Leader-follower Formation Consensus of Quadrotor UAVs Based on Prescribed Performance Adaptive Constrained Backstepping Control View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2022-08-27

AUTHORS

Kaibiao Yang, Wenhan Dong, Yingyi Tong, Lei He

ABSTRACT

This paper proposes a solution to the external disturbance, uncertain aerodynamic parameters and inter formation collision in coordinated flight of leader-follower quadrotor UAV formation. We present a trajectory tracking control method for UAV formation with preset performance function constraints. We first model the quadrotor UAV system with a dual closed-loop system with position outer loop and attitude inner loop. The performance constraint function transforms the output constraint problem into an unconstrained problem through error transformation. We show that the uncertain aerodynamic parameters and the external disturbance can be estimated by proper design of an exponential disturbance observer. To solve the trajectory tracking problem of the Leader UAV, we introduce a backstepping adaptive control (BC) based on the preset performance. Furthermore, to overcome the issue of the collision between aircrafts in the formation flying, the formation sliding mode control (SMC) based on the power approach rate is proposed. Such a mechanism ensures that the UAVs track their respective reference trajectories quickly, so as to achieve the desired formation. The effectiveness of the control strategy is investigated by simulation. In addition, the open-source autopilot as well as the formation control airborne computer, wireless communication links and used data packet structure are presented, and the designed control law is transplanted into the Pixhawk flight control processor. The feasibility of the control strategy is demonstrated by the quadrotor UAV formation experimental platform based on the Robot Operating System (ROS). More... »

PAGES

3138-3154

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12555-021-0437-x

DOI

http://dx.doi.org/10.1007/s12555-021-0437-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1150553850


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