Sistemas de pulverização com injeção direta possibilitam o uso de diferentes agrotóxicos em uma mesma aplicação, reduzindo o desperdício de agrotóxicos e minimizando desta forma os impactos toxicológico e ambiental relacionados com o preparo e descarte da calda. Neste trabalho foram desenvolvidos modelos matemáticos para um sistema de pulverização com injeção direta de agrotóxico, incluindo a dinâmica da concentração da calda. Também foi desenvolvida uma estratégia de controle preditivo com antecipação das taxas de aplicação para ajustar as taxas de aplicação do agrotóxico e da calda. Também, uma plataforma flexível para o desenvolvimento de pulverizadores foi projetada e construída. A sua automação foi baseada em um controlador embarcado de tempo real adequado para aplicações de controle, aquisição e temporização. Para obter os parâmetros dos modelos e avaliar a estratégia de controle ensaios de vazão e concentração para diferentes pontas de pulverização foram propostos. Com o emprego da abordagem de controle preditivo, os erros das vazões do agrotóxico e da calda ficaram abaixo do nível admissível de 5%. O uso da estratégia de antecipação das taxas de aplicação permitiu aumentar a eficiência da aplicação, reduzindo em até 40% os erros de aplicação. Resultados experimentais são apresentados para validar os modelos e mostrar a eficiência da estratégia de controle desenvolvida. / Sprayer systems with direct injection allow the use of different pesticides in a single application, reducing the waste of chemicals and thereby minimizing the toxicologic and environmental risks associated with the carrier-chemical mix preparation and discard. In this work, mathematical models for a direct chemical injection sprayer system including the dynamics of the carrier-chemical mix concentration are developed. Also, a predictive control strategy with anticipative reference of application rates was developed to adjust the carrier-chemical mix and chemical flow rates. Also, a flexible platform for the development of sprayers was designed and constructed. The automation of this platform was based on a programmable automation controller suitable for control, acquisition and timming applications. To obtain the models and analyse the control strategy, essays flow and concentration for different spray nozzles were proposed. With the use of predictive control approach, the errors of the carrier-chemical mix and chemical flow rates were lower than the admissible level of 5 %. The use of the advanced references increased the efficiency of the variable rate application, reducing up to 40 % application errors. Practical results are presented to validate the models and show the efficiency of the developed control strategy.

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.

Au cours des deux dernières décennies, la prise de conscience du changement climatique et des conséquences du réchauffement climatique a incité diverses institutions à prendre de nouvelles directives. Ces directives portent principalement sur le contrôle des émissions des gaz à effet de serre, sur l'utilisation des ressources énergétiques non conventionnelles et l'optimisation de la consommation d'énergie dans les systèmes existants. L'Union européenne a proposé de nombreux projets dans le cadre du 7e PCRD pour réaliser jusqu'à 20% d’économies d'énergie d’ici 2020. En particulier, selon la directive sur l'efficacité énergétique, les bâtiments sont majoritairement responsables de 40% des dépenses énergétiques en Europe et de 36% des émissions de CO2 ; c’est la raison pour laquelle un ensemble d’initiatives européennes dans le cadre du 7ième PCRD favorise l'utilisation de technologie intelligente dans les bâtiments et rationalise les règles existantes. Energy IN TIME est l'un des projets axés sur l'élaboration d'une méthode de contrôle basée sur la simulation intelligente de l'énergie qui permettra de réduire la consommation des bâtiments non résidentiels. Ce mémoire de thèse propose plusieurs solutions novatrices pour réaliser les objectifs du projet mandaté à l'Université de Lorraine. Les solutions développées dans le cadre de ce projet devraient être validées sur différents sites européens de démonstration. Une première partie présente l'analyse détaillée de ces sites de démonstration et leurs contraintes respectives. Un cadre général correspondant à la construction type de ces sites a été élaboré pour simuler leur comportement. Ce cadre de construction de référence sert de banc d'essai pour la validation des solutions proposées dans ce travail de thèse. Sur la base de la conception de la structure de construction de référence, nous présentons une formulation de contrôle économique utilisant un modèle de contrôle prédictif minimisant la consommation d'énergie. Ce contrôle optimal possède des propriétés de contrôle conscientes de la maintenance. En outre, comme les bâtiments sont des systèmes complexes, les occurrences de pannes peuvent entraîner une détérioration de l'efficacité énergétique ainsi que du confort thermique pour les occupants à l'intérieur des bâtiments. Pour résoudre ce problème, nous avons élaboré une stratégie de diagnostic des dysfonctionnements et une stratégie de contrôle adaptatif des défauts basé sur le modèle économique ; les résultats en simulation ont été obtenus sur le bâtiment de référence. En outre, l'application des solutions proposées peut permettre de relever des défis ambitieux en particulier dans le cas de bâtiments à grande échelle. Dans la partie finale de cette thèse, nous nous concentrons sur le contrôle économique des bâtiments à grande échelle en formulant une approche novatrice du contrôle prédictif de mode réparti. Cette formule de contrôle distribué présente de nombreux avantages tels que l'atténuation de la propagation des défauts, la flexibilité dans la maintenance du bâtiment et les stratégies simplifiées de contrôle du plug-and-play. Enfin, une attention particulière est accordée au problème d'estimation des mesures dont le nombre est limité sur des bâtiments à grande échelle. Les techniques d'estimation avancées proposées sont basées sur les méthodologies de l'horizon mobile. Leur efficacité est démontrée sur les systèmes de construction de référence / Since the last two decades, there has been a growing awareness about the climate change and global warming that has instigated several Directorate initiatives from various administrations. These initiatives mainly deal with controlling greenhouse gas emissions, use of non-conventional energy resources and optimization of energy consumption in the existing systems. The European Union has proposed numerous projects under FP7 framework to achieve the energy savings up to 20% by the year 2020. Especially, stated by the Energy Efficiency Directive, buildings are majorly responsible for 40% of energy resources in Europe and 36% of CO2 emission. Hence a class of projects in the FP7 framework promotes the use of smart technology in the buildings and the streamline existing rules. Energy IN TIME is one of the projects focused on developing a Smart Energy Simulation Based Control method which will reduce the energy consumption in the operational stage of existing non-residential buildings. Essentially, this thesis proposes several novel solutions to fulfill the project objectives assigned to the University of Lorraine. The developed solutions under this project should be validated on the demonstration sites from various European locations. We design a general benchmark building framework to emulate the behavior of demonstration sites. This benchmark building framework serves as a test bench for the validation of proposed solutions given in this thesis work. Based on the design of benchmark building layout, we present an economic control formulation using model predictive control minimizing the energy consumption. This optimal control has maintenance-aware control properties. Furthermore, as in buildings, fault occurrences may result in deteriorating the energy efficiency as well as the thermal comfort for the occupants inside the buildings. To address this issue, we design a fault diagnosis and fault adaptive control techniques based on the model predictive control and demonstrate the simulation results on the benchmark building. Moreover, the application of these proposed solutions may face great challenges in case of large-scale buildings. Therefore, in the final part of this thesis, we concentrate on the economic control of large-scale buildings by formulating a novel approach of distributed model predictive control. This distributed control formulation holds numerous advantages such as fault propagation mitigation, flexibility in the building maintenance and simplified plug-and-play control strategies, etc... Finally, a particular attention is paid to the estimation problem under limited measurements in large-scale buildings. The suggested advanced estimation techniques are based on the moving horizon methodologies and are demonstrated on the benchmark building systems

Direct lift control for aircraft has been around in the aeronautical industry for decades but is mainly used in commercial aircraft with dedicated direct lift control surfaces. The focus of this thesis is to investigate if direct lift control is feasible for a fighter aircraft, similar to Saab JAS 39 Gripen, without dedicated control surfaces. The modelled system is an aircraft that is inherently unstable and contains nonlinearities both in its aerodynamics and in the form of limited control surface deflection and deflection rates. The dynamics of the aircraft are linearised around a flight case representative of a landing scenario. Direct lift control is then applied to give a more immediate relation from pilot stick input to change in flight path angle while also preserving the pitch attitude. Two different control strategies, linear quadratic control and model predictive control, were chosen for the implementation. Since fighter aircraft are systems with fast dynamics it was important to limit the computational time. This constraint motivated the use of specialised methods to speed up the optimisation of the model predictive controller. Results from simulations in a nonlinear simulation environment supplied by Saab, as well as tests in high-fidelity flight simulation rigs with a pilot, proved that direct lift control is feasible for the investigated fighter aircraft. Sufficient control authority and performance when controlling the flight path angle were observed. Both developed controllers have their own advantages and which strategy is the most suitable depends on what the user prioritises. Pilot workload during landing as well as precision at touch down were deemed similar to conventional control.

Cette thèse traite du problème de la chute de robots humanoïdes. L’étude consiste à découpler la stratégie de chute en une phase de pré-impact et une phase de post-impact. Dans la première, une solution géométrique permet au robot de choisir des points d’impact dans un environnement encombré. Pour ce faire, le robot réadapte sa posture tout en évident les singularités de chute et en préparant le seconde phase. La phase de post-impact utilise une commande par Programmation Quadratique (QP) qui permet d’adapter les gains Proportionnels-Dérivés (PD)des moteurs en ligne, ceci afin d’obtenir de la compliance dans les articulations. L’approche consiste à incorporer les gains de raideur et d’amortissement dans le vecteur d’optimisation du QP avec les variables habituelles que sont l’accélération articulaire et les forces de contact. Les contraintes ont été adaptées à ce nouveau QP. Enfin,comme la solution est locale, une commande de modèle prédictif sur un modèle simplifié du robot. A chaque pas du développement, plusieurs expériences et simulations ont été effectuées. / This thesis deals with the problem of humanoid falling with a decoupled strategy consisting of a pre-impactand a post-impact stages. In the pre-impact stage, geometrical reasoning allows the robot to choose appropriateimpact points in the surrounding environment –that can be unstructured and may contain cluttered obstacles,and to adopt a posture to reach them while avoiding impact singularities and preparing for the post-impact. Thepost-impact stage uses a quadratic program controller that adapts on-line the joint proportional-derivative (PD)gains to make the robot compliant, i.e. to absorb post-impact dynamics, which lowers possible damage risks.We propose a new approach incorporating the stiffness and damping gains directly as decision variables in theQP along with the usually-considered variables that are the joint accelerations and contact forces. By doing so,various constraints can be added to the QP. Finally, since the gain adaptation is local, we added a preview ona time-horizon for more optimal gain adaptation based on model reduction. At each step of the development,several experiments on the humanoid robot HRP-4 in a full-dynamics simulator are presented and discussed.

The use of robotic manipulators in industrial applications is continuously growing. Therefore, the proposal of novel kinematic architectures for robotic manipulators can be a strategy for coping with the required performance of specific tasks. On this matter, the parallel manipulators represent an alternative to fulfill this gap. The objective of this manuscript is to prove that the energy efficiency of parallel manipulators can be increased by the use of kinematic redundancy. Due to the presence of kinematic redundancy, the number of solutions to the inverse kinematics problem become infinite. Hence, a redundancy resolution scheme is required to select a suitable one among the infinite solutions. In this work, a model predictive control (MPC) based method is proposed as redundancy resolution scheme. This proposal is evaluated numerically and experimentally by comparing the energy consumption of non-redundant and kinematically redundant manipulators during the execution of pre-defined tasks. The non-redundant manipulator under study is the planar parallel 3RRR manipulator. This manipulator consists of three identical kinematic chains containing one active revolute joint and two passive revolute joints. Kinematic redundancies were added to the manipulator by including one active prismatic joint in each kinematic chain. In this way, the kinematically redundant manipulator under study is the planar parallel 3PRRR manipulator. By activating or locking the prismatic joints, up to three levels of kinematic redundancy can be evaluated. Numerical kinematic and dynamic models of the manipulators under study were derived not only for their numerical evaluation but also for the derivation of the model-based redundancy resolution scheme. Experimental data was acquired using the prototype built at the Laboratory of Dynamics at São Carlos School of Engineering at University of São Paulo. This experimental data was exploited for assessing the usability of the MPC for deriving a redundancy resolution scheme and for evaluating the impact of several levels of kinematic redundancy on the manipulator\'s energy consumption. Based on this data, one can conclude that MPC can be a suitable alternative for solve redundancy resolution problems and that the redundant parallel manipulators presented a lower energy consumption than the non-redundant one to execute the pre-defined tasks. The rate of reduction on the energy consumption achieved by the redundant manipulators varied between 6% and 60% depending on the task. Nevertheless, the numerical and experimental data presented differences in some particular cases. / O número de aplicações realizadas pelos manipuladores robóticos cresce continuamente. Assim, o desenvolvimento de novas arquiteturas para os manipuladores robóticos mais adaptadas a aplicações concretas é necessário. Destarte, os manipuladores paralelos constituem uma alternativa a ser considerada. O objetivo deste texto é provar que a eficiência energética dos manipuladores paralelos pode ser incrementada por meio da redundância cinemática. A presença de redundância cinemática implica um número infinito de soluções no problema da cinemática inversa. Logo, é precisso um esquema de resolução de redundância para escolher uma das soluções. No presente texto, um método baseado no modelo de controle preditivo (MPC), é proposto como esquema de resolução de redundância. Esta proposta é avaliada tanto numérica como experimentalmente comparando o consumo energético dos manipuladores não redundante e redundantes durante a execução de umas trajetórias predefinidas. O manipulador paralelo não redundante estudado é o 3RRR. Este manipulador é composto por três cadeias cinemáticas idênticas que incluem uma junta rotativa ativa e duas juntas rotativas passivas. Redundâncias cinemáticas foram adicionadas ao manipulador incluindo uma junta prismática ativa em cada uma das três cadeias cinemáticas, obtendo assim, o manipulador redundante 3PRRR. Ativando ou bloqueando as juntas prismáticas podem ser avaliados até três níveis de redundância cinemática. Modelos matemáticos dos manipuladores foram propostos tanto para a estabelecer uma avaliação numérica como para a dedução do esquema de resolução de redundância. Um protótipo do manipulador 3PRRR construído na Escola da Engenharia de São Carlos foi usado para realizar os experimentos. Os dados experimentais foram utilizados para comprovar a utilidade do MPC como esquema de resolução de redundância, e para avaliar os efeitos da redundância cinemática no consumo energético. Com fundamento nos resultados é possível concluir que o MPC pode ser uma alternativa adequada para resolver problemas de resolução de redundância e que os manipuladores paralelos redundantes apresentaram um menor consumo energético para realizar a mesma tarefa quando comparados aos não redundante. A taxa de redução da energia em favor dos manipuladores redundantes varia entre 6% e 60% dependendo da tarefa. Por outro lado, a análise numérica mostrou discrepâncias com a análise experimental em certas circunstâncias.

The present research study is comprised of two main parts. The first part aims at the development of a systematic system-theoretic framework that allows the derivation of optimal chemotherapy protocols for HIV patients. The proposed framework is conceptually aligned with a notion of continuous-time model predictive control of nonlinear dynamical systems, and results in an optimal way to control viral replication, while maintaining low antiretroviral drug toxicity levels. This study is particularly important because it naturally integrates powerful system-theoretic techniques into a clinically challenging problem with worldwide implications, namely the one of developing chemotherapy patterns for HIV patients that are effective and do not induce adverse side-effects. The second part introduces a new digital controller design methodology for nonlinear (bio)chemical processes, that reflects contemporary necessities in the practical implementation of advanced process control strategies via digital computer-based algorithms. The proposed methodology relies on the derivation of an accurate sampled-data representation of the process, and the subsequent formulation and solution to a nonlinear digital controller synthesis problem. In particular, for the latter two distinct approaches are followed that are both based on the methodological principles of Lyapunov design and rely on a short-horizon model-based prediction and optimization of the rate of“energy dissipation" of the system, as it is realized through the time derivative of an appropriately selected Lyapunov function. First, the Lyapunov function is computed by solving the discrete Lyapunov matrix equation. In the second approach however, it is computed by solving a Zubov-like functional equation based on the system's drift vector field. Finally, two examples of a chemical and a biological reactor that both exhibit nonlinear behavior illustrate the main features of the proposed digital controller design method.

La voiture autonome pourrait réduire le nombre de morts et de blessés sur les routes tout en améliorant l'efficacité du trafic. Cependant, afin d'assurer leur déploiement en masse sur les routes ouvertes au public, leur sécurité doit être garantie en toutes circonstances. Cette thèse traite de l'architecture de planification et de contrôle pour la conduite automatisée et défend l'idée que l'intention du véhicule doit correspondre aux actions réalisées afin de garantir la sécurité à tout moment. Pour cela, la faisabilité cinématique et dynamique de la trajectoire de référence doit être assurée. Sinon, le contrôleur, aveugle aux obstacles, n'est pas capable de la suivre, entraînant un danger pour la voiture elle-même et les autres usagers de la route. L'architecture proposée repose sur la commande à modèle prédictif fondée sur un modèle bicyclette cinématique afin de planifier des trajectoires de référence sûres. La faisabilité de la trajectoire de référence est assurée en ajoutant une contrainte dynamique sur l'angle au volant, contrainte issue de ces travaux, afin d'assurer que le modèle bicyclette cinématique reste valide. Plusieurs contrôleurs à haute-fréquence sont ensuite comparés afin de souligner leurs avantages et inconvénients. Enfin, quelques résultats préliminaires sur les contrôleurs à base de commande sans modèle et leur application au contrôle automobile sont présentés. En particulier, une méthode efficace pour ajuster les paramètres est proposée et implémentée avec succès sur la voiture expérimentale de l'ENSIAME en partenariat avec le laboratoire LAMIH de Valenciennes. / Autonomous vehicles are believed to reduce the number of deaths and casualties on the roads while improving the traffic efficiency. However, before their mass deployment on open public roads, their safety must be guaranteed at all time.Therefore, this thesis deals with the motion planning and control architecture for autonomous vehicles and claims that the intention of the vehicle must match with its actual actions. For that purpose, the kinematic and dynamic feasibility of the reference trajectory should be ensured. Otherwise, the controller which is blind to obstacles is unable to track it, setting the ego-vehicle and other traffic participants in jeopardy. The proposed architecture uses Model Predictive Control based on a kinematic bicycle model for planning safe reference trajectories. Its feasibility is ensured by adding a dynamic constraint on the steering angle which has been derived in this work in order to ensure the validity of the kinematic bicycle model. Several high-frequency controllers are then compared and their assets and drawbacks are highlighted. Finally, some preliminary work on model-free controllers and their application to automotive control are presented. In particular, an efficient tuning method is proposed and implemented successfully on the experimental vehicle of ENSIAME in collaboration with the laboratory LAMIH of Valenciennes.

Sistemas de pulverização com injeção direta possibilitam o uso de diferentes agrotóxicos em uma mesma aplicação, reduzindo o desperdício de agrotóxicos e minimizando desta forma os impactos toxicológico e ambiental relacionados com o preparo e descarte da calda. Neste trabalho foram desenvolvidos modelos matemáticos para um sistema de pulverização com injeção direta de agrotóxico, incluindo a dinâmica da concentração da calda. Também foi desenvolvida uma estratégia de controle preditivo com antecipação das taxas de aplicação para ajustar as taxas de aplicação do agrotóxico e da calda. Também, uma plataforma flexível para o desenvolvimento de pulverizadores foi projetada e construída. A sua automação foi baseada em um controlador embarcado de tempo real adequado para aplicações de controle, aquisição e temporização. Para obter os parâmetros dos modelos e avaliar a estratégia de controle ensaios de vazão e concentração para diferentes pontas de pulverização foram propostos. Com o emprego da abordagem de controle preditivo, os erros das vazões do agrotóxico e da calda ficaram abaixo do nível admissível de 5%. O uso da estratégia de antecipação das taxas de aplicação permitiu aumentar a eficiência da aplicação, reduzindo em até 40% os erros de aplicação. Resultados experimentais são apresentados para validar os modelos e mostrar a eficiência da estratégia de controle desenvolvida. / Sprayer systems with direct injection allow the use of different pesticides in a single application, reducing the waste of chemicals and thereby minimizing the toxicologic and environmental risks associated with the carrier-chemical mix preparation and discard. In this work, mathematical models for a direct chemical injection sprayer system including the dynamics of the carrier-chemical mix concentration are developed. Also, a predictive control strategy with anticipative reference of application rates was developed to adjust the carrier-chemical mix and chemical flow rates. Also, a flexible platform for the development of sprayers was designed and constructed. The automation of this platform was based on a programmable automation controller suitable for control, acquisition and timming applications. To obtain the models and analyse the control strategy, essays flow and concentration for different spray nozzles were proposed. With the use of predictive control approach, the errors of the carrier-chemical mix and chemical flow rates were lower than the admissible level of 5 %. The use of the advanced references increased the efficiency of the variable rate application, reducing up to 40 % application errors. Practical results are presented to validate the models and show the efficiency of the developed control strategy.

Increasing worldwide demand for petroleum motivates greater efficiency, safety, and environmental responsibility in upstream oil and gas processes. The objective of this research is to improve these areas with advanced control methods. This work develops the integration of optimal control methods including model predictive control, moving horizon estimation, high fidelity simulators, and switched control techniques applied to subsea riser slugging and managed pressure drilling. A subsea riser slugging model predictive controller eliminates persistent offset and decreases settling time by 5% compared to a traditional PID controller. A sensitivity analysis shows the effect of riser base pressure sensor location on controller response. A review of current crude oil pipeline wax deposition prevention, monitoring, and remediation techniques is given. Also, industrially relevant control model parameter estimation techniques are reviewed and heuristics are developed for gain and time constant estimates for single input/single output systems. The analysis indicates that overestimated controller gain and underestimated controller time constant leads to better controller performance under model parameter uncertainty. An online method for giving statistical significance to control model parameter estimates is presented. Additionally, basic and advanced switched model predictive control schemes are presented. Both algorithms use control models of varying fidelity: a high fidelity process model, a reduced order nonlinear model, and a linear empirical model. The basic switched structure introduces a method for bumpless switching between control models in a predetermined switching order. The advanced switched controller builds on the basic controller; however, instead of a predetermined switching sequence, the advanced algorithm uses the linear empirical controller when possible. When controller performance becomes unacceptable, the algorithm implements the low order model to control the process while the high fidelity model generates simulated data which is used to estimate the empirical model parameters. Once this online model identification process is complete, the controller reinstates the empirical model to control the process. This control framework allows the more accurate, yet computationally expensive, predictive capabilities of the high fidelity simulator to be incorporated into the locally accurate linear empirical model while still maintaining convergence guarantees.