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    Smooth Sliding Mode Control Based Technique of an Autonomous Underwater Vehicle Based Localization Using Obstacle Avoidance Strategy
    (Science and Technology Publications, Lda, 2023) Demim, Fethi; Rouigueb, Abdenebi; Belaidi, Hadjira; Messaoui, Ali Zakaria; Bensseghieur, Khadir Lakhdar; Allam, Ahmed; Benatia, Mohamed Akram; Nouri, Abdelmadjid; Nemra, Abdelkrim
    Navigating underwater environments presents serious challenges in control and localization technology. The successful navigation of uncharted territories requires autonomous maneuvers that achieve goals while avoiding obstacles, posing a significant problem to be addressed. Detection-based control using sensor data and obstacle avoidance technology are vital for the autonomy of Autonomous Underwater Vehicles (AUVs). This study focuses on developing a control method based on Sliding Mode Control (SMC) and utilizing an imaging sonar sensor for obstacle avoidance. The proposed approach includes a controller for pitch and depth control, enabling avoidance of stationary objects. A Gaussian potential function is employed to guide the AUV’s maneuvers and avoid obstructions. Numerous simulation results evaluate the control performance of the AUV in realistic simulation conditions, assessing accuracy and stability. The experimental in simulation results demonstrate the excellent performance of our approach in navigating various obstacles such as gentle rise, steep drop-off, and underwater walls, using seafloor environment simulation models.
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    Sliding mode controller for linear and nonlinear trajectory tracking of a quadrotor
    (Praise Worthy Prize, 2020) Loubar, Hocine; Boushaki, Razika Zamoum; Aouati, Ayoub; Bouanzoul, Mahdi
    During 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 capabilities