Distributed optimization of networked marine surface vehicles: A fixed-time estimator-based approach

Abstract

This paper focuses on the fixed-time consensus problem of the networked marine surface vehicles (NMSVs) while minimizing the sum of the cost functions. To tackle this complex problem, we propose a fixed-time optimization hierarchical control approach that transforms the problem into two sub-problems: a distributed fixed-time optimization estimation problem and a local fixed-time tracking problem respectively. Specifically, the proposed approach leverages a distributed fixed-time optimization estimator to enable the NMSVs to estimate the state and velocity of a virtual leader while minimizing the sum of cost functions. Additionally, the above estimated signal will be tracked by the NMSVs under a fixed-time local tracking controller. We demonstrate the effectiveness of our proposed approach through simulation experiments on a network of four marine surface vehicles, and present the sufficient conditions for stability through Lyapunov stability analysis.