Fuzzy-based Robust Precision Consensus Tracking for Uncertain Networked Systems with Cooperative-Antagonistic Interactions

TL;DR

This paper introduces a fuzzy fault-tolerant control scheme for nonlinear multiagent systems that achieves finite-time, robust bipartite consensus tracking despite disturbances and faults, verified through vehicle group simulations.

Contribution

It proposes an improved finite-time performance function and a fuzzy fault-tolerant control scheme for better transient performance and robustness in uncertain multiagent systems.

Findings

Achieves semi-global uniform boundedness of system signals

Ensures bipartite consensus errors meet arbitrary precision in finite time

Demonstrates effectiveness through vehicle group simulations

Abstract

In bipartite consensus tracking (BCT) tasks for nonlinear multiagent systems, stochastic disturbances and actuator faults are regarded as essential factors that hamper effective controller formulation and tracking precision improvement. To address these difficulties, we design an improved finitetime performance function (FTPF) for a fuzzy fault-tolerant distributed cooperative control scheme to achieve finite-time robust precision BCT tasks for nonlinear multiagent systems. The parameter selection range of the improved FTPF is relaxed, which renders systems to achieve better transient performance. Benefitting from stochastic Lyapunov stability theory, it is shown that all signals of systems are semi-global uniformly ultimately bounded in probability, and bipartite consensus errors can satisfy the arbitrary precision with probability in the predefined time. Finally, to verify its effectiveness, the proposed control scheme is applied to BCT tasks of a group of vehicles, which manifests anticipated control performance under various uncertainties.