Adaptive Fuzzy Inverse Optimal Formation Control for Unmanned Surface Vehicle Systems

Abstract

In this paper, an adaptive fuzzy inverse optimal formation control method is introduced for unmanned surface vehicles (USVs). Fuzzy logic systems (FLSs) are utilized to approximate the unknown nonlinear dynamics, and a bounded estimation algorithm is employed to develop the controller and parameter adaptive law. Drawing from the leader-follower formation approach and inverse optimal stability theory, an inverse optimal formation controller is proposed. This controller ensures the semi-global uniform ultimate boundedness (SGUUB) of all system signals and facilitates effective tracking of the leader vehicle by the follower vehicles. Additionally, it aims to minimize the cost function. The proposed approach presents a promising solution for USV formation control, offering enhanced stability and tracking performance.