Multiple UAVs Formation Flight Experiments Using Virtual Structure and Motion Synchronization

2009 ◽  
Author(s):  
Norman Li ◽  
Hugh Liu
Keyword(s):  
Formation Flight ◽  
Structure And Motion ◽  
Multiple Uavs ◽  
Motion Synchronization

Multivariable adaptive distributed leader-follower flight control for multiple UAVs formation

2017 ◽  
Vol 121 (1241) ◽  
pp. 877-900 ◽  
Author(s):  
Y. Xu ◽  
Z. Zhen
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Flight Control ◽  
Control Strategy ◽  
Formation Control ◽  
Parametric Uncertainty ◽  
Lyapunov Theory ◽  
Formation Flight ◽  
Flight Control System ◽  
Multiple Uavs

ABSTRACTThe Unmanned Aerial Vehicles (UAVs) become more and more popular due to various potential application fields. This paper studies the distributed leader-follower formation flight control problem of multiple UAVs with uncertain parameters for both the leader and followers. This problem has not been addressed in the literature. Most of the existing literature considers the leader-follower formation control strategy with parametric uncertainty for the followers. However, they do not take the leader parametric uncertainty into account. Meanwhile, the distributed control strategy depends on less information interactions and is more likely to avoid information conflict. The dynamic model of the UAVs is established based on the aerodynamic parameters. The establishment of the topology structure between a collection of UAVs is based on the algebraic graph theory. To handle the parametric uncertainty of the UAVs dynamics, a multivariable model reference adaptive control (MRAC) method is addressed to design the control law, which enables follower UAVs to track the leader UAV. The stability of the formation flight control system is proved by the Lyapunov theory. Simulation results show that the proposed distributed adaptive leader-following formation flight control system has stronger robustness and adaptivity than the fixed control system, as well as the existing adaptive control system.

${\cal H}_{\infty}$ Based Motion Synchronization in Formation Flight With Delayed Communications

2014 ◽  
Vol 61 (11) ◽  
pp. 6175-6182 ◽  
Author(s):  
Hamed Rezaee ◽  
Farzaneh Abdollahi ◽  
Heidar A. Talebi
Keyword(s):  
Formation Flight ◽  
Motion Synchronization

Design of Multi-Criteria PI Controller Using Particle Swarm Optimization for Multiple UAVs Close Formation

2010 ◽  
Vol 1 (2) ◽  
pp. 1-17
Author(s):  
Xiangyin Zhang ◽  
Haibin Duan ◽  
Shan Shao ◽  
Yunhui Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Absolute Error ◽  
Pi Controller ◽  
Formation Flight ◽  
Swarm Optimization ◽  
Formation Tracking ◽  
Multiple Uavs ◽  
On Line ◽  
Uninhabited Aerial Vehicles

Close formation flight is one of the most complicated problems on multiple Uninhabited Aerial Vehicles (UAVs) coordinated control. This paper proposes a new method to achieve close formation tracking control of multiple UAVs by applying Particle Swarm Optimization (PSO) based Proportional plus Integral (PI) controller. Due to its simple structure and effectiveness, multi-criteria PI control strategy is employed to design the controller for multiple UAVs formation, while PSO is used to optimize the controller parameters on-line. With the inclusion of overshoot, rise time, and system accumulated absolute error in the multi-criteria performance index, the overall performance of multi-criteria PI controller is optimized to be satisfactory. Simulation results show the feasibility and effectiveness of the proposed approach.

scholarly journals Autonomous Formation Flight Tests of Multiple UAVs

2010 ◽  
Vol 38 (3) ◽  
pp. 264-273 ◽  
Author(s):  
Yong-Kyu Song ◽  
Chang-Hwan Heo ◽  
Sang-Jun Lee ◽  
Jung-Han Kim
Keyword(s):  
Formation Flight ◽  
Flight Tests ◽  
Multiple Uavs

Hybrid Dec-POMDP/PID Guidance System for Formation Flight of Multiple UAVs

2021 ◽  
Vol 101 (3) ◽  
Author(s):  
Bruno R. O. Floriano ◽  
Geovany A. Borges ◽  
Henrique C. Ferreira ◽  
João Y. Ishihara
Keyword(s):  
Formation Flight ◽  
Guidance System ◽  
Multiple Uavs
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