Communication-efficient fault-tolerant control for fractional-order multi-agent systems through LMI-based event-triggering

This work introduces an advanced event-triggered fault-tolerant control scheme for fractional-order multi-agent systems (MAS) subject to actuator faults. The core innovation lies in the integration of a Linear Matrix Inequality (LMI)-driven design for event-triggering thresholds, replacing conventional fixed or manually tuned parameters. This LMI-based formulation provides a systematic method to determine thresholds that balance tracking accuracy and communication efficiency while ensuring global stability of the closed-loop system. The control strategy combines adaptive neural networks for handling model uncertainties and unknown actuator faults with an LMI-optimized event-triggered mechanism that eliminates Zeno behavior by guaranteeing a strictly positive lower bound on inter-event times. Rigorous stability proofs are developed using fractional-order Lyapunov theory expressed through LMI conditions. Numerical simulations confirm the effectiveness of the proposed design, demonstrating improved tracking performance and reduced communication load compared to fixed-threshold approaches.