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This contribution presents a non-linear control of a hybrid pumping system supplied with a photovoltaic generator and a battery. This system is employed for delivering a continuous volume of water whatever the climatic conditions. In the DC side, a boost converter is controlled with the indirect double integral sliding mode controller (DISMC) for maximum power point tracking (MPPT). The DISMC is suitable for MPPT because it gives a fast response and reduces the amplitude of power oscillations. Then, a bidirectional buck-boost converter is adopted to ensure the energy management between the battery and the DC-bus, and this converter is controlled with integral sliding mode control (ISMC) theory. The non-linear predictive control (NPC) is chosen to drive an induction motor (IM), the NPC is known by its fast dynamic and high capacity to reject disturbances. The hybrid system is modelled in MATLAB/Simulink software. During simulations, the DISMC-MPPT is compared with other techniques such as sliding mode controller (SMC) MPPT and integral SMC MPPT, the DISMC provides the best tracking performances under different irradiances. Moreover, the designed controller for the bidirectional converter regulates the DC-link voltage with better performances than the classical PI controller. Lastly, the NPC regulates the speed of the IM with high robustness.

Model Predictive Control (MPC) is a modern technique that, nowadays, encapsulates different optimal control techniques. For the case of non-linear dynamics, many possible variants can be developed which can lead to new control algorithms. In this manuscript a novel generic control system method is presented. This method can be applied to control, in an optimal way, different systems having non-linear dynamics. Particularly, in this paper, the proposed technique is presented in the context of developing a control system for autonomous flight of UAVs. This technique can be used for different types of aerial vehicles having any type of generic non-linear dynamics. The presented method is based on the use of iteratively defined optimal candidate state-space trajectories in global state-space. The method uses a generalized linearization process which, opposite to standard methods, does not need to be predefined in a certain equilibrium state but instead it is performed along any arbitrary state. The technique allows the inclusion of constraints with ease. The presented technique is used as a centralized control system unit that is able to control the full aircraft dynamics without the need of decoupling the system in different reduced modes. The technique is tested by making a Cessna 172 airplane model to perform the following autonomous unmanned maneuvers: climbing at constant speed to a desired altitude, heading change to a desired flight direction, and, coordinate turn. Fil: Murillo, Marina Hebe. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentina Fil: Limache, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentina Fil: Rojas Fredini, Pablo Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentina Fil: Giovanini, Leonardo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina

Fil: Murillo, Marina Hebe. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina. Fil: Murillo, Marina Hebe. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina. The main objective of this thesis involves the design of control systems for flight and navigation of autonomous unmanned aerial vehicles (UAVs), as well as the use and development of a simulation, visualization and flight control platform that allows the validation and evaluation of them. Unmanned aerial vehicles have the capabilty to fly without aircrew on board. They have different shapes, configurations and are small in size. They are clasified into two groups: those with the ability to perform tasks without human intervention (autonomous); and those which are controlled remotely by a human operator. In order to fly autonomously, it is essential that UAVs have an adequate attitude and navigation control system. The attitude control computes the deflection values that the aerodynamic surfaces and the propulsion column must have in order to control the orientation and the velocity of the vehicle. The navigation control determines the navigation trajectory that the UAV must follow. The design of the attitude and navigation control systems was posed from two different perspectives, one unified and other decoupled. The first one refers to the use of a single controller to congtrol both dynamic and navigation. The second one refers to the decouple of the control system into two independent controllers, one to control the attitude and the other to compute the navigation trajectories. El objetivo principal de la presente tesis involucra el diseño de sistemas de control para el vuelo y navegación de vehículos aéreos no tripulados (UAVs) autónomos, como así también la utilización y desarrollo de una plataforma de simulación, visualización y control de vuelo que permite la validación y evaluación de los mismos. Los vehículos aéreos no tripulados son vehículos capacitados para volar sin tripulación a bordo. Los mismos poseen diversas formas, configuraciones y son de reducido tamaño. Se clasifican en dos grandes grupos: aquellos que cuentan con la capacidad de realizar misiones sin intervención humana (autónomos); y aquellos controlados por un operador humano de manera remota. Para que los UAVs puedan volar autónomamente, es indispensable que los mismos cuenten con un adecuado sistema de control de actitud y de navegación. El control de actitud se encarga de computar los valores de deflexiones que deben tomar las superficies aerodinámicas y la columna de propulsión para controlar la orientación y velocidad del vehículo. El control de navegación se encarga de determinar la trayectoria de navegación que el UAV debe seguir. El diseño de los sistemas de control de actitud y de navegación se planteó desde dos perspectivas diferentes, una unificada y otra desacoplada. La primera se refiere a la utilización de un único controlador para controlar tanto dinámica como navegación. La segunda se refiere al desacople del sistema de control en dos controladores independientes, uno para controlar la actitud y otro para obtener trayectorias de navegación. Consejo Nacional de Investigaciones Científicas y Técnicas

This thesis deals with the control of closed microalgal photobioreactor. Mathematical modeling and model parameters identification are particularly approached. The kinetics and light transfer model parameters were obtained by fitting the experimental data acquired along the exponential phase of batch cultivation of Porphyridium purpureum under different conditions in the photobioreactor (2.5 liters). Biomass is one of the most valuable variables to control. Because biomass concentration is very difficult to measure on-line, a software sensor for its estimation is proposed. An extended Kalman filter (EKF) is developed, based on a dynamic process model in combination with total inorganic carbon measurement within an algorithm of state observation. This software sensor leads to good results and was experimentally validated in a new bubble column photobioreactor (9.6 liters) which carried different probes and sensors necessary to implement a control system. Several control strategies for microalgae culture were also proposed: non-linear and linear controllers, PID controller, generic model controller (GMC), input-output linerarizing controller and non-linear predictive controller. We illustrated our approaches with numerical simulations which allowed us to choose the most successful strategies and to validate them on the instrumented photobioreactor., Cette thèse porte sur la commande d'un photobioréacteur continu pour la culture des microalgues. La modélisation du système et l'identification des paramètres du modèle ont été particulièrement abordées. Les paramètres cinétiques et de transfert de l'énergie lumineuse ont été obtenus à partir des données acquises le long de la phase exponentielle de la culture de Porphyridium purpureum en mode batch sous différentes conditions expérimentales dans un photobioréacteur de 2,5 litres. La concentration en biomasse est la quantité physique la plus importante à réguler. Puisque elle n'est pas toujours facile à mesurer en ligne, un capteur logiciel permettant d'estimer la quantité de biomasse produite à partir des mesures en ligne est proposé. Il s'agit d'un filtre de Kalman étendu (EKF) qui combine le modèle du système avec la mesure de la concentration du carbone inorganique total et d'autres variables physiques (pH, intensité lumineuse,...) afin d'estimer en ligne la concentration de la biomasse. Ce capteur logiciel a été validé expérimentalement en utilisant un nouveau photobioréacteur de 9,6 litres de type colonne à bulles, équipé de plusieurs dispositifs destinés à mettre en place un système de commande et de régulation, et de techniques de mesure permettant d'accéder à l'évolution des principales variables. Plusieurs démarches pour la commande de la culture de microalgues ont été également proposées : commande non-linéaire et linéaire, régulation par PID, commande par modèle générique GMC, commande linéarisante par retour d'état et commande prédictive non-linéaire. Ces différentes commandes ont été mises oeuvre en simulation ce qui nous a permis de choisir les stratégies les plus performantes et de les valider sur le photobioréacteur instrumenté.

[EN] This work focuses on development of control algorithms by incorporating energy and water consumption to maintain climatic conditions in greenhouse. Advanced control algorithms can supply solutions to modern exploitations. The new developments usually require accurate models (probably multivariable and non-linear ones) and control methodologies capable of using these models. As an additional requirement it is important for the final application to be easy to use, so advanced control will not mean an increase in complexity of the manipulation of the installation. This article shows an alternative to classical climate control. It is based on two fundamental elements: an accurate non-linear model and a model-based predictive control (MBPC) that incorporate energy and water consumption. Genetic algorithms (GAs) play a key role in these two elements because functions to solve are non-convex and with local minima. First of all GAs supply a way to adjust the non-linear model parameters obtained from first principles, and finally GAs open the possibility of using non-linear model in the MBPC and of establishing a flexible cost index to minimize energy and water consumption. The results on a plastic greenhouse with arch-shaped roofs and for Mediterranean area are presented, important reduction in energy and water used in the cooling system (nebulization) is obtained. (c) 2006 Elsevier B.V. All rights reserved., Partially supported by MEC (Spanish government) and FEDER funds: projects DPI2004-8383-C03-02 and DPI2005-07835.

In this work a MIMO non-linear predictive controller was developed for an extractive alcoholic fermentation process. The internal model of the controller was represented by two MISO Functional Link Networks (FLNs), identified using simulated data generated from a deterministic mathematical model whose kinetic parameters were determined experimentally. The FLN structure presents as advantages fast training and guaranteed convergence, since the estimation of the weights is a linear optimization problem. Besides, the elimination of non-significant weights generates parsimonious models, which allows for fast execution in an MPC-based algorithm. The proposed algorithm showed good potential in identification and control of non-linear processes.Neste trabalho um controlador preditivo não linear multivariável foi desenvolvido para um processo de fermentação alcoólica extrativa. O modelo interno do controlador foi representado por duas redes do tipo Functional Link (FLN), identificadas usando dados de simulação gerados a partir de um modelo validado experimentalmente. A estrutura FLN apresenta como vantagem o treinamento rápido e convergência garantida, já que a estimação dos seus pesos é um problema de otimização linear. Além disso, a eliminação de pesos não significativos gera modelos parsimoniosos, o que permite a rápida execução em algoritmos de controle preditivo baseado em modelo. Os resultados mostram que o algoritmo proposto tem grande potencial para identificação e controle de processos não lineares.