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 -Download RIS file
00000nam^a2200301^i^4500 | |||
001 | 7224888 | ||
005 | 20181113145410.0 | ||
008 | 160524s2016------------------------eng-- | ||
020 | a 978-1-4673-8691-3 | ||
022 | a 1844-7872 | ||
024 | a 000390997900078 2 wos | ||
024 | a 1854/LU-7224888 2 handle | ||
040 | a UGent | ||
245 | a AR.Drone UAV control parameters tuning based on particle swarm optimization algorithm | ||
260 | c 2016 | ||
520 | a 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. | ||
598 | a P1 | ||
700 | a Mac Thi, Thoa u UGent 0 000141057501 0 802002036834 0 978565687555 9 2D5F88B4-42A4-11E4-8378-3F18B5D1D7B1 | ||
700 | a Copot, Cosmin u UGent 0 000070928622 0 802001569820 0 974272123005 9 3DF4B582-F0EE-11E1-A9DE-61C894A0A6B4 | ||
700 | a Duc, Trung Tran | ||
700 | a De Keyser, Robain u TW08 0 801000334204 9 F3BA6A3E-F0ED-11E1-A9DE-61C894A0A6B4 | ||
650 | a Technology and Engineering | ||
773 | t IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR) g PROCEEDING OF 2016 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION, QUALITY AND TESTING, ROBOTICS (AQTR) . 2016. p.475-480 q :<475 | ||
856 | 3 Full Text u https://biblio.ugent.be/publication/7224888/file/7224908 z [open] y AR.Drone_UAV_control_parameters_tuning_based_on.pdf | ||
920 | a confcontrib | ||
Z30 | x EA 1 TW08 | ||
922 | a UGENT-EA |
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