Controlling an unmanned quad-rotor aerial vehicle with model parameter uncertainty and actuator failure. (2016)

• Record Type: Journal Article
• Authors: Alshbatat, Abdel Ilah Nour; Dong, Liang; Vial, Peter James
• Is Part Of: International journal of intelligent systems technologies and applications. Volume 15:Number 4(2016)
• Page Start: 295
• Page End: 322
• Publication Date: 2016
• Subjects: MRAC -- model reference adaptive control -- LQR -- linear quadratic regulator -- quad-rotor UAVs -- unmanned aerial vehicles -- Lyapunov stability -- UAV control -- model parameter uncertainty -- actuator failure -- kinematics -- dynamics -- thrust loss -- controller design -- simulation -- propeller damage -- rotor control; Artificial intelligence -- Periodicals; Intelligent control systems -- Periodicals; 006.3
• Languages: English
• ISSNs: 1740-8865

Abstract

It is challenging to stabilise an unmanned quad-rotor aerial vehicle when a dynamic change in its model parameters or failure of its actuator occurs. In this paper, a quad-rotor unmanned aerial vehicle (UAV) is controlled based on model reference adaptive control (MRAC) and a linear quadratic regulator (LQR). The kinematics and dynamics of the quad-rotor are calculated, and Lyapunov's direct stability method is used to design the MRAC. In order to evaluate the performance of the adaptive control algorithms in the presence of thrust loss that may occur due to component failure or physical damage, a real quad-rotor is built from scratch using commercial components. Both controllers are designed, implemented and tested using AVR microcontrollers. Comparison is made between the controllers under normal and faulty situations and the effectiveness of the proposed control strategy is verified. Simulation and experimental results show that both controllers have satisfactory performance under normal conditions and even in the presence of the partial loss of thrust that may occur due to the loss of control effectiveness in one of the rotors or the damage of one propeller, superior system performance is observed using the proposed MRAC controller.