TY - JOUR
T1 - Time-varying nonholonomic UAV formation control with trajectory prediction and nonlinear model predictive control
AU - Wu, Junqi
AU - Wu, Bi
AU - Deng, Hongbin
AU - Xu, Yahao
AU - Ma, Xunju
N1 - Publisher Copyright:
© 2024 American Society of Civil Engineers.
PY - 2024/5/1
Y1 - 2024/5/1
N2 - This paper proposes a time-varying unmanned aerial vehicle (UAV) formation control method based on trajectory prediction and nonlinear model predictive control (NMPC). First, in formation control, the nominal controller is constructed using a linear model and consensus for theoretical stability assurance. The time-varying formation control of nonholonomic UAVs subsequently is achieved by integrating the nonholonomic model with the NMPC, using the desired state derived from the nominal controller. Furthermore, considering the optimal obstacle avoidance problem of moving obstacles, the transformer is used to predict the trajectory in the predictive horizon, the safety constraints are established in combination with the discrete control barrier function (DCBF), and the optimal obstacle avoidance is realized by reducing the additional motion generated during obstacle avoidance. Subsequently, the NMPC-DCBF-Transformer is integrated to realize the optimal obstacle avoidance control of nonholonomic UAV time-varying formation. Finally, the algorithm s effectiveness was verified by numerical simulation, and the advantages of the algorithm were verified by comparison.
AB - This paper proposes a time-varying unmanned aerial vehicle (UAV) formation control method based on trajectory prediction and nonlinear model predictive control (NMPC). First, in formation control, the nominal controller is constructed using a linear model and consensus for theoretical stability assurance. The time-varying formation control of nonholonomic UAVs subsequently is achieved by integrating the nonholonomic model with the NMPC, using the desired state derived from the nominal controller. Furthermore, considering the optimal obstacle avoidance problem of moving obstacles, the transformer is used to predict the trajectory in the predictive horizon, the safety constraints are established in combination with the discrete control barrier function (DCBF), and the optimal obstacle avoidance is realized by reducing the additional motion generated during obstacle avoidance. Subsequently, the NMPC-DCBF-Transformer is integrated to realize the optimal obstacle avoidance control of nonholonomic UAV time-varying formation. Finally, the algorithm s effectiveness was verified by numerical simulation, and the advantages of the algorithm were verified by comparison.
UR - http://www.scopus.com/inward/record.url?scp=85185759014&partnerID=8YFLogxK
U2 - 10.1061/JAEEEZ.ASENG-5397
DO - 10.1061/JAEEEZ.ASENG-5397
M3 - Article
AN - SCOPUS:85185759014
SN - 0893-1321
VL - 37
JO - Journal of Aerospace Engineering
JF - Journal of Aerospace Engineering
IS - 3
M1 - 04024020
ER -