Neuro-Adaptive Formation Tracking for Networked Autonomous Surface Vehicles Under Time Delay via Hierarchical Information Security Control

This paper investigates the formation tracking control problem for autonomous surface vehicles (ASVs) with dynamic uncertainties and external disturbances under secure and privacy-preserving interaction. An innovative hierarchical information security control (HISC) framework is proposed to solve the estimation problem in a secure and privacy-preserving way and the formation tracking problem for ASVs. The information processing layer of HISC framework focuses on the distributed secure and privacy-preserving estimator (DSPE) algorithm under sampled-data interaction and the local control layer is mainly about the robust neuro-adaptive controller without any model information for the formation of networked ASVs under communication delay. Through systematic analysis, sufficient conditions are given for guaranteeing the stability and convergence of the studied closed-loop system. Ultimately, simulation outcomes are showcased to corroborate the efficacy of the proposed control scheme.