Neural Adaptive Command Filtered Control for Cooperative Path Following of Multiple Underactuated Autonomous Underwater Vehicles Along One Path
Hao Wang, Yu Tian, Hongli Xu
Abstract
The aim of this article is to develop a new cooperative path following control scheme for a team of autonomous underwater vehicles (AUVs) which track one curve with nonlinear uncertainties. Individual path-following controllers are designed to guarantee that each AUV meets the desired tracking performance. For the cooperative path following, a containment control approach is incorporated into the design, where each AUV is forced to evenly disperse on a path that is parameterized by a continuous variable over a communication network. The main features of the paper that unlike the existing designs are that: first, by employing the command filtered control technique, the assumption of second-order derivative of the reference path is removed. Second, a globally uniformly ultimately bounded (GUUB) path following control structure is proposed that enables two kinds of controllers to switch under different cases. Third, coordination between multiple AUVs is achieved through a containment design, and a path variable containment cooperative path following controller is derived that enables multiple AUVs to be evenly dispersed and guided by the virtual leaders. Finally, the stability analysis and simulation example are given to verify the proposed control strategy.