TY - JOUR
T1 - Distributed MPC for Trajectory Tracking and Formation Control of Multi-UAVs With Leader-Follower Structure
AU - Xu, Tianlai
AU - Liu, Jinlong
AU - Zhang, Zexu
AU - Chen, Guodong
AU - Cui, Di
AU - Li, Huiping
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2023
Y1 - 2023
N2 - Multiple Unmanned Aerial Vehicle (UAV) cooperation systems, such as flocking, consensus, formation control have a wide range of applications in monitoring, mapping, and target tracking. Optimal cooperative control of such systems is particularly important to increase their working efficiency. This paper studies the optimal trajectory tracking and formation control problems for multi-UAVs with a leader-follower structure, and the distributed model predictive control (MPC) scheme based formation control method is proposed. In particular, a novel MPC strategy is firstly designed for the leader modelled by the nonlinear Newton-Euler equations, to generate a feasible tracking trajectory for the formation systems. Then, by separating the system dynamics of the followers into the translation motion and the rotation motion, a two-layer distributed MPC formation control algorithm is designed to reduce the computation and communication loads, while only requiring limited information of the neighbors' states. Finally, simulation and comparison studies verify the effectiveness of the designed algorithms.
AB - Multiple Unmanned Aerial Vehicle (UAV) cooperation systems, such as flocking, consensus, formation control have a wide range of applications in monitoring, mapping, and target tracking. Optimal cooperative control of such systems is particularly important to increase their working efficiency. This paper studies the optimal trajectory tracking and formation control problems for multi-UAVs with a leader-follower structure, and the distributed model predictive control (MPC) scheme based formation control method is proposed. In particular, a novel MPC strategy is firstly designed for the leader modelled by the nonlinear Newton-Euler equations, to generate a feasible tracking trajectory for the formation systems. Then, by separating the system dynamics of the followers into the translation motion and the rotation motion, a two-layer distributed MPC formation control algorithm is designed to reduce the computation and communication loads, while only requiring limited information of the neighbors' states. Finally, simulation and comparison studies verify the effectiveness of the designed algorithms.
KW - UAVs
KW - leader-follower control
KW - model predictive control
UR - https://www.scopus.com/pages/publications/85177773059
U2 - 10.1109/ACCESS.2023.3329232
DO - 10.1109/ACCESS.2023.3329232
M3 - 文章
AN - SCOPUS:85177773059
SN - 2169-3536
VL - 11
SP - 128762
EP - 128773
JO - IEEE Access
JF - IEEE Access
ER -