Extended Version of "Distributed Adaptive Resilient Consensus Control for Uncertain Nonlinear Multiagent Systems Against Deception Attacks"

TL;DR

This paper proposes a novel distributed adaptive control strategy for uncertain nonlinear multiagent systems under deception attacks, ensuring finite-time consensus and improved output performance.

Contribution

It introduces a new resilient consensus control method using Nussbaum functions and dynamic gains, enhancing robustness against sensor and actuator deception attacks.

Findings

All closed-loop signals remain bounded under attacks.

Output consensus errors converge in finite time.

The proposed method outperforms existing approaches in reducing residual errors.

Abstract

This paper studies distributed resilient consensus problem for a class of uncertain nonlinear multiagent systems susceptible to deception attacks. The attacks invade both sensor and actuator channels of each agent. A specific class of Nussbaum functions is adopted to manage the attack-incurred multiple unknown control directions. Additionally, a general form of these Nussbaum functions is provided, which helps to ease the degeneration of output performance caused by Nussbaum gains. Then, by introducing finite-time distributed reference systems and local-error-based dynamic gains, we propose a novel distributed adaptive backstepping-based resilient consensus control strategy. We prove that all the closed-loop signals are uniformly bounded under attacks, and output consensus errors converge in finite time to a clearly-defined residual set whose size can be reduced by tuning control parameters, which is superior to existing results. Simulation results display the effectiveness of the proposed controllers.