The core objective of this research is to develop a comprehensive understanding of Floating Offshore Wind Turbines' (FOWTs') dynamic behavior and design robust control strategies to enhance their performance and reliability in offshore environments. This begins with a detailed dynamic model of FOWTs, accounting for complex interactions between the wind field and the turbine, leading to transient motions and structural loadings. The model's novelty lies in its use of an acausal modeling environment, facilitating reconfigurability, reuse, and plug-and-play features for Control Co-Design (CCD), where system design and control development occur in parallel, optimizing performance. A significant contribution of this work is applying the Quantitative Feedback Theory (QFT) framework to FOWT control systems. QFT is a robust control methodology that enables the synthesis of controllers to accommodate uncertainties and disturbances. QFT-based controllers are designed to ensure stable and efficient FOWT operation under varying environmental conditions. Specific goals include reducing vibrational loads from blade root bending moments, tower fore-aft oscillations, and tower side-to-side oscillations, in addition to wind turbine speed control. The main actuations used are generator torque in addition to collective and individual blade pitch actuations. To validate the proposed modeling and control strategies, comprehensive simulations are performed. The dynamic model of FOWTs is rigorously validated against industry-standard tools such as OpenFAST and experimental data from a prototype FOWT. This validation ensures the model's accuracy and reliability, providing confidence in its suitability for control system design and analysis. The validation process includes achieving accurate aerodynamic characteristics, joint force predictions, and blade pitch predictions during operation. The findings of this research significantly advance floating offshore wind turbine technology. By enhancing the understanding of FOWT dynamics and providing robust control solutions, this work contributes to optimizing offshore wind energy generation, reducing the cost of energy production, and improving the sustainability of energy infrastructure.

Afin de satisfaire les besoins futurs en énergie et de réduire l’impact environnemental, l’application de l’énergie renouvelable propre a été récemment reconsidérée. Dans ce contexte, un intérêt croissant pour le système d’alimentation isolé a été mesuré.Le besoin de topologies de faible puissance alimentées par un générateur photovoltaïque, évitant l’utilisation de transformateur, accentue l’étude de systèmes d’alimentation autonomes de basse tension. D’où la nécessité d’étudier les stratégiesde contrôle associées garantissant la stabilité, la fiabilité et l’efficacité.À mesure que les systèmes d’alimentation autonome deviennent plus complexes, les non-linéarités jouent un rôle de plus en plus important dans le comportement du système. La modélisation doit refléter avec précision la dynamique des composants et du système. En outre, les outils d’analyse des systèmes dynamiques devraient être fiable, même dans différents régimes de fonctionnement, fournissant des prédictions précises du comportement de ces derniers. Ce travail est consacré à l’étude d’un système photovoltaïque autonome. La structure proposée se compose d’un panneau photovoltaïque, d’un hacheur et d’une charge connectée en cascade via un bus continu. Les efforts de recherche se concentrent sur le processus de modélisation et l’analyse de stabilité du système. Une implémentation avec une description complète du modèle est ainsi détaillée est validé epar des résultats de simulation. Après avoir donné l’état de l’art, le manuscrit est divisé en quatre parties. Ces parties sont dédiées à la modélisation d’une installation photovoltaïque, à l’amélioration de la simulation numérique, et à l’étude de dynamique de ce système sous contrôles numériques.La thèse présente un aperçu des modèles de générateurs photovoltaïques. Ensuite,un modèle électrique modifié du panneau photovoltaïque est proposé. Nous avons également détaillé le processus de modélisation de l’installation photovoltaïque.Un solveur amélioré de modèle Differential-Algebraic Equations (DAEs) est ensuite développé. Une dixième approche de modélisation est aussi présentée. Nous avons également décrit le système photovoltaïque par un modèle discret simplifié. Ensuite, l’analyse de stabilité du système étudié est détaillée. En outre, nous avons étudié le comportement chaotique qui apparaît dans l’installation photovoltaïque basée sur le hacheur à deux cellules. Le but de la dernière partie est de montrer comment stabiliser l’orbite chaotique du système. Enfin, pour atteindre cet objectif, la commande par retour d’état retardé Time-Delayed Feedback Control (TDFC) est appliquée. / In order to satisfy future energy requirement and reduce environmental impact, application of clean renewable energy, have been reconsidered recently. In this context, a growing interest in isolated power system has been observed. The need of low power topologies fed by photovoltaic array avoiding the use oftransformer open the study of small-scale stand-alone power system. Hence, theneed to study the associated control design strategies ensuring stability, reliability and high efficiency.As systems become more complex, nonlinearities play an increasingly importantrole in stand-alone power system behaviour. Modeling must accurately reflect component and system dynamics. In addition, analysis tools should continue to workreliably, even under various system conditions, providing accurate predictions of systems behaviour.This work is devoted to the study of a stand-alone photovoltaic power system.The proposed structure consists on photovoltaic array, a dc-dc buck converter, anda load connected in cascade through a dc bus. The research efforts focus on themodeling process and stability analysis, which leads to an implementation with acomprehensive description validated through simulation results.After giving the state-of-the-art in second chapter, the manuscript is divided into four chapters. These parts are dedicated to photovoltaic plant modeling, the numeric simulation improvements and dynamic investigation of the photovoltaic system under digital controls.The thesis presents an overview of the photovoltaic generator models. Then, amodified photovoltaic array model is proposed. We also detailed the photovoltaic plant modeling process. An improved Differential-Algebraic Equations (DAEs)solver is then investigated. We also described the photovoltaic system by a simplified discrete model. Then, the dynamic stability analysis is detailled. In addition,we have studied the chaotic behaviour that appears in the photovoltaic plant basedon the two-cell dc-dc buck converter.The aim of the last part is to show, using control theory and numerical simulation,how to apply a method to stabilize the chaotic orbit. Finally, to accomplish this aim, a time-delayed feedback controller is used.

This diploma thesis deals with creation of elektromechanical model in Modelica language which is subsequently imported into LabVIEW environment. The Modelica language, LabVIEW graphical programming tool and Functional Mock-up Interface 2.0 standard are described in the introduction of this thesis. Functional Mock-up Interface is a tool independent standard witch, defines a standardized interface to ModelExchange and Co-simulation of complex system components. The model of electromechanical system was created based on Functional Mock-up Interface standard. Part of the work focuses on the Functional Mock-up Unit storage possibilities and LabVIEW support to import models of this type. The imported model was simulated and tested in this environment. Finally, the instance of Functional Mock-up Unit was connected with LabVIEW FPGA target for the purpose of model HIL simulation on CompactRIO platform.

This thesis solves the use of Modelica models in Matlab/Simulink enviroment. The first part is focused on Modelica language and Functional Mock-up Interface, a standard way for model exchange and co-simulation of dynamic models, which is supported by most Modelica oriented tools. Based on this standard FMUtoolbox was created and it provides the ability to import and simulate models exported as Functional Mock-up Unit. The tool provides a Simulink block, graphical and command-line interface.