Filtering robust adaptive formation guidance law with uncertain leader dynamics
Zhouhua Peng, Dan Wang, Weiyao Lan, Xiaoqiang Li, Gang Sun · 2010
A new filtering robust adaptive formation guidance law is proposed for unmanned surface vehicles (USVs) in the presence of uncertain leader dynamics. Using the approximation properties of neural network (NN) and adaptive bounding technique, the developed controller does not require the knowledge of the velocity of the leader. The derived guidance law is a velocity command for the follower and guarantees arbitrary close tracking of reference signals both in the transient and steady phase. The effectiveness of the formation guidance law is illustrated by numerical simulations.