Event-triggered-based adaptive dynamic programming for distributed formation control of multi-UAV

• Published in: Journal of the Franklin Institute 2022-05, Vol.359 (8), p.3671-3691
• Main Authors: Dou, Liqian, Cai, Siyuan, Zhang, Xiuyun, Su, Xiaotong, Zhang, Ruilong
• Format: Article
• Language: English
• Subjects: Adaptive control; Algorithms; Attitude control; Control systems; Control systems design; Controllers; Cost function; Dynamic programming; Finite element analysis; Neural networks; Tracking control; Unmanned aerial vehicles; Unmanned helicopters
• ISSN: 0016-0032; 1879-2693; 0016-0032
• DOI: 10.1016/j.jfranklin.2022.02.034

This paper is concerned with the distributed formation control problem of multi-quadrotor unmanned aerial vehicle (UAV) in the framework of event triggering. First, for the position loop, an adaptive dynamic programming based on event triggering is developed to design the formation controller. The critic-only network structure is adopted to approximate the optimal cost function. The merit of the proposed algorithm lies in that the event triggering mechanism is incorporated the neural network (NN) to reduce calculations and actions of the multi-UAV system, which is significant for the practical application. What’s more, a new weight update law based on the gradient descent technology is proposed for the critic NN, which can ensure that the solution converges to the optimal value online. Then, a finite-time attitude tracking controller is adopted for the attitude loop to achieve rapid attitude tracking. Finally, the efficiency of the proposed method is illustrated by numerical simulations and experimental verification.