TY - GEN
T1 - Pigeon-Inspired optimization approach to multiple UAVs formation reconfiguration controller design
AU - Zhang, Xiaomin
AU - Duan, Haibin
AU - Yang, Chen
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2015/1/12
Y1 - 2015/1/12
N2 - This article introduces a controller for solving the problem of multiple unmanned aerial vehicles (UAVs) formation reconfiguration. Under the constraints of terminal status and of control action energy, the controller aims to find the best values of UAV's inputs (including thrust, load factor, bank angle) to accomplish the task. The basis of our controller is a method which combines PIO with CPTD. Pigeon-Inspired optimization (PIO) is a novel algorithm. It has been proposed and applied in engineering problems by following the inspirational precious works. CPTD is a method called control parameterization and time discretization. Besides, we use a mathematical model to get a function which can evaluate the reconfiguration effects. Finally, to verify the validity of our controller, comparative experiments between PIO and particle swarm optimization (PSO) are conducted. The comparative results demonstrate that our proposed controller embedded with PIO is much better than the one with PSO.
AB - This article introduces a controller for solving the problem of multiple unmanned aerial vehicles (UAVs) formation reconfiguration. Under the constraints of terminal status and of control action energy, the controller aims to find the best values of UAV's inputs (including thrust, load factor, bank angle) to accomplish the task. The basis of our controller is a method which combines PIO with CPTD. Pigeon-Inspired optimization (PIO) is a novel algorithm. It has been proposed and applied in engineering problems by following the inspirational precious works. CPTD is a method called control parameterization and time discretization. Besides, we use a mathematical model to get a function which can evaluate the reconfiguration effects. Finally, to verify the validity of our controller, comparative experiments between PIO and particle swarm optimization (PSO) are conducted. The comparative results demonstrate that our proposed controller embedded with PIO is much better than the one with PSO.
UR - http://www.scopus.com/inward/record.url?scp=84922570847&partnerID=8YFLogxK
U2 - 10.1109/CGNCC.2014.7007594
DO - 10.1109/CGNCC.2014.7007594
M3 - Conference contribution
AN - SCOPUS:84922570847
T3 - 2014 IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2014
SP - 2707
EP - 2712
BT - 2014 IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2014
Y2 - 8 August 2014 through 10 August 2014
ER -