TY - GEN
UR - http://lib.ugent.be/catalog/pug01:7224888
ID - pug01:7224888
LA - eng
TI - AR.Drone UAV control parameters tuning based on particle swarm optimization algorithm
PY - 2016
SN - 978-1-4673-8691-3
SN - 1844-7872
PB - 2016
AU - Mac Thi, Thoa UGent 000141057501 802002036834
AU - Copot, Cosmin UGent 000070928622 802001569820
AU - Duc, Trung Tran
AU - De Keyser, Robain
AB - In this paper, a proposed particle swarm optimization called multi-objective particle swarm optimization (MOPSO) with an accelerated update methodology is employed to tune Proportional-Integral-Derivative (PID) controller for an AR.Drone quadrotor. The proposed approach is to modify the velocity formula of the general PSO systems in order for improving the searching efficiency and actual execution time. Three PID control parameters, i.e., the proportional gain K-p, integral gain K-i and derivative gain K-d are required to form a parameter vector which is considered as a particle of PSO. To derive the optimal PID parameters for the Ar.Drone, the modified update method is employed to move the positions of all particles in the population. In the meanwhile, multi-objective functions defined for PID controller optimization problems are minimized. The results verify that the proposed MOPSO is able to perform appropriately in Ar.Drone control system.
ER -