Resilient-triggered fault-tolerant fuzzy consensus for DPS-based MASs against multiple attacks and data compression
Chuan Zhang, Xiaoyu Sun, Huai‐Ning Wu, Zipeng Wang · Fuzzy Sets and Systems · 2025
This paper develops a novel event-triggered (ET) leader-follower fault-tolerant fuzzy consensus framework for nonlinear parabolic distributed parameter system (DPS)-based multi-agent systems (MASs) under multiple cyber attacks. First, a dual-scale modeling framework is proposed, synergizing Galerkin spectral decomposition with Takagi-Sugeno fuzzy techniques to derive a finite-dimensional MASs that accurately captures the dominant dynamics of the original DPS. Second, a resilient hybrid dynamic ET mechanism is devised to intelligently schedule transmissions, significantly alleviating network bandwidth burden while enhancing dynamic performance beyond conventional ET schemes. Subsequently, an event-based fault-tolerant consensus protocol incorporating three data compression mechanisms is designed to counteract multiple cyber attacks. Sufficient conditions for achieving attack-resilient cooperative consensus are then established using a tailored Lyapunov functional approach, with controller gains derived via linear matrix inequality formulations. Finally, simulations on a thermal management system for hypersonic vehicle cooling fins validate the theoretical advances and demonstrate significant engineering applicability.