TY - JOUR
T1 - 基于一致性理论和 S-MPC 的四旋翼编队协同避障
AU - Hu, Shuxin
AU - Zhang, An
AU - Sun, Manyi
AU - Li, Minghao
N1 - Publisher Copyright:
© 2024 Chinese Institute of Electronics. All rights reserved.
PY - 2024/2
Y1 - 2024/2
N2 - Aiming at the problem of quadrotors unmanned aerial vehicle (UAV) formation maintenance and obstacle avoidance, the safety-critical model predictive control (S-MPC) and consistency theory is proposed to design the formation controller to achieve formation maintenance with obstacle avoidance ability. By using the decentralized S-MPC algorithm, each UAV only plans its own motion to track the trajectory specified by the formation control algorithm within the feasible area that meets the collision avoidance conditions. This paper studies how each decoupled UAV solves the optimization problem with coupling constraints in parallel with other UAVs, so as to ensure the consistency of independent decision-making of each UAV. At the same time, the proposed algorithm introduces the control barrier function (CBF) into the constraints of the MPC controller, so as to ensure that the UAV flies in a safe set far away from obstacles, the planned trajectory is smoother, and the system is reduced energy consumption. Finally, the effectiveness of the proposed method is verified by simulation experiments.
AB - Aiming at the problem of quadrotors unmanned aerial vehicle (UAV) formation maintenance and obstacle avoidance, the safety-critical model predictive control (S-MPC) and consistency theory is proposed to design the formation controller to achieve formation maintenance with obstacle avoidance ability. By using the decentralized S-MPC algorithm, each UAV only plans its own motion to track the trajectory specified by the formation control algorithm within the feasible area that meets the collision avoidance conditions. This paper studies how each decoupled UAV solves the optimization problem with coupling constraints in parallel with other UAVs, so as to ensure the consistency of independent decision-making of each UAV. At the same time, the proposed algorithm introduces the control barrier function (CBF) into the constraints of the MPC controller, so as to ensure that the UAV flies in a safe set far away from obstacles, the planned trajectory is smoother, and the system is reduced energy consumption. Finally, the effectiveness of the proposed method is verified by simulation experiments.
KW - consensus algorithm
KW - control barrier function (CBF)
KW - formation obstacle avoidance
KW - model predictive control
UR - http://www.scopus.com/inward/record.url?scp=85186644193&partnerID=8YFLogxK
U2 - 10.12305/j.issn.1001-506X.2024.02.29
DO - 10.12305/j.issn.1001-506X.2024.02.29
M3 - 文章
AN - SCOPUS:85186644193
SN - 1001-506X
VL - 46
SP - 658
EP - 667
JO - Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
JF - Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
IS - 2
ER -