Intelligent Leader-Following Consensus Formation Control Using Recurrent Neural Networks for Small-Size Unmanned Helicopters

Abstract

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.