Neural networks adaptive time-varying formation control for quadrotor unmanned aerial vehicles with finite-time prescribed performance

Yizhe Cao, Shulin Song, Jiahe Huo, Dianbiao Dong, Dengxiu Yu

Abstract: The time-varying formation control problem for quadrotor unmanned aerial vehicles with finite-time prescribed performance subject to nonlinear disturbances is investigated in this paper. To address the unknown nonlinear disturbances, neural networks are introduced. In addition, a novel performance function is formulated specifically for finite-time control. A time-varying formation control strategy for quadrotor unmanned aerial vehicles, which aims to confine the sliding mode error within a prescribed region during a finite time interval, is proposed in this study. This method guarantees both finite-time stability in the closed-loop system and error convergence towards the desired boundary. Subsequently, simulations are performed to confirm the effectiveness and feasibility of the proposed algorithm.

Submission Number: 113