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Intelligent Controller Design for Quad-Rotor Stabilization in Presence of Parameter Variations
Doukhi, Oualid,Fayjie, Abdur Razzaq,Lee, Deok Jin Hindawi Limited 2017 Journal of advanced transportation Vol.2017 No.-
<P>The paper presents the mathematical model of a quadrotor unmanned aerial vehicle (UAV) and the design of robust Self-Tuning PID controller based on fuzzy logic, which offers several advantages over certain types of conventional control methods, specifically in dealing with highly nonlinear systems and parameter uncertainty. The proposed controller is applied to the inner and outer loop for heading and position trajectory tracking control to handle the external disturbances caused by the variation in the payload weight during the flight period. The results of the numerical simulation using gazebo physics engine simulator and real-time experiment using AR drone 2.0 test bed demonstrate the effectiveness of this intelligent control strategy which can improve the robustness of the whole system and achieve accurate trajectory tracking control, comparing it with the conventional proportional integral derivative (PID).</P>
Autonomous UAV for Rescue Applications in Unknown Degraded Environments
Oualid Doukhi,Sabir Hossain,Amir Ramezani Dooraki,Jo Yeonho,Deok-Jin Lee 대한기계학회 2021 대한기계학회 춘추학술대회 Vol.2021 No.5
Autonomous Navigation and collision avoidance (ANCA) missions represent a fundamental challenge in the robotics research field as they are usually deployed in dynamic unknown environments to perform specific missions such as rescue and environment exploration, which makes it require a high-level of autonomy and versatile decision-making capabilities. This challenge becomes even more relevant in unmanned aerial vehicles (UAV) platforms due to their limited payload and computational capabilities. This paper presents a fully autonomous aerial robotic solution for executing complex ANCA missions in unstructured unknown indoor or outdoor GPS-denied environments. The proposed system is based on the combination of a complete hardware configuration and a flexible, optimized software architecture that allows the execution of high-level missions in a fully unsupervised manner (i.e., without human intervention). The proposed approach relies on a robust monocular visual-inertial navigation system (MVINS) for full UAV state estimation in GPS-denied conditions. While the UAV is performing the exploration task, a 2D object detector runs in real-time to detect possible targets such as humans and radioactivity signs. Moreover, the detected object location was estimated, and a semantic map is generated, which contains the environment architecture and the location and ID of the detected objects. Keywords Aerial Robot, Autonomous System, Semantic Map, Sensor Fusion
Oualid Doukhi,이덕진 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.9
In this paper, a robust adaptive neural network certainty equivalent controller for a quadrotor unmanned aerial vehicle is proposed, which is applied in the outer loop for position control to directly generate the desired roll and pitch angles commands and then to the inner loop for attitude control. The newly proposed controller takes into account the vehicle’s kinematic and modelling error uncertainties which are associated with external disturbances, inertia, mass, and nonlinear aerodynamic forces and moments. The control method integrates an adaptive radial basis function neural networks to approximate the unknown nonlinear dynamics with certainty equivalent control technique, in this way leading to the fact that precise dynamic model and prior information of disturbances are not needed. The adaptation law was derived by using a Lyapunov theory to verify the stability and superiority of the new algorithms. The performance and effectiveness are also verified by carrying out several simulations. It was shown from the analysis that the altitude, position, and attitude tracking errors are converged to zero and the closed loop stability is guaranteed under extreme conditions.