Fuzzy State Observer-Based Cooperative Path-Following Control of Autonomous Underwater Vehicles with Unknown Dynamics and Ocean Disturbances

Abstract

This article considers the cooperative path-following control problem for a cluster of networked autonomous underwater vehicles (AUVs) suffering from unknown dynamics and ocean disturbances. By virtue of light-of-sight guidance and undirected graph, a synchronized guidance approach is created for underactuated AUVs, where multiple geometry curves are taken into account and information exchanges-related path variables are utilized, and thereby enabling AUVs to be synchronized and stabilized into a desired formation pattern. Within the distributed surge and yaw controller design, the unknown dynamics and the ocean disturbances are lumped together by using a linear state transformation. And a prediction-based fuzzy state observer (PFSO) is devised for estimating the unmeasured lumped states, where prediction errors are used to update fuzzy weights. Through the Lyapunov analysis, it is proven that surge and yaw-tracking errors and state observation errors are uniformly ultimately bounded. Simulation verifications are deployed to illustrate the efficacy and superiority of the designed method.