O objetivo principal desta tese foi a implantação de uma nova estratégia para a integração da otimização em tempo real (RTO), com o controle preditivo multivariável em uma unidade de processo industrial. A solução proposta pode ser considerada como uma estratégia de uma camada, na qual os problemas de controle e otimização econômica são resolvidos simultaneamente, na mesma camada da estrutura de controle. Supondo que o objetivo econômico a ser maximizado (minimizado) seja uma função côncava (convexa) das entradas e saídas de processo, o controlador MPC com otimização econômica (OMPC) foi obtido através da inclusão do gradiente reduzido do objetivo econômico, na função objetivo do controlador preditivo. Esta abordagem foi testada inicialmente através da simulação do conjunto reator regenerador de uma Unidade de Craqueamento Catalítico Fluido (UFCC). O controlador otimizador foi implementado com sucesso em uma coluna de destilação de tolueno, na Unidade de Recuperação de Aromáticos da refinaria de Cubatão da Petrobras. Este controlador está em funcionamento contínuo por cerca de um ano, sem qualquer problema relatado. Para a determinação das condições ótimas, um modelo rigoroso de coluna de destilação multicomponentes no estado estacionário é incluído no controlador preditivo para permitir o cálculo online do objetivo econômico. A trajetória prevista para o sistema de destilação até o ponto ótimo é calculada utilizando-se um modelo linear dinâmico, o qual foi obtido através de testes em degrau na planta real. O ponto ótimo obtido através da estratégia proposta leva em consideração as restrições nas entradas manipuladas e a faixa de controle para as saídas. O problema de otimização resultante para cálculo das ações de controle é uma QP, que pode ser facilmente resolvida com os solvers disponíveis. O MPC com otimização econômica foi implementado como um módulo do pacote SICON (Sistema de Controle da Petrobras). / This thesis was mainly aimed at the implementation of a new strategy for the integration of real time optimization (RTO) with multivariable predictive control in an industrial process system. The proposed strategy can be considered as a one-layer strategy where the control and economic optimization problems are solved simultaneously in the same layer of the control structure. Assuming that the economic objective to be maximized (minimized) is a concave (convex) function of the process inputs and outputs, the optimizing model predictive control (OMPC) was obtained through the inclusion of the reduced gradient of the economic objective in the control objective of the predictive controller. The approach was initially tested through the simulation of the reactorregenerator of a Fluid Catalytic Cracking Unit (FCCU). The optimizing controller has been successfully implemented in a toluene distillation column at the Aromatic Recovery Unit of the Cubatão refinery of Petrobras. This controller has been in continuous operation for about one year without any reported problem. For determining the optimum operating conditions, a steady-state rigorous multicomponent distillation model is included in the predictive controller to allow the on-line computation of the economic objective. The predicted trajectory of the distillation system towards the optimum point is computed with a linear dynamic model that was obtained through step tests in the real plant. The optimum point that is achieved with the proposed strategy takes into account the constraints in the manipulated inputs and the zone control of the outputs. The resulting optimization problem that produces the control actions is a QP that can be easily solved with available solvers. The optimizing MPC was implemented as a module of the SICON (Petrobras Control System) package.

La distillation est une opération unitaire de séparation qui est largement utilisée. Toutefois, lorsque les volatilités des corps à séparer sont proches, le besoin en énergie de la colonne augmente, et l’efficacité énergétique du procédé de séparation diminue. Ainsi, la faiblesse de la distillation est son efficacité énergétique (au maximum 10 %). La réduction de la consommation énergétique des colonnes à distiller est donc un enjeu majeur dans le contexte énergétique actuel. Une des voies prometteuses est les colonnes à distiller dites HIDiC (Heat Integrated Distillation Column). Dans ce type de configuration, la colonne est scindée en deux colonnes : une colonne d’appauvrissement et une colonne d’enrichissement. La colonne d’appauvrissement opère à un niveau de pression plus faible que la colonne d’enrichissement. Un compresseur ainsi qu’une vanne de détente sont installés pour ajuster les niveaux de pression respectifs dans les deux parties. La différence de pression ainsi établie permet d’imposer une différence de températures qui offre la possibilité de transférer de l’énergie entre les deux colonnes par l’intermédiaire d’une technologie de transfert de chaleur. Dans un premier temps, l’objet de cette étude est de valider une nouvelle technologie de transfert thermique pour les colonnes concentriques HIDiC. Cette technologie innovante, Mousse métallique à cellules ouvertes, est caractérisée et validée en comparant avec un garnissage classique. Pour cela, un pilote expérimental de colonne concentrique contenant le garnissage structuré a été mis en oeuvre au laboratoire. Les résultats des mousses métalliques ont montré une performance thermique plus importante que le garnissage classique avec un gain moyen de 102 %. La conductance thermique des mousses métallique à cellules ouvertes obtenue expérimentalement est de 1285 W.K-1. Ces résultats confirment l’intérêt de l’utilisation du garnissage innovant dans les colonnes de distillation HIDiC en tant que technologie de transfert de chaleur. Dans un deuxième temps, un outil de simulation des colonnes HIDiC est développé dans le logiciel commercial ProSim Plus™®. Par rapport aux colonnes de distillation conventionnelles, les colonnes HIDiC possèdent des paramètres spécifiques tels que le rapport de pression et le profil d’échange de chaleur entre les deux sections de la colonne. Une procédure d’optimisation est élaborée afin d’obtenir une colonne HIDiC avec un coût total annuel « TAC » minimal et une distribution énergétique optimale. La méthode stochastique est adoptée avec un algorithme génétique « AG » ou l’initialisation des variables d’action n’est pas nécessaire. Deux études de cas sont effectuées. L’une est un système largement étudié dans la littérature, le mélange (Benzène/Toluène). La procédure de conception et d’optimisation est évaluée. Une réduction du TAC de 7,4 % et 13,9 % est obtenue par rapport aux précédents travaux de la littérature. L’autre étude de cas est un mélange binaire (Cyclohexane/n-Heptane). Les résultats de la simulation concernant les quantités d’énergie échangées de la colonne d’enrichissement vers la colonne d’appauvrissement sont validés en vérifiant la faisabilité du transfert thermique par la conductance thermique de la technologie innovante obtenue expérimentalement UA (W.K-1). / Distillation is the most applied separation technology. Its major drawback is the low thermodynamic efficiency (typically around 10 %). In response to environmental issues that concern energy consumption of distillation column, HIDiC (heat integrated distillation column) which combines advantages of vapor recompression and diabatic operation is expected to have a large impact on energy saving. The mixtures with close boiling point are confirmed to be the best candidates for HIDiC. In fact, in this configuration the rectifying section and the stripping section are separated. Heat is transferred inside the distillation column from the rectifying to the stripping section, because the operating pressure (and thus the temperature) of the rectifying section is increased by means of the compressor. First, a novel technology of heat and mass transfer between rectifying column and stripping column is characterized and validated on an experimental pilot. A concentric HIDiC which contains metal foam packing is designed. Compared to the Raschig Super-Ring results, the heat transfer in this structured packing is more efficient, with a gain up to 102 %. The obtained thermal conductance UA (W.K-1) of the innovative column packing is 1285 W.K-1. This confirms the purpose of open cell metal foams use in HIDiC as a heat transfer technology. Secondly, the aim of this study is to optimize the HIDiC sensitive parameters so as to minimize the Total Annual Cost (TAC). For this, a HIDiC simulation model is developed by using commercial software ProSim Plus™®. GA (Genetic Algorithm) is used to find the optimal HIDiC configuration where variables are optimized without initialization. Binary (Benzene/Toluene) separation case is examined for the evaluation of the proposed method. As a result, 7.4 % and 13.9 % TAC reductions are realized in comparison with the reported solutions in previous works. Binary (Cyclohexane/n-Heptane) is studied to evaluate the physical feasibility of heat transfer between rectifying and stripping column by the experimental thermal conductance (UA experimental [W.K-1]) of the innovative column packing.

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Made available in DSpace on 2014-12-17T14:08:55Z (GMT). No. of bitstreams: 1 PauloECB_DISSERT.pdf: 998748 bytes, checksum: ca9ede6adc0bf3c38d53d423e9580270 (MD5) Previous issue date: 2013-04-01 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / This work aims to obtain a low-cost virtual sensor to estimate the quality of LPG. For the acquisition of data from a distillation tower, software HYSYS ? was used to simulate chemical processes. These data will be used for training and validation of an Artificial Neural Network (ANN). This network will aim to estimate from available simulated variables such as temperature, pressure and discharge flow of a distillation tower, the mole fraction of pentane present in LPG. Thus, allowing a better control of product quality / Este trabalho tem como objetivo a obten??o de um sensor virtual de baixo custo para estimar a qualidade do GLP. Para a simula??o dos dados gerados por uma torre de destila??o foi utilizado um software que simula processos qu?micos, chamado HYSYS?. Esses dados ser?o utilizados para treinamento e valida??o de uma Rede Neural Artificial (RNA). Essa rede ter? como objetivo estimar a partir de vari?veis dispon?veis em uma simula??o, como a temperatura, press?o e vaz?o de refluxo de uma torre de destila??o, a fra??o molar de pentano presente no GLP. Possibilitando, desta forma, um melhor controle de qualidade do produto final

Made available in DSpace on 2014-12-17T14:55:08Z (GMT). No. of bitstreams: 1 ThiagoMB_DISSERT.pdf: 1745996 bytes, checksum: af67dc28800011b16eb3931959630ac2 (MD5) Previous issue date: 2012-11-12 / Funda??o Norte-Riograndense de Pesquisa e Cultura / The need to implement a software architecture that promotes the development of a SCADA supervisory system for monitoring industrial processes simulated with the flexibility of adding intelligent modules and devices such as CLP, according to the specifications of the problem, it was the motivation for this work. In the present study, we developed an intelligent supervisory system on a simulation of a distillation column modeled with Unisim. Furthermore, OLE Automation was used as communication between the supervisory and simulation software, which, with the use of the database, promoted an architecture both scalable and easy to maintain. Moreover, intelligent modules have been developed for preprocessing, data characteristics extraction, and variables inference. These modules were fundamentally based on the Encog software / A necessidade de desenvolver uma arquitetura de software que promovesse o desenvolvimento de supervis?rio SCADA para monitora??o de processos industriais simulados, com flexibilidade de agregar m?dulos inteligentes e equipamentos como CLP, de acordo com as especifica??es do problema, foi a for?a motriz desse trabalho. No presente estudo foi desenvolvido um supervis?rio inteligente sobre uma simula??o de uma coluna de destila??o modelada no Unisim. Foi utilizado como comunica??o entre o supervis?rio e o software de simula??o o OLE Automation, o qual, junto ao uso de banco de dados, promoveu uma arquitetura de f?cil manuten??o e escal?vel. Foram desenvolvidos ainda m?dulos inteligentes para pr?processamento, extra??o de caracter?sticas dos dados e infer?ncia de vari?veis. Estes m?dulos tiveram como base principal o software Encog.

Made available in DSpace on 2014-12-17T14:55:42Z (GMT). No. of bitstreams: 1 LeandroLSL_DISSERT.pdf: 1890433 bytes, checksum: 540cbd4cf39fb3515249b7cecd6d0dcc (MD5) Previous issue date: 2010-03-19 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / Nowadays, where the market competition requires products with better quality and a constant search for cost savings and a better use of raw materials, the research for more efficient control strategies becomes vital. In Natural Gas Processin Units (NGPUs), as in the most chemical processes, the quality control is accomplished through their products composition. However, the chemical composition analysis has a long measurement time, even when performed by instruments such as gas chromatographs. This fact hinders the development of control strategies to provide a better process yield. The natural gas processing is one of the most important activities in the petroleum industry. The main economic product of a NGPU is the liquefied petroleum gas (LPG). The LPG is ideally composed by propane and butane, however, in practice, its composition has some contaminants, such as ethane and pentane. In this work is proposed an inferential system using neural networks to estimate the ethane and pentane mole fractions in LPG and the propane mole fraction in residual gas. The goal is to provide the values of these estimated variables in every minute using a single multilayer neural network, making it possibly to apply inferential control techniques in order to monitor the LPG quality and to reduce the propane loss in the process. To develop this work a NGPU was simulated in HYSYS R software, composed by two distillation collumns: deethanizer and debutanizer. The inference is performed through the process variables of the PID controllers present in the instrumentation of these columns. To reduce the complexity of the inferential neural network is used the statistical technique of principal component analysis to decrease the number of network inputs, thus forming a hybrid inferential system. It is also proposed in this work a simple strategy to correct the inferential system in real-time, based on measurements of the chromatographs which may exist in process under study / Nos dias atuais, em que a concorr?ncia de mercado exige produtos de melhor qualidade e a busca constante pela redu??o de custos e pelo melhor aproveitamento das mat?rias-primas, a utiliza??o de estrat?gias de controle mais eficientes torna-se fundamental. Nas Unidades de Processamento de G?s Natural (UPGNs), assim como na maioria dos processos qu?micos, o controle de qualidade ? realizado a partir da composi??o de seus produtos. Entretanto, a an?lise de composi??es qu?micas, mesmo quando realizada por equipamentos como os cromat?grafos a g?s, apresenta longos intervalos de medi??o. Esse fato dificulta a elabora??o de estrat?gias de controle que proporcionem um melhor rendimento do processo. Geralmente, o principal produto econ?mico de uma UPGN ? o GLP (G?s Liquefeito de Petr?leo). Outros produtos comumente obtidos nessas unidades s?o a gasolina natural e o g?s residual. O GLP ? formado idealmente por propano e butano. Entretanto, na pr?tica, apresenta em sua composi??o contaminantes, tais como o etano e o pentano. Neste trabalho ? proposto um sistema de infer?ncia utilizando redes neurais para estimar as fra??es molares de etano e pentano no GLP e a fra??o molar de propano no g?s residual. O objetivo ? estimar essas vari?veis a cada minuto com uma ?nica rede neural de m?ltiplas camadas, permitindo a aplica??o de t?cnicas de controle inferencial visando a controlar a qualidade do GLP e reduzir a perda de propano no processo. No desenvolvimento deste trabalho, ? simulada no software HYSYS R uma UPGN formada por uma coluna de destila??o deetanizadora e outra debutanizadora. A infer?ncia ? realizada a partir das vari?veis de processo de alguns controladores PID presentes na instrumenta??o das colunas citadas. Com o intuito de reduzir a complexidade da rede neural de infer?ncia, ? utilizada a t?cnica estat?stica de an?lise de componentes principais (ACP) para diminuir o n?mero de entradas da rede. Tem-se, portanto, um sistema h?brido de infer?ncia. Tamb?m ? proposta neste trabalho, uma estrat?gia simples para a corre??o em tempo real do sistema de infer?ncia, tendo como base as medi??es dos poss?veis cromat?grafos de linha presentes no processo em estudo

Made available in DSpace on 2014-12-17T14:55:51Z (GMT). No. of bitstreams: 1 BrunoXC_DISSERT.pdf: 1188084 bytes, checksum: 9f335fff2b0475dfa1b67655e6d44e2f (MD5) Previous issue date: 2011-03-11 / The main purpose of this work is to develop an environment that allows HYSYS R chemical process simulator communication with sensors and actuators from a Foundation Fieldbus industrial network. The environment is considered a hybrid resource since it has a real portion (industrial network) and a simulated one (process) with all measurement and control signals also real. It is possible to reproduce different industrial process dynamics without being required any physical network modification, enabling simulation of some situations that exist in a real industrial environment. This feature testifies the environment flexibility. In this work, a distillation column is simulated through HYSYS R with all its variables measured and controlled by Foundation Fieldbus devices / O principal objetivo deste trabalho ? desenvolver um ambiente que permite a comunica??o do simulador de processos qu?micos HYSYS R com medidores e atuadores de uma rede industrial Foundation Fieldbus. O ambiente ? considerado h?brido por possuir uma parte real (a rede industrial) e uma parte simulada (o processo) com os sinais de controle e medi??o sendo reais. O ambiente ? bastante flex?vel, permitindo a reprodu??o de diversas din?micas t?picas de processos industriais sem a necessidade de altera??o na rede f?sica, possibilitando gerar diversas situa??es existentes em um ambiente industrial real. No presente trabalho, a din?mica utilizada ? de uma coluna de destila??o, simulada no HYSYS R, com suas vari?veis medidas e controladas pelos dispositivos da rede industrial Foundation Fieldbus

Made available in DSpace on 2014-12-17T14:56:09Z (GMT). No. of bitstreams: 1 JoaoTCN_DISSERT.pdf: 3199747 bytes, checksum: e80bdfe5ca1e9afb305fbbd4d3a99259 (MD5) Previous issue date: 2012-07-30 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / The need to implement a software architecture that promotes the development of a SCADA supervisory system for monitoring industrial processes simulated with the flexibility of adding intelligent modules and devices such as CLP, according to the specifications of the problem, it was the motivation for this work. In the present study, we developed an intelligent supervisory system on a simulation of a distillation column modeled with Unisim. Furthermore, OLE Automation was used as communication between the supervisory and simulation software, which, with the use of the database, promoted an architecture both scalable and easy to maintain. Moreover, intelligent modules have been developed for preprocessing, data characteristics extraction, and variables inference. These modules were fundamentally based on the Encog software / A necessidade de desenvolver uma arquitetura de software que promovesse o desenvolvimento de supervis?rio SCADA para monitora??o de processos industriais simulados, com flexibilidade de agregar m?dulos inteligentes e equipamentos como CLP, de acordo com as especifica??es do problema, foi a for?a motriz desse trabalho. No presente estudo foi desenvolvido um supervis?rio inteligente sobre uma simula??o de uma coluna de destila??o modelada no Unisim. Foi utilizado como comunica??o entre o supervis?rio e o software de simula??o o OLE Automation, o qual, junto ao uso de banco de dados, promoveu uma arquitetura de f?cil manuten??o e escal?vel. Foram desenvolvidos ainda m?dulos inteligentes para pr?processamento, extra??o de caracter?sticas dos dados e infer?ncia de vari?veis. Estes m?dulos tiveram como base principal o software Encog

Orientadores: Maria Regina Wolf Maciel, Antonio Andre Chivanga Barros, Henry França Meier / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica / Made available in DSpace on 2018-08-05T18:14:26Z (GMT). No. of bitstreams: 1 Soares_Cintia_D.pdf: 3816439 bytes, checksum: e39afd5653e2802b28899a3c09f4753c (MD5) Previous issue date: 2005 / Resumo: Grande parte dos estudos envolvendo colunas de destilação está fundamentada por modelos macroscópicos de conservação de massa e de energia. Exemplo disto são os modelos de estágios de equilíbrio e de não-equilíbrio. Nestes, os aspectos fluidodinâmicos do escoamento são restritos e orientados à medição de parâmetros macroscópicos. Porém, graças aos avanços introduzidos pelo emprego das técnicas da fluidodinâmica computacional (CFD), a análise de processos empregando uma abordagem microscópica tornou-se mais sofisticada e precisa. Além disto, há necessidade de trabalho experimental com o propósito de validar modelos e métodos em CFD e medir outros parâmetros ao longo do equipamento. Dentro deste contexto, este trabalho visa o desenvolvimento de uma metodologia de caráter numérico e experimental que possibilite o estudo do escoamento líquido-vapor, em nível microscópico, em um prato perfurado de uma coluna de destilação. Para tanto, objetiva-se a proposição de um modelo microscópico de conservação da quantidade de movimento, em condições de escoamento turbulento, sob a influência da fase vapor, e de uma metodologia para a aquisição de dados experimentais. A metodologia numérica consistiu em iniciar com um estudo aprofundado do escoamento com superfície livre, utilizando um módulo experimental de hidráulica, seguido do estudo do escoamento monofásico na superfície de um prato perfurado. Estudos em uma coluna de bolhas permitiram a obtenção de experiência com modelos e métodos associados ao escoamento multifásico. Finalmente, foram realizados estudos sobre o escoamento líquido-vapor em pratos perfurados com a proposição de um modelo 3-D e homogêneo. Na metodologia de solução, o principal objetivo esteve relacionado às características numéricas, tais como: fatores de relaxação, esquemas de interpolação, integração temporal, acoplamento pressão-velocidade, entre outras. A metodologia experimental consistiu no projeto e construção de uma coluna de destilação para a simulação física do escoamento líquido-vapor em um estágio a frio, sendo as informações microscópicas obtidas por meio do emprego da técnica de anemometria térmica. Técnicas de visualização do escoamento foram empregadas como ferramenta de análise qualitativa na identificação de padrões de escoamento, como mecanismo de apoio à realização de medidas experimentais e, finalmente, como instrumento complementar de análise para facilitar a interpretação dos resultados. A metodologia numérica permitiu a avaliação de estratégias de solução de modelos e métodos em CFD, além do desenvolvimento de um modelo homogêneo capaz de predizer o escoamento líquidovapor, em nível microscópico, em um prato perfurado de uma coluna de destilação. A metodologia experimental permitiu a caracterização do escoamento em um tanque retangular, entretanto, a técnica de anemometria térmica apresentou limitações quando da aplicação no escoamento bifásico. Na análise dos resultados obtidos concluiu-se que há a ocorrência de diferentes padrões de escoamento no interior de uma coluna de destilação, de acordo com a vazão da fase gás e da geometria do prato, sendo o escoamento não uniforme. Além disto, há uma tendência do fluxo de líquido próximo à parede retroceder, o que resulta no fenômeno de circulação. Outra observação importante foi que a fase vapor, em contato com o líquido fluindo horizontalmente, obtém uma energia cinética na direção do fluxo de líquido / Abstract: Greater part of researches involving distillation columns is based on macroscopic models of mass and energy conservation. Examples are the equilibrium and non-equilibrium stage models. In these cases, the fluid dynamics characteristics are restricted in measuring macroscopic parameters. However, advances introduced by fluid dynamic techniques made possible a more sophisticated and accurate process analysis using a microscopic approach. Researches in this area are indispensable and more experimental studies is necessary in order to validate models and methods in CFD and measure other parameters along the equipment. Based on these statements, this work takes aim the development of a numerical and experimental methodology that enables the study of liquid-vapour flow, in a microscopic level, on a sieve plate of a distillation column. It is proposed the development, implementation and application of a microscopic model for momentum conservation subjected to turbulent flow of the vapour phase, complemented by the development of an experimental methodology for data acquisition in an apparatus in laboratory scale. The numerical methodology consisted to make a deep study of flow with free surface using a hydraulic modulus and a study of a single-phase flow on a sieve plate. Studies in a bubble column allowed building knowledge for modelling momentum transfer phenomenon in multiphase flow. Finally, studies about the liquid-vapour flow in sieve plates were carried out with development of a 3-D and homogeneous model. The main objective in the solution methodology was related to numerical characteristics, such as: relaxation factors, interpolation schemes, temporal integration and pressure-velocity coupling. The experimental methodology consisted in the design and building of a distillation column that simulates the liquid-vapour in a sieve plate. The information related to velocity profiles were obtained by means of definition and implementation of the thermal anemometry technique. During the numerical and experimental studies, flow visualization techniques have also been employed in different ways as a tool for qualitative analysis of different flow patterns, as an assistance to the experimental measures, and finally, as a complement to the analysis, supporting the interpretation of results. The numerical methodology allowed the evaluation of models and methods strategies in CFD, and the development of a homogeneous model able to predict the liquid-vapour flow in a sieve plate of a distillation column. On the other hand, the experimental methodology allowed the evaluation of flow inside a rectangular reservoir, but the thermal anemometry technique presented limitations in the multiphase flow. It was concluded that there is the occurrence of different flow patterns inside the distillation column, according to the gas flow and plate geometry, and the flow is not uniform in the plate surface. Besides, there is a tendency of the liquid flow to go back near the wall, resulting in a circulating zone. Other observation was that the vapour phase, contacting with the horizontally flowing liquid, gains a kinetic energy in the direction of liquid flow / Doutorado / Desenvolvimento de Processos Químicos / Doutor em Engenharia Química

Le procédé de distillation est largement utilisé dans de nombreuses applications telles que la production pétrochimique, le traitement du gaz naturel, les raffineries de pétrole, etc. Généralement, la maintenance des réacteurs chimiques est très coûteuse et perturbe la production pendant de longues périodes. Tous ces facteurs démontrent réellement la nécessité de stratégies efficaces de diagnostic et de pronostic des défauts pour pouvoir réduire et éviter le plus grand nombre de ces problèmes catastrophiques. La première partie de nos travaux vise à proposer une méthode de diagnostic fiable pouvant être utilisée dans le régime permanent d’une procédure non linéaire. De plus, nous proposons une procédure modifiée de la méthode MFCM permettant de calculer la variation en pourcentage entre deux classes. L’utilisation de MFCM a pour objectif de réduire le temps de calcul et d’accroître les performances du classifieur. Les résultats de la méthode proposée confirment la capacité de classifier entre les différentes classes de défaillances considérées. Le calcul de la durée de vie du système est extrêmement important pour éviter les pannes catastrophiques. Notre deuxième objectif est de proposer une méthode fiable de pronostic permettant d’estimer le chemin de dégradation d’une colonne de distillation et de calculer le pourcentage de durée de vie de ce système. Le travail présente une approche basée sur le système d’inférence neuro-fuzzy adaptatif (ANFIS) combiné avec (FCM) pour prédire la trajectoire future et calculer le pourcentage de durée de vie du système. Les résultats obtenus démontrent la validité de la technique proposée pour atteindre les objectifs requis avec une précision de haut niveau. Pour améliorer les performances d’ANFIS, nous proposons la distribution de Parzen comme nouvelle fonction d’appartenance de l’algorithme ANFIS. Les résultats ont démontré l’importance de la technique proposée car elle s’est avérée efficace pour réduire le temps de calcul. En outre, la distribution de Parzen présentait la plus petite erreur quadratique moyenne (RMSE). La dernière partie de cette thèse se concentrait sur la proposition d’un nouvel algorithme pouvant être appliqué pour obtenir un système de surveillance en temps réel s’appuyant sur la prédiction de défauts ; cela signifie que cette méthode permet de prédire l’état futur du système, puis de diagnostiquer quelle est la source d’erreur probable. Elle permet d’évaluer la dégradation d’une colonne de distillation et de diagnostiquer par la suite les défauts ou accidents pouvant survenir à la suite de la dégradation estimée. Cette nouvelle approche combine les avantages d’ANFIS à ceux de RNA permettant d’atteindre un haut niveau de précision. / The distillation process is largely used in many applications such a petrochemical production, natural gas processing, and petroleum refineries, etc. Usually, maintenance of the chemical reactors is very costly and it disrupts production for long periods of time. All these factors really demonstrate the fundamental need for effective fault diagnosis and prognostic strategies that they are able to reduce and avoid the greatest number of thes problems and disasters. The first part of our work aims to propose a reliable diagnostic method that can be used in the steady-state regime of a nonlinear procedure. Moreover, we propose a modified procedure of the fuzzy c-means clustering method (MFCM) where MFCM calculates the percentage variation between the two clustered classes. The purpose of using MFCM is to reduce the computing time and increase the performance of the classifier. The results of the proposed method confirm the ability to classify between normal mode and eight abnormal modes of faults. Our second goal aims to propose a prognosis reliable method used to estimate the degradation path of a distillation column and calculate the lifetime percentage of this system. The work presents an approach based on adaptive neuro-fuzzy inference system (ANFIS) combined with (FCM) to predict the future path and calculate the lifetime percentage of the system. The results obtained demonstrate the validity of the proposed technique to achieve the needed objectives with a high-level accuracy. To improve ANFIS performance we propose Parzen windows distribution as a new membership function for ANFIS algorithm. Results demonstrated the importance of the proposed technique since it proved to be highly successful in terms of reducing the time consumed. Additionally, Parzen windows had the smallest Root Mean Square Error (RMSE). The last part of this thesis was focusing on the proposing of new algorithm which can be applied to obtain real-time monitoring system which relies on the fault production module to reach the diagnosis module in contrast to the previous strategies ; this means this method predict the future state of the system then diagnosis what is the probable fault source. This proposed method has proven to be a reliable process that can evaluate the degradation of a distillation column and subsequently diagnose the possible faults or accidents that can emerge as a result of the estimated degradation. This new approach combines the benefits of ANFIS with the benefits of feedforward ANN. The results were demonstrated that the technique achieved with a high level of accuracy, the objective of prediction and diagnosis especially when applied to the data obtained from automated distillation process in the chemical industry.