. Um estudo de caso no sistema de craqueamento catalítico ilustrou a flexibilidade de definição dos objetivos da técnica lexicográfica. Um estudo de caso sobre uma coluna de fracionadora de óleo pesado em malha fechada com um controlador preditivo por modelo comparou ambas as estratégias de sintonia desenvolvidas aqui e pode-se concluir que a técnica lexicográfica dá prioridade aos objetivos importantes enquanto a técnica de compromisso calcula uma solução média, com respeito aos objetivos. A técnica de compromisso foi comparada a um método de sintonia da literatura quanto a aplicação em um controlador preditivo de horizonte infinito com targets para as entradas e controle por faixas das saídas com uma coluna de destilação. Observou-se que a técnica desenvolvida aqui é computacionalmente mais rápida e não requer a escolha de uma solução não-dominada dentre um conjunto de soluções de Pareto. Aplicações reais de controle preditivo são severamente afetadas por incerteza de modelo. Estendeu-se as técnicas desenvolvidas aqui para considerar o caso de incerteza multi-planta, calculando parâmetros de sintonia robustos para controladores nominais, visando tratar o compromisso entre performance e estabilidade e robustez da malha fechada. Um controlador preditivo de horizonte infinito foi sintonizado de forma robusta e comparado com um controlador preditivo robusto em malha fechada com um modelo de separadora C3/C4. Observou-se que este consegue controlar melhor o processo, entretanto, tem um tempo de computação duas ordens de grandeza maior que o controlador nominal, em operação on-line. / Two multi-objective optimization based tuning techniques for Model Predictive Control (MPC) were developed. Both take into account the sum of the squared errors between closed-loop trajectories and reference responses based on pre-defined goals as tuning objectives; one solves a lexicographic optimization to obtain an optimum set of tuning parameters (LTT), whereas the other solves a compromise optimization problem (CTT). The main advantages are an automated framework, and straightforward goal definition, which are capable of taking into account a specification on the process dynamics, a time-domain metrics, and of embedding the control engineers knowledge into a reliable approach. A fluid catalytic cracking tuning case study unveiled the goal definition flexibility of the LTT, with respect to output tracking and variable coupling. A heavy oil fractionator in closed-loop with a MPC case study compared both tuning techniques developed here, and it was observed that the LTT in fact prioritizes the main objectives, whereas the CTT yields an average solution, in terms of the tuning objectives. The CTT was compared to another multi-objective tuning technique from the literature, in the tuning of a MPC with input targets and output zone control in closed-loop with a crude distillation unit model. The simulation results showed that the CTT allows for faster results, regarding the computational time to compute the tuning parameters and there is no need of a posteriori decisions to select the best non-dominated solution. Real MPC applications are strongly hindered by model uncertainty. This limitation was addressed by the extension of the tuning techniques to account for multi-plant model uncertainty, thus obtaining optimum robustly tuned parameters for nominal controllers, addressing the trade-off between robustness and performance. A robustly tuned Infinite Horizon MPC (IHMPC) was compared to a Robust IHMPC, in closed-loop with a C3/C4 splitter system model. It was observed in a simulation that even though the latter yields better output responses, it is two orders of magnitude slower than the former in online operation.

Orientador: Aline Carvalho da Costa / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Química / Made available in DSpace on 2018-08-21T12:53:49Z (GMT). No. of bitstreams: 1 BozaCondorena_EdwinGuido_D.pdf: 5093932 bytes, checksum: 505cbc2b6c875e35004ad875c0f0ac6a (MD5) Previous issue date: 2012 / Resumo: Na presente tese foram abordados problemas no contexto da produção de etanol de primeira e segunda geração. No caso de etanol de segunda geração foi abordado o problema de melhorar a eficiência da hidrolise enzimática, com as seguintes contribuições: (1) otimização da carga enzimática utilizando técnicas de modelagem por redes neurais. (2) substituição de um modelo com limitações na representatividade dos pontos experimentais obtido por desenho experimental pela superfície de resposta de um modelo de redes neurais que permite a exploração da região do ótimo no espaço de fatores e respostas. Os resultados obtidos mostram (1) boa precisão para a localização das coordenadas da região ótima de trabalho. (2) um mapeamento da evolução do processo com localização do ótimo global utilizando algoritmos genéticos e técnicas de computação evolutiva. No caso dos processos de produção de etanol de primeira geração foi estudado o problema do controle com modelo de um processo de fermentação continua com extração de etanol utilizando vácuo quando não se tem modelo fenomenológico disponível com as seguintes contribuições e resultados: (1) foi desenvolvida uma abordagem que integrou redes neurais artificiais, com o controle preditivo com modelo (MPC). (2) foram desenvolvidos modelos empíricos do processo com redes neurais artificiais (3) foi desenvolvida uma abordagem que utiliza o "conhecimento aprendido" pelas redes neurais o qual e armazenado em pesos sinápticos e bias. (4) foram desenvolvidos vários modelos empíricos de redes neurais para o monitoramento das concentrações de etanol que podem ser utilizados para desenvolver software sensores. (5) foram implementadas diferentes estruturas de controle preditivo com diferentes modelos internos de redes neurais para os controladores, com otimiza dor linear e não linear para o caso de estudo. Nos diferentes capítulos em que foram implementadas estruturas de controle integrando as redes neurais com a tecnologia MPC, se mostrou que, a abordagem desenvolvida e eficiente para os projetos dos sistemas de controle com modelo empírico / Abstract: In this thesis were studied problems in the context of ethanol production of first and second generation. In the case of second generation ethanol was studied the problem of improving the enzymatic hydrolysis efficiency, with the following contributions: 1) optimization of enzyme loading by using modeling techniques based on neural networks, 2) substitution of a model with limited representation capacity of the experimental points which was obtained by using experimental design by the response surface model of a neural network that allows the exploration of the space of factors and responses. The results show: 1) good accuracy in locating the coordinates of the optimum working region, 2) the mapping of the evolution of the process with the location of the global optimum by using genetic algorithms and evolutionary computing techniques. In case of the production of first generation ethanol was studied the problem of the control with process model of a fermentation process with continuous extraction of ethanol by using a vacuum system when there is no a phenomenological model available with the following contributions and results: 1) It was developed an approach in which were integrated artificial neural networks with model predictive control (MPC). 2) It were developed empirical process models by using artificial neural networks 3) It was developed an approach that uses the "learned knowledge" by neural networks which is stored in synaptic weights and bias. 4) It were developed several empirical models of neural networks for monitoring concentrations of ethanol that can be used to develop software sensors. 5) It were implemented different predictive control structures with different internal models based on neural networks for controllers with linear and non-linear optimizer to be applied on the case of study. In the different chapters in which were implemented control structures by integrating neural networks with MPC technology, it was showed that the developed approach is efficient to be applied in the designs of control systems with empirical model / Doutorado / Desenvolvimento de Processos Químicos / Doutor em Engenharia Química

Orientador: João Maurício Rosário, Didier Dumur / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia / Made available in DSpace on 2018-08-20T08:06:43Z (GMT). No. of bitstreams: 1 LaraMolina_FabianAndres_D.pdf: 6567422 bytes, checksum: 5d5531b99af8de161a3f8f390bcac8cf (MD5) Previous issue date: 2012 / Resumo: Este trabalho visa o desenvolvimento, síntese e aplicação de um controlador baseado em controle preditivo generalizado para rastreamento de trajetórias de robôs paralelos. A finalidade é melhorar o desempenho dinâmico do robô paralelo através do desenvolvimento de controladores avançados que considerem características do robô tais como não-linearidades da dinâmica, incertezas paramétricas e distúrbios externos. Inicialmente é revisada a formulação do modelo dinâmico do robô paralelo que envolve: modelo geométrico, cinemático e dinâmico. À continuação é realizado o projeto dos controladores de posição no espaço das juntas: controladores de torque computado com PID na forma RST, controlador preditivo generalizado e robustificação com os parâmetros de Youla. A seguir, a dinâmica do robô paralelo e os controladores desenvolvidos são simulados no ambiente MATLAB/Simulink. Finalmente, é realizada a implementação experimental e validação dos controladores no robô Orthoglide no laboratório de robótica do IRCCyN, École Centrale de Nantes. O controlador preditivo generalizado robustificado melhora a resposta dinâmica em relação ao controlador de torque computado que tem sido amplamente utilizado nesta classe de robôs. Os resultados obtidos através da implementação experimental da lei de controle preditiva robustificada no robô Orthoglide e testes experimentais indicam que o desempenho dinâmico do robô é melhorado em termos das seguintes caraterísticas: precisão no rastreamento de trajetórias típicas para usinagem no espaço de trabalho, estas trajetórias são executadas com diferentes acelerações máximas; robustez a variação dos parâmetros do robô tais como mudança da carga na plataforma móvel, obtendo desta forma uma melhor regulação; e finalmente, atenuação do efeito do ruído de medição nos sensores no sinal de controle dos atuadores durante a execução de um movimento. Os resultados experimentais mostraram que o controlador preditivo generalizado robustificado aplicado no robô Orthoglide é eficiente frente as incertezas paramétricas e restrições no domínio do tempo, melhorando assim o desempenho dinâmico do robô com um custo computacional equivalente ao controle de torque computado / Abstract: This thesis addresses the development and application of a controller based on generalized predictive control to track a desired trajectory using parallel robots. The main purpose of this thesis is to improve the dynamical behavior with an advanced controller which considers the proper characteristics of the parallel robot such as no linear dynamics, parameters uncertainties and external disturbances. This work is divided into four parts. A first part formulates the complete dynamical model of the parallel robot, considering the geometrical, kinematic and dynamic modelling. Then, the joint space control is performed for the parallel robot using the computed torque controller in the RST form and the robustified generalized predictive control via Youla parameterization. A third part shows the simulation of the dynamic of the robot with the controllers in MATLAB/Simulink to establish a comparison between controllers. Finally, the controllers are implemented in the prototype and some experiments are performed on the Orthoglide robot at the laboratory of robotics, IRCCyN, Ecole Centrale de Nantes to assess the dynamic performance of the controllers. The experimental results show that the robustification of the generalized predictive control against parametric uncertainties including time domain constraints improves the dynamical behavior of the parallel robots. The experimental results shows that the the robustified generalized predictive control enhances the dynamic performance of is in terms of: tracking accuracy of trajectories used in milling process; robustness to parameters variation such as payload changing (on the end effector), therefore, a better regulation is obtained; and finally, attenuation of noise due to sensor measurement in control. Additionally, the robustification of the generalized predictive control applied on the Orthoglide robot improves the dynamical behavior compared to controllers widely used in parallel robots such as computed torque control with and equivalent computational cost / Doutorado / Mecanica dos Sólidos e Projeto Mecanico / Doutor em Engenharia Mecânica

Orientador: Basilio Ernesto de Almeida Milani / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-04T02:32:56Z (GMT). No. of bitstreams: 1 VargasLara_JoseMaria_D.pdf: 1539805 bytes, checksum: cb3f1db3ea06ddceb5dac7d0f33c587c (MD5) Previous issue date: 2005 / Resumo: Este trabalho trata da síntese de um controlador preditivo adaptativo, baseado em modelos reduzidos obtidos mediante identificação orientada para controle preditivo. A metodologia proposta envolve duas áreas importantes para o sucesso do experimento de identificação. Na primeira, projeto de sinais de excitação, é mostrado como sinais de excitação pseudo-aleatórios multi-níveis podem ser projetados para atender com eficácia requisitos que sinais de excitação relevantes para controle devem satisfazer. Na segunda, modelagem de preditores, é abordada a modelagem por identificação de preditores de horizonte estendido. O objetivo central da metodologia proposta é o controle da remoção de matéria nitrogenada de uma planta de tratamento de esgotos por lodos ativados com pré-desnitrificação. A metodologia é aplicada para controlar a concentração de amônia mediante o controle do set-point de oxigênio dissolvido. A metodologia também é aplicada para o controle da concentração de nitrato no reator desnitrificante. Os controladores são avaliados em um estudo de simulação, mostrando a eficácia da metodologia proposta para o controle das concentrações de amônia e nitrato / Abstract: This work deals with the synthesis of an adaptive predictive controller, based on reduced models obtained via identification oriented to predictive control. The methodology proposed involves two important areas for the success of the identification experiment. In the first one, excitation signal design, it is shown how pseudo-random multilevel signals can be designed to effectively satisfy the requirements that excitation signals relevant for control should satisfy. In the second, predictor modelling, the identification of long-range horizon predictors is approached. The main objective of the proposed methodology is the control of the nitrogen removal in an predenitrifying activated sludge wastewater treatment plant. This methodology is applied to control the ammonium concentration in the denitrifying reactor. The controllers are evaluated in a simulation study, showing the effectiveness of the proposed methodology to control ammonium and nitrate concentrations / Doutorado / Automação / Doutor em Engenharia Elétrica

L'étendue des mouvements que les robots humanoïdes peuvent réaliser est fortement limitée par des contraintes dynamiques. Une loi de commande qui ne prend pas en compte ses res- trictions, d'une manière ou autre, ne va pas réussir d'éviter une chute. La Commande Prédictive est capable de considérer les contraintes sur l'état et le contrôle de manière explicite, ce qui la rend particulièrement appropriée pour le contrôle des mouvements des robots marcheurs.Nous commençons par dévoiler la structure spécifique de ces contraintes, démontrant notamment l'importance des appuis au sol. Nous développons ensuite une condition suffisante pour l'évitement d'une chute et nous proposons une loi de commande prédictive qui y réponde. Cette formulation nous sert ensuite pour la conception des contrôleurs pratiques, capables d'un contrôle plus efficace et plus robuste des robots marcheurs humanoïdes. / The range of motions that humanoid robots are able to realize is strongly limited by inherent dynamical constraints so that any control law that does not consider these limitations, in one way or another, will fail to avoid falling. The Model Predictive Control (MPC) technique is capable of handling constraints on the state and the control explicitly, which makes it highly apt for the control of walking robots.We begin by unveiling the specific structure of these constraints, stressing especially the impor- tance of the supports on the ground. We give thereupon a sufficient condition for keeping balance and formulate an MPC law that complies with it. This formulation serves us then for the design of practicable controllers capable of more efficient and more robust control of humanoid robots.

Dans l'objectif de réduire les consommations énergétiques des bâtiments et de diminuer leur impact sur le réseau électrique, il est utile de disposer de stratégies de gestion énergétique en temps réel. Il s'agit en effet d'un verrou clé dans la perspective des réseaux intelligents (« smart grids ») et des programmes de gestion de la demande (« demand response »). Cette thèse propose ainsi le développement de stratégies de gestion en temps réel du chauffage électrique d'un bâtiment énergétiquement performant en période de pointe électrique. Tout d'abord, ces stratégies nécessitent l'utilisation et le développement de plusieurs modèles, à savoir un modèle de prévision météorologique, un modèle d'occupation et un modèle énergétique dynamique du bâtiment. Ensuite, dans l'objectif d'un suivi fiable des performances énergétiques et pour un pilotage optimal des installations, le calibrage du modèle de bâtiment à partir de relevés in situ est préférable. Une nouvelle méthodologie, basée sur un criblage des paramètres incertains et sur l'utilisation d'une méthode d'inférence bayésienne (calcul bayésien approché) a ainsi été développée. Enfin, deux méthodes d'optimisation ont été étudiées pour le développement de stratégies de régulation adaptées au temps réel. La première repose sur une méthode d'optimisation hors-ligne dont l'objectif est d'approximer les résultats d'une stratégie optimale calculée par une méthode d'optimisation exacte et ainsi identifier des lois de commandes simplifiées. La deuxième méthode repose quant à elle sur la commande prédictive et l'adaptation au temps réel de la commande optimale sous contraintes d'état et de commande utilisant la pénalisation intérieure. Une maison de la plateforme INCAS de l'Institut National de l'Énergie Solaire (INES) a été utilisée comme cas d'application pour étudier par simulation les différentes stratégies développées. / To reach the objectives of reducing the energy consumption of buildings and decreasing their impact on the electrical grid, it is necessary to elaborate real time control strategies in view of smart grids and demand response programs. In this context, this thesis aims at developing real time control strategies for electric load shifting in energy efficient buildings. First, these strategies require appropriate models regarding weather forecast, occupants' behaviour and building energy simulation. Then, in order to improve the reliability of building energy simulation and to ensure optimal control of facilities, a calibration process of the model based on on-site measurements is recommended. In this way a new methodology was developed , based on a screening technique and a bayesian inference method (approximate bayesian computation). Finally, two optimisation techniques were studied to develop real time control strategies. The first technique was based on offline optimisation methods. The principle is to approximate optimisation results (and more specifically model based predictive controllers results) and to extract simplified control strategies. The second method consisted in using model predictive control and, more precisely, in solving in real time a state and input constrained optimal control problem by interior penalty methods. An actual experimental passive house being part of the INCAS platform built by the National Solar Energy Institute (INES) was used to study by numerical simulation the different strategies developed.

La conduite autonome a attiré une attention croissante au cours des dernières décennies en raison de son potentiel impact socio-économique, notamment concernant la réduction du nombre d'accidents de la route et l'amélioration de l'efficacité du trafic. Grâce à l'effort de plusieurs instituts de recherche et d'entreprises, les véhicules autonomes ont déjà accumulé des dizaines de millions de kilomètres parcourus dans des conditions de circulation réelles. Cette thèse porte sur la conception d'une architecture de contrôle pour les véhicules autonomes et coopératifs dans l'optique de leur déploiement massif. La base commune des différentes architectures proposées dans cette thèse est le Contrôle-Commande Prédictif, reconnu pour son efficacité et sa polyvalence. Nous présentons tout d'abord une architecture classique de contrôle hiérarchique, qui utilise la commande prédictive pour planifier un déplacement (choix de trajectoire), puis déterminer un contrôle permettant de suivre cette trajectoire. Toutefois, comme nous le montrons dans un deuxième temps, cette architecture simple n'est pas capable de gérer certaines contraintes logiques, notamment liées aux règles de circulation et à l'existence de choix de trajectoires discrets. Nous proposons donc approche hybride de la commande prédictive, que nous utilisons pour développer une architecture de contrôle pour un véhicule autonome individuel. Nous étudions le problème de contrôler un ensemble de véhicules autonomes circulant en convoi, i.e. maintenir une formation prédéterminée sans intervention humaine. Pour ce faire, nous utilisons à nouveau une architecture hiérarchique basée sur la commande prédictive, composée d'un superviseur de convoi et de contrôleurs pour chaque véhicule individuel. Enfin, nous proposons encore une architecture pour le problème de coordonner un groupe de véhicules autonomes dans une intersection sans feux de circulation, en utilisant un contrôleur d'intersection et en adaptant les contrôleurs des véhicules individuels pour leur permettre de traverser l'intersection en toute sécurité. / Autonomous driving has been gaining more and more attention in the last decades, thanks to its positive social-economic impacts including the enhancement of traffic efficiency and the reduction of road accidents. A number of research institutes and companies have tested autonomous vehicles in traffic, accumulating tens of millions of kilometers traveled in autonomous driving. With the vision of massive deployment of autonomous vehicles, researchers have also started to envision cooperative strategies among autonomous vehicles. This thesis deals with the control architecture design of individual autonomous vehicles and cooperative autonomous vehicles. Model Predictive Control (MPC), thanks to its efficiency and versatility, is chosen as the building block for various control architectures proposed in this thesis. In more detail, this thesis first presents a classical hierarchical control architecture for individual vehicle control that decomposes the controller into a motion planner and a tracking controller, both using nonlinear MPC. In a second step, we analyze the inability of the proposed planner in handling logical constraints raised from traffic rules and multiple maneuver variants, and propose a hybrid MPC based motion planner that solves this issue. We then consider the convoy control problem of autonomous vehicles in which multiple vehicles maintain a formation during autonomous driving. A hierarchical formation control architecture is proposed composing of a convoy supervisor and local MPC based vehicle controllers. Finally, we consider the problem of coordinating a group of autonomous vehicles at an intersection without traffic lights. A hierarchical architecture composed of an intersection controller and multiple local vehicle controllers is proposed to allow vehicles to cross the intersection smoothly and safely.

Les systèmes énergétiques désignent une classe de systèmes dont les spécificités structurelles et fonctionnelles posent la question de la distribution de l’énergie, en temps réel, pour satisfaire des services. Cette problématique multi-objectifs, nommée énergétique, a pour solution une stratégie de gestion,dont la conception représente un problème ouvert. Les verrous étudiés dans cette thèse s’inscrivent dans le cadre d’un partenariat industriel et en particulier celui des démarches de conception systémique. Trois contributions sont apportées. La première est une méthodologie de conception modulaire et générique de la stratégie énergétique, pour les systèmes multi-clients et multi-sources. Elle définit deux types d’éléments fonctionnels : les clients et les sources, interagissant par le biais d’un nœud, porteur de la stratégie. La seconde traite la simplification de la stratégie par une décomposition selon deux problématiques déjà connues de la littérature : l’hybridation de sources et la concurrence de clients. La troisième porte sur la sélection d’algorithmes novateurs ou existants, compatibles avec une cible temps réel, pour exécuter la stratégie. Enfin, la stratégie énergétique d’un camion frigorifique disposant d’une architecture énergétique hybride série est conçue par notre approche modulaire, et la faisabilité algorithmique est validée en simulation. / The energy systems describe a class of systems whose from structural and functional characteristics raise the problem of the energy distribution to satisfy the services in real time. The solution of this multi-objectives problem, namely energetic, is the energy management strategy, whose design is still an open problem. The solutions studied in this thesis are incorporated in the framework of an industrial partnership and particularly in those systemic design approaches. The first contribution is a methodology of modular and generic design of the energy management strategy, for the multi- clients and multi-sources systems. It defines two types of functional elements: the clients and the sources, interacting through a node, which is the carrier of thestrategy. The second contribution deals with thegeneric formulation of the strategy and itssimplification by means of decomposition in accordance with two problems: the hybridization of sources and the competition of clients, which a real ready known in the literature. The third contribution is partial to the selection of innovative or existing algorithms, which are compatible with a real-time target to execute the strategy. Finally, the energy strategy of a refrigerated truck with a hybrid energy architecture is designed by the proposed modular approach, and the algorithm feasibility is validated by the simulation.

Garantir le confort thermique des bâtiments est directement lié à la consommation d'énergie. Dans les zones tropicales, les systèmes de refroidissement représentent l'un des postes les plus gourmands en énergie. Afin de réduire la consommation d'énergie mondiale, il est primordial d'améliorer l'efficacité de ces systèmes ou bien de développer de nouvelles méthodes de production de froid. Une installation de refroidissement solaire basé sur le cycle à absorption est une alternative pour réduire les émissions de gaz à effet de serre et la consommation d'électricité. Contrairement aux systèmes classiques de refroidissement à compression mécanique, la production de froid par absorption est un système complexe composé de plusieurs composants comme des panneaux solaires, un ballon de stockage, une tour de refroidissement et une machine à absorption. Outre le dimensionnement des composants, ce système complexe nécessite des actions de contrôle pour être efficace parce que la coordination entre le stockage d'eau chaude, la production et la consommation du froid est nécessaire. Le but de cette thèse est de proposer une structure producteur-consommateur d'énergie basée sur la commande prédictive (MPC). Le système de refroidissement par absorption solaire est considéré comme faisant partie de ce système de production-consommation d'énergie, le système de stockage d'eau chaude est le producteur et la machine à absorption qui distribue de l'eau froide au bâtiment est l'un des consommateurs. Pour que la structure de commande soit modulaire, la coordination entre les sous-systèmes est réalisée en utilisant une approche de partitionnement où des contrôleurs prédictifs locaux sont conçus pour chacun des sous-systèmes. Les contrôleurs des consommateurs calculent un ensemble de profils de demande d'énergie. Ces profils sont ensuite envoyés au contrôleur du producteur qui sélectionne le profil qui minimise le coût global. Dans une première partie, l'approche proposée est testée sur un modèle linéaire simplifié composé d'un producteur et plusieurs consommateurs. Dans une deuxième partie, un cas plus complexe est étudié. Un modèle simplifié d'un système de refroidissement à absorption est évaluée en utilisant l'outil de simulation TRNSYS. Le modèle de production n'est plus linéaire, il est décrit par un modèle non linéaire hybride qui augmente la complexité du problème d'optimisation. Les résultats des simulations montrent que la sous-optimalité induite par la méthode est faible. De plus, la performance de l'approche atteint les objectifs de commande tout en respectant les contraintes. / To guarantee thermal comfort in buildings is directly related to energy consumption. In tropical climates, cooling systems for buildings represent one of the largest energy consumers. Therefore, as energy consumption is a major concern around the world, it is important to improve the systems efficiency or seeking new methods of cooling production. A solar cooling installation based on the absorption cycle is an alternative to mitigate greenhouse gas emissions and electricity consumption. In contrast to conventional vapor-compression based cooling systems, the absorption cooling production involves a complex system composed of several components as collector panel, storage tank, cooling tower and absorption chiller. Besides the sizing of the components, this complex system requires control actions to be efficient as a coordination between hot water storage, cooling water production and consumption is necessary. The aim of this research is to propose a management approach for a production-consumption energy system based on Model Predictive Control (MPC). The solar absorption cooling system is seen as part of this production-consumption energy system where the hot water storage system is the producer and the chiller-building system is one of the consumers. In order to provide modularity to the control structure, the coordination between the subsystems is achieved by using a partitioning approach where local predictive controllers are developed for each of the subsystems. The consumer controllers compute a set of energy demand profiles sent to the producer controller which selects the profile that better minimize the global optimization cost. In a first part, the proposed approach is tested on a simplified linear model composed of one producer and several consumers. In a second part, a more complex case is studied. A simplified model of an absorption cooling system is evaluated using the simulation tool TRNSYS. The producer model is no longer linear, instead it is described by a nonlinear hybrid model which increases the complexity of the optimization problem. The simulations results show that the suboptimality induced by the method is low and the control strategy fulfills the objectives and constraints while giving good performances.