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Intelligent Leader-Following Consensus Formation Control Using Recurrent Neural Networks for Small-Size Unmanned Helicopters
IEEE Transactions on Systems, Man, and Cybernetics: Systems ( IF 8.6 ) Pub Date : 2021-02-01 , DOI: 10.1109/tsmc.2019.2896958
Chia-Wei Kuo , Ching-Chih Tsai , Chi-Tai Lee

In this paper, an intelligent leader-following consensus formation control method using recurrent neural networks (RNNs) is presented for a team of uncertain small-size unmanned helicopters (SSUHs). After a brief description of the dynamic model of each uncertain SSUH by a set of multivariable fourth-order state equations, the leader–follower multi-SSUH system with a virtual leader is modeled by the directed graph theory. An intelligent adaptive formation control approach is proposed to fly together all the follower SSUHs in formation by using RNN to online learn the system uncertainties, consensus tracking, and the Lyapunov stability theory. The four simulations on three cooperating SSUHs are conducted to exemplify the effectiveness and merits of the proposed control method.

中文翻译:

使用循环神经网络的小型无人直升机智能领导者跟随共识形成控制

在本文中,针对不确定的小型无人直升机(SSUH)团队,提出了一种使用循环神经网络(RNN)的智能领导跟随共识编队控制方法。在通过一组多变量四阶状态方程对每个不确定 SSUH 的动力学模型进行简要描述后,利用有向图理论对具有虚拟领导者的领导者-跟随者多 SSUH 系统进行建模。提出了一种智能自适应编队控制方法,通过使用 RNN 在线学习系统不确定性、一致性跟踪和 Lyapunov 稳定性理论,将所有跟随 SSUH 编队飞行。对三个合作的 SSUH 进行了四次模拟,以举例说明所提出的控制方法的有效性和优点。
更新日期:2021-02-01
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