New control methods are developed for the unconstrained motion and constrained force and motion control of flexible robots. The dynamic equations of the flexible robots are partitioned as pseudostatic equilibrium equations and deviations from them. The pseudostatic equilibrium considered here is defined as a hypothetical state where the tip point variables have their desired values while the modal variables are instantaneously constant. Then, the control torques for the pseudostatic equilibrium and for the stabilization of the deviation equations are formed in terms of tip point coordinates, modal variables and contact force components. The performances of the proposed methods are illustrated on a planar two-link robot and on a spatial three-link robot. Unmodeled dynamics and measurement noises are also taken into consideration. Performance of the proposed motion control method is compared with the computed torque method.

Ce travail présente une nouvelle approche basée sur l’étude de la stabilité du mouvement de systèmes continus, multivariables, non linéaires. Elle repose sur l’utilisation de la seconde méthode de Lyapunov pour le calcul d’une loi de commande de suivi de trajectoire d’un processus dont l’évolution est décrite par son équation d’état. Cette commande est réalisée à partir d’informations accessibles concernant le processus et son évolution désirée.Cette approche est étudiée dans le cas où cette commande n’est pas définie.Afin d’étudier la robustesse de cette commande, nous présentons une approche basée sur la stabilité des systèmes non linéaires par le calcul des systèmes majorants. Cette approche est appliquée sur les systèmes décrivant l’erreur entre le système perturbé réel présentant d’importantes imprécisions et/ou incertitudes et le modèle théorique / This work presents a new approach based on the study of the stability of motion of continuous, multivariable, nonlinear systems. It relies on the use of the second Lyapunov method for computing a control law trajectory tracking of a process whose evolution is described by the equation of state. This control is made from accessible information about the process and its desired evolution. This approach is studied in the case where the command is not defined. To investigate the robustness of this control, we present an approach based on the stability of nonlinear systems by calculating the overvaluing systems. This approach is applied to the systems describing the error between the actual perturbed system with significant inaccuracies and / or uncertainties and the theoretical model

Formation and tracking control are critical for of today's vehicle applications in and this will be true for future vehicle technologies as well. Although the general function of these controls is for data collection and military applications, formation and tracking control may be applied to automobiles, drones, submarines, and spacecraft. The primary application here is the investigation of formation keeping and tracking solutions for realistic, real-time, and multi-vehicle simulations. This research explores the creation of a predictive navigation and control algorithm for formation keeping and tracking, raw measurement data collection, and building a real-time GNSS closed HWIL testbed for simulations of different vehicles. The L1 frequency band of the Global Positioning System (GPS) constellation is used to observe and generate raw measurement data that encompasses range, pseudo-range, and Doppler frequency. The closed HWIL simulations are implemented using Spirent's Communication Global Navigation Satellite system (GNSS) 6560 and 8000 hardware simulators along with Ashtech, G-12 and DG-14, and Novetel OEM 628 receivers. The predictive navigation control is similar to other vision-based tracking techniques, but relies mainly on vector projections that are controlled by acceleration, velocity magnitude, and direction constraints to generate realistic motion. The current state of the testbed is capable of handling one or more vehicle applications. The testbed can model simulations up to 24 hours. The vehicle performance during simulations can be customized for any required precision by setting a variety of vehicle parameters. The testbed is built from basic principles and is easily upgradable for future expansions or upgrades. / Master of Science

This thesis discusses the modeling of a micro-grid with photovoltaic (PV)-wind-fuel cell (FC) hybrid energy system and its operations. The system consists of the PV power, wind power, FC power, static var compensator (SVC) and an intelligent power controller. Wind and PV are primary power sources of the system, and an FC-electrolyzer combination is used as a backup and a long-term storage system. A simulation model for the micro-grid control of hybrid energy system has been developed using MATLAB/Simulink. A SVC was used to supply reactive power and regulate the voltage of the hybrid system. To achieve a fast and stable response for the real power control, the intelligent controller consists of a Radial Basis Function Network-Sliding Mode Control (RBFNSM) and a General Regression Neural Network (GRNN) for maximum power point tracking (MPPT). The pitch angle of wind turbine is controlled by RBFNSM, and the PV system uses GRNN, where the output signal is used to control the DC/DC boost converters to achieve the MPPT.

Ce travail présente une nouvelle approche de synthèse de la commande non linéaire en suivi de trajectoire de robots manipulateurs. Malgré la richesse de la littérature dans le domaine, le problème n'a pas encore été traité de manière adéquate : en raison de l'existence inévitable dans les applications pratiques de perturbations et incertitudes telles que les forces de frottement, des perturbations externes ou les variations des paramètres il est difficile d'assurer un suivi de trajectoire de haute précision. Afin de résoudre ce problème, nous proposons tout d'abord une méthode de commande prenant en compte la performance H∞ pour le suivi de trajectoire d'un robot manipulateur. Deuxièmement, nous proposons un nouveau cadre pour la synthèse de lois de commande combinant une action anticipatrice et un retour d'état basée sur une représentation sous forme Takagi-Sugeno descripteur de la dynamique du manipulateur. Un avantage de la représentation choisie est de pouvoir simultanément simplifier le calcul des gains de commande à l'aide de LMI de dimension réduite et de réduire la complexité du correcteur en agissant sur le nombre de règles du modèle de Takagi-Sugeno. Basé sur la théorie de la stabilité de Lyapunov, le réglage du correcteur est formulé comme un problème d'optimisation LMI (inégalité matricielle linéaire). Les résultats obtenus en simulation effectuée avec un modèle de manipulateur série développé dans l'environnement Simscape MultibodyTM de Matlab R démontrent clairement l'efficacité de la méthode proposée en comparaison avec le régulateur PID et la commande CTC (Computed Torque Control). / This work presents a new design approach for trajectory tracking control of robot manipulators. In spite of the rich literature in the field, the problem has not yet been addressed adequately due to the lack of an effective control design. In general, it is difficult to adopt design to achieve high-precision tracking control due to the uncertainties in practical applications, such as friction forces, external disturbances and parameter variations. In order to cope this problem, we propose first control with H∞ performance to reference trajectory tracking control of two degrees of freedom robot. Secondly, we propose a new design framework with parametric uncertainties and unknown disturbances by using the feedback and the feedforward controllers. Using the descriptor Takagi-Sugeno systems, the design goal is to achieve a guaranteed tracking performance while signicantly reducing the numerical complexity of the designed controller through a robust control scheme. Based on Lyapunov stability theory, the control design is formulated as an LMI (linear matrix inequality) optimization problem. Simulation results carried out with a high-fidelity serial manipulator model embedded in the Simscape MultibodyTM environment of MatlabR clearly demonstrate the effectiveness of the proposed method by comparing with PID controller and computed torque controller.