Title :
Novel bioinspired stochastic tuning of a quadrotor PD controller
Author :
Merheb, Abdel-Razzak ; Noura, H.
Author_Institution :
Lebanese Int. Univ., Lebanon
Abstract :
Unmanned Aerial Vehicles (UAVs) have been attractive for years for many researchers and companies worldwide due to their commercial and military applications. The control of UAVs has been widely studied and implemented, but new techniques are yet to be explored in order to make tuning of controllers easier. In this paper, ecosystem equilibrium established in nature between different species is used to develop a novel bio-inspired stochastic search algorithm. The algorithm is then tested in offline tuning of the PD controller of a quadrotor UAV. MATLAB simulations emphasize the good performance of the proposed algorithm.
Keywords :
PD control; autonomous aerial vehicles; rotors; stochastic systems; MATLAB simulations; bioinspired stochastic search algorithm; bioinspired stochastic tuning; ecosystem equilibrium; military applications; offline tuning; quadrotor PD controller; quadrotor UAV; unmanned aerial vehicles; Aerospace electronics; Biological system modeling; Genetic algorithms; Mathematical model; PD control; Tuning; Vehicles;
Conference_Titel :
Control Conference (AUCC), 2012 2nd Australian
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-922107-63-3
