Robot Analysis and Control
Controlling a drone: Comparison between a based model method and a fuzzy inference system
Applied Soft Computing
Backstepping Approach for Controlling a Quadrotor Using Lagrange Form Dynamics
Journal of Intelligent and Robotic Systems
Image-based visual servo control of the translation kinematics of a quadrotor aerial vehicle
IEEE Transactions on Robotics - Special issue on rehabilitation robotics
An integral predictive/nonlinear H∞ control structure for a quadrotor helicopter
Automatica (Journal of IFAC)
Output feedback control of a quadrotor UAV using neural networks
IEEE Transactions on Neural Networks
Stabilization and Trajectory Tracking of a Quad-Rotor Using Vision
Journal of Intelligent and Robotic Systems
Vision Based Position Control for MAVs Using One Single Circular Landmark
Journal of Intelligent and Robotic Systems
Journal of Intelligent and Robotic Systems
A Practical Visual Servo Control for an Unmanned Aerial Vehicle
IEEE Transactions on Robotics
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In this paper an adaptive control scheme along with its simulation, and its implementation on a quadrotor are presented. Parametric and non- parametric uncertainties in the quadrotor model make it difficult to design a controller that works properly in various conditions during flight time. Decentralized adaptive controller, which is synthesized based on improved Lyapunov-based Model Reference Adaptive Control (MRAC) technique, is suggested to solve the problem. The proposed control scheme does not need knowing the value of any physical parameter for generating appropriate control signals, and retuning the controller is not required for different payloads. An accurate simulation that includes empirical dynamic model of battery, sensors, and actuators is performed to validate the stability of the closed loop system. The simulation study simplifies implementation of the controller on our real quadrotor. A practical algorithm is proposed to alleviate and accelerate the tuning of controller parameters. The controller is implemented on the quadrotor to stabilize its attitude and altitude. Simulation and experimental results demonstrate the efficiency and robustness of the proposed controller.