TY - GEN
T1 - Reversed Pigeon-Inspired Optimization Algorithm for Unmanned Aerial Vehicle Swarm Cooperative Autonomous Formation Reconfiguration
AU - Peng, Yalan
AU - Duan, Haibin
AU - Deng, Yimin
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - A cooperative control method for unmanned aerial vehicle (UAV) swarm cooperative autonomous formation reconfiguration based on the reversed pigeon-inspired optimization (RPIO) algorithm is proposed. Firstly, the formation controller is designed to realize UAV swarm autonomous formation reconfiguration. Secondly, following the basic idea of pigeon-inspired optimization (PIO), for optimizing the slow convergence speed and falling into local optimum, adjust the updating strategy and topological structure of standard PIO. And the reversed PIO is used to optimize the parameters of UAV swarm formation controller. Finally, through the simulation experiment, it is verified that the UAV swarm can form expectedly, keep the formation under the leader UAV's complex movement condition and reconfigure under the action of the UAV swarm autonomous formation controller proposed in this paper. The reversed PIO proposed in this paper is compared with the standard PIO, particle swarm optimization (PSO) and genetic algorithm (GA) and the results prove the effectiveness and superiority of the method proposed in this article.
AB - A cooperative control method for unmanned aerial vehicle (UAV) swarm cooperative autonomous formation reconfiguration based on the reversed pigeon-inspired optimization (RPIO) algorithm is proposed. Firstly, the formation controller is designed to realize UAV swarm autonomous formation reconfiguration. Secondly, following the basic idea of pigeon-inspired optimization (PIO), for optimizing the slow convergence speed and falling into local optimum, adjust the updating strategy and topological structure of standard PIO. And the reversed PIO is used to optimize the parameters of UAV swarm formation controller. Finally, through the simulation experiment, it is verified that the UAV swarm can form expectedly, keep the formation under the leader UAV's complex movement condition and reconfigure under the action of the UAV swarm autonomous formation controller proposed in this paper. The reversed PIO proposed in this paper is compared with the standard PIO, particle swarm optimization (PSO) and genetic algorithm (GA) and the results prove the effectiveness and superiority of the method proposed in this article.
UR - https://www.scopus.com/pages/publications/85135778560
U2 - 10.1109/ICCA54724.2022.9831958
DO - 10.1109/ICCA54724.2022.9831958
M3 - 会议稿件
AN - SCOPUS:85135778560
T3 - IEEE International Conference on Control and Automation, ICCA
SP - 377
EP - 382
BT - 2022 IEEE 17th International Conference on Control and Automation, ICCA 2022
PB - IEEE Computer Society
T2 - 17th IEEE International Conference on Control and Automation, ICCA 2022
Y2 - 27 June 2022 through 30 June 2022
ER -