Publications Scientifiques
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Item Linear and nonlinear control design for a quadrotor(2025) Hadid, Samira; Boushaki Zamoum, Razika; Refis, YoucefIn the current study, the quadrotor's nonlinear dynamic model is developed using the Newton-Euler approach. Following that, several nonlinear and linear control strategies for tracking the quadrotor's trajectory are applied. First, by employing distinct controllers for each output variable, direct application of the linear proportional integral derivative (PID) controller to the nonlinear system is realized. This system may also be linearized about an operational point to generate linear controllers, according to the linear quadratic regulator (LQR) demonstration. Nevertheless, in practice, the system dynamics may not always be accurately reflected by this linear approximation and may even be relatively wasteful. Nonlinear regulators, including the feedback linearization (FBL) controller, sliding mode controller (SMC), and modified sliding mode controller (MSMC), perform better in such situations. The trajectory tracking capabilities, dynamic performance, and potential disruption impact of both methods are evaluated and compared. The FBL with LQR was the best controller among them all. The SMC and the MSMC were also very good in tracking the trajectory.Item Modern artificial intelligence technics for unmanned aerial vehicles path planning and control(2025) Zamoum, Yasmine; Baiche, Karim; Benkeddad, Youcef; Bouzida, BrahimUnmanned aerial vehicles (UAVs) require effective path planning algorithms to navigate through complex environments. This study investigates the application of Deep Q-learning and Dyna Q-learning methods for UAV path planning and incorporates fuzzy logic for enhanced control. Deep Q-learning, a reinforcement learning technique, employs a deep neural network to approximate Q-values, allowing the UAV to improve its path planning capabilities by maximizing cumulative rewards. Conversely, Dyna Q-learning leverages simulated scenarios to update Q- values, refining the UAV’s decision-making process and adaptability to dynamic environments. Additionally, fuzzy logic control is integrated to manage UAV movements along the planned path. This control system uses linguistic variables and fuzzy rules to handle uncertainties and imprecise information, enabling real-time adjustments to speed, altitude, and heading for accurate path following and obstacle avoidance. The research evaluates the effectiveness of these methods individually, with a focus on model-free learning in a gradual training approach, and compares their performance in terms of path planning accuracy, adaptability, and obstacle avoidance. The paper contributes to a deeper understanding of UAV path planning techniques and their practical applications in various scenarios.Item Optimal control design for uncertain aerial manipulator system based on an adaptive approach(Inderscience Publishers, 2024) Riache, Samah; Kidouche, Madjid; Doghmane, Mohamed Zinelabidine; Tee, Kong FahIn this paper, an optimal controller has been proposed for an aerial manipulator (AM) consisting of a quadrotor uncertain system with a two-degrees-of-freedom robotic arm. Wherein, the dynamics of this system have been derived based on Gauss's principle. The employment of this principal has permitted the pinpoint of the inner structure of the uncertain system and its possible moves. It has kept the AM in a very precise formation to analyse its dynamics and propose the suitable control. The proposed controller is designed using an adaptive approach of the non-singular terminal sliding mode technique. The main contribution is that the proposed approach guarantees both the good tracking of the desired trajectories in finite time and the chattering effect attenuation without overestimating the switching control gains. The design does not necessitate a priori knowledge of the upper limits of disturbances; the stability of the system has been established through the utilisation of Lyapunov theory. The simulation results have proved the effectiveness and robustness of the proposed optimal nonlinear terminal sliding mode technique for such an uncertain system in comparison to the sliding mode controller.Item Backstepping Control of Drone †(MDPI, 2022) Saibi, Ali; Boushaki, Razika; Belaidi, HadjiraThis work derives the models which can be used to design and implement control laws for six degrees-of-freedom (DOF) quadrotor stability. The first part of this paper deals with the presentation of the background of quadrotor modeling; the second part describes the direct control of the drone using the backstepping control principal. This principal is based on the division of the system into several sub-systems in a cascade, which makes the control laws generated on each subsystem, in a decreasing manner, until a global control law for the whole system is generated. The simulation results for the sm controller are generated on the MATLAB/Simulink platform; the results show a good performance in both the transient and steady-state operations.Item Enhanced backstepping control for disturbances rejection in quadrotors(2022) Saibi, Ali; Belaidi, Hadjira; Boushaki, Razika; Recham, Zine Eddine; Amrouche, HafidThis work studies the issue of quadrotor trajectory tracking control in presence of disturbances and model uncertainties. The paper starts by extracting the kinematics and dynamics models of the quadrotor. This results in the motion equations, which eventually serve as a blueprint for creating the suggested smart flight control scheme. Secondly, an enhanced backstepping controller (BSC) is developed and tested to keep the quadrotor tracking the desired trajectory both in steady state and in presence of disturbances. Finally, BSC beside two other controllers: sliding mode controller (SMC) and proportional derivative controller (PDC) are implemented in MATLAB/Simulink and the obtained results are compared and conclusions are extracted. Therefore, it is established that PDC is not robust to disturbances as noise will be amplified due to the derivative term. Whereas, although SMC is robust to parameter variations and disturbances; however, it is not continuous which may affect the actuators due to the increased gains which may saturate them. In contrast, BSC requires too many tuning parameters; however, it ensures Lyapunov Stability and does not depend on the system as it does not involve cancelling system nonlinearity. Moreover, BSC results are 1017 better than the results of the two other controllers.Item Modeling and simulation of three control techniques for UAV quadrotor(IEEE, 2019) Loubar, Hocine; Zammoum Boushaki, Razika; Aribi, Yacine; Azouaou, Ait Said; Dorbane, Sedik; Kouzou, AbdellahThis paper presents the modeling of a four rotor type unmanned aerial vehicle (UAV) called the quadrotor and three techniques to control its altitude, attitude, heading and position. The dynamic model of the quadrotor is nonlinear and has been derived using Newton's and Euler's laws. The first approach is designed using a linear Proportional-Integral-Derivative (PID) control technique. The second approach is based on a nonlinear Back-stepping controller while the third one is a gain Gain-Scheduling based PID controller. The Genetic Algorithm technique has been used to get an optimal tuning for the gains and parameters of the three mentioned controllers. MATLAB/Simulink software was used to evaluate and compare the three designed control approaches in terms of the stability, the effect of possible disturbances and the dynamic performanceItem Modeling and control of UAV quadrotor(IEEE, 2019) Zammoum Boushaki, Razika; Aribi, Yacine; Loubar, Hocine; Hamza, Younes; Kouzou, AbdellahSince the advances in technologies and the ability to manufacture miniature sensors and controllers using the Micro-Electro-Mechanical Systems (MEMS) technologies, there have been a lot of advances in the Unmanned Aerial Vehicle (UAV) area. A lot of the research conducted focused on the quadrotor due to its previously mentioned advantages of easier manufacturing, compactness and maneuverability among others. a detailed description of the dynamic modelling of the Quadrotor is presented. Various control strategies like the Proportional Derivative Control, the Sliding Mode Control and the Backstepping Control methods have been elucidated and implemented in MATLAB and SIMULINK. Simulations have been carried out and the results have been presentedItem Sliding mode controller for linear and nonlinear trajectory tracking of a quadrotor(Praise Worthy Prize, 2020) Loubar, Hocine; Boushaki, Razika Zamoum; Aouati, Ayoub; Bouanzoul, MahdiDuring the last decades, Unmanned Aerial Vehicles (UAV) quadrotors 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 known 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 SMC and PD controllers are designed in order to investigate linear and nonlinear trajectory tracking capabilities of the quadrotor. Step input response tests are also performed in order to study the performance of both controllers. Chattering effect of SMC controller is minimized using the boundary layer solution technique and genetic algorithm (GA) is used to tune the parameters of both PD and SMC controllers for better performance. The simulation is carried out using MATLAB Simulink and both techniques are compared in order to evaluate their dynamic performance and tracking capabilitiesItem Robust decentralized control for a quadrotor attitude(2016) Deia, Yacine; Kidouche, Madjid; Ahriche, Aimad; Lamraoui, Oualid