Zero-Sum-Game-Based Fixed-Time Event-Triggered Optimal Consensus Control of Multi-Agent Systems Under FDI Attacks

Jing Yang, Ruihong Li (), Qintao Gan and Xinxin Huang
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Jing Yang: Shijiazhuang Campus, Army Engineering University of PLA, Shijiazhuang 050003, China
Ruihong Li: Shijiazhuang Campus, Army Engineering University of PLA, Shijiazhuang 050003, China
Qintao Gan: Shijiazhuang Campus, Army Engineering University of PLA, Shijiazhuang 050003, China
Xinxin Huang: Shijiazhuang Campus, Army Engineering University of PLA, Shijiazhuang 050003, China

Mathematics, 2025, vol. 13, issue 3, 1-19

Abstract: This paper concentrates on the fixed-time optimal consensus issue of multi-agent systems (MASs) under false data injection (FDI) attacks. To mitigate FDI attacks on sensors and actuators that may cause systems to deviate from the reference trajectory, a zero-sum game framework is established, where the secure control protocol aims at the better system performance, yet the attacker plays a contrary role. By solving the Hamilton–Jacobi–Isaacs (HJI) equation related to the zero-sum game, an optimal secure tracking controller based on the event-triggered mechanism (ETM) is obtained to decrease the consumption of system resources while the fixed-time consensus can be guaranteed. Moreover, a critic-only online reinforcement learning (RL) algorithm is proposed to approximate the optimal policy, in which the critic neural networks are constructed by the experience replay-based approach. The unmanned aerial vehicle (UAV) systems are adopted to verify the feasibility of the presented approach.

Keywords: multi-agent systems; FDI attacks; zero-sum game; fixed-time optimal consensus (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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