Dynamic Event-Triggered Control for Leader-Following Consensus of Nonlinear Multi-Agent Systems Against Malicious Attacks
Lingzhi Zhao, Jianquan Lu, Yang Liu, Jungang Lou
Abstract
This paper addresses the leader-following consensus problems in nonlinear multi-agent systems (MASs), focusing on handling malicious denial-of-service (DoS) attacks. Initially, we introduce an innovative dynamic event-triggered scheme to mitigate network congestion induced by DoS attacks. This scheme, utilizing sampled data, aims to minimize the harmful effects of attacks, and ensures the proficient allocation of limited network resources. Specifically, the sampling period automatically switches depending on the system’s attack status, while the threshold parameter within the predefined triggering condition can be adaptively tuned to match the dynamic characteristics of the controlled system. Building upon this, we propose an event-driven control protocol, along with the construction of a new switched MASs model. It is shown, both analytically and numerically, that our designed control strategy exhibits superiority over traditional co-design frameworks from the aspect of three pivotal metrics: average number of event triggers (ANET), convergence time, and control cost.