Doctorat

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Author: search.filters.author.Boushaki, Razika(Directeur de thèse)Has files: No

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    Adaptive control of drone by rejection of disturbances
    (Université M'Hamed Bougara Boumerdès : Faculté de Technologie, 2025) Hadid, Samira; Boushaki, Razika(Directeur de thèse)
    Quadrotor or Unmanned Aerial Vehicles (UAVs), a popular type, use four propellers for flight and are gaining popularity due to their versatility and ease of use. Interest in controlling UAVs has significantly increased recently. This work focuses on the control and trajectory planning challenges of quadrotors. While many studies address disturbances and faults, the inherent underactuation (four inputs controlling six degrees of freedom) makes precise control and trajectory tracking difficult, particularly in complex scenarios. The research aims to improve quadrotor control in challenging environments. The Newton-Euler method is used in this work to develop the quadrotor's dynamic model. Then, an exploration using Dyna-Q reinforcement learning for autonomous quadrotor navigation in complex environments. The algorithm allows the quadrotor to learn optimal flight paths through trial and error. In addition, this thesis presents an in-depth investigation into improving the autonomy and control capabilities of quadrotors. The focus is on developing and implementing various linear and nonlinear control strategies to regulate the behavior of quadrotor UAVs. Each control strategy is carefully adjusted and fine-tuned to achieve the desired dynamic response and stability during quadrotor flight. Following that, we provide a comparison of the designed controllers. It then focuses on comparing the performance of fractional-order PID (FOPID) and sliding mode control (SMC) for trajectory tracking, emphasizing robustness against disturbances and nonlinearities. Furthermore, the research introduces an intelligent trajectory planning system using Dyna-Q learning to enable autonomous navigation and obstacle avoidance in complex environments, enhancing quadrotor adaptability and responsiveness for various applications. Extensive simulations validate the proposed control strategies and trajectory planning. Overall, this study contributes significantly to the field of quadrotor control and autonomy, providing valuable insights and solutions for improving flight stability and enabling secure and efficient operations in a variety of real-world scenarios.
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    Feedback linearization control of multivariable and nonlinear systems (UAV)
    (2022) Loubar, Hocine; Boushaki, Razika(Directeur de thèse)
    ors have been widely used for many applications; furthermore, various techniques for their modelling and control have been proposed. Among the challenges encountered in the design of controllers for a quadrotor is the fact that it is a highly coupled and nonlinear multivariable system. It is also nown as being an under-actuated system because it uses four actuators to control six degrees of freedom. In this work, the nonlinear dynamic model of the quadrotor is formulated using the Newton-Euler method. Then different linear and nonlinear control techniques for quadrotor trajectory tracking are investigated. First, SMC and PD controllers for linear and nonlinear trajectory tracking of the quadrotor are implemented, and genetic algorithm is used to optimize the controller parameters according to different objective functions. Both techniques are evaluated and compared in terms of trajectory tracking capabilities, dynamic performance, and the effect of possible disturbances. Then, backstepping and gain scheduling ontrol techniques are designed in order to control the altitude and attitude of the quadrotor, in the absence of disturbances and also in a windy environment. Finally, a new feedback nearization approach based on coordinate transformation and state feedback, is proposed. In this approach, the state space description of nonlinear quadrotor system is transformed into a linear quasi block controller decoupled form, then eigenstructure assignment using state feedback is applied. The proposed approach is used to control a quadrotor, in order to assess its performance in terms of trajectory tracking capabilities, time response performance, robustness and robust stability. The simulation is carried out using MATLAB/Simulink software.