Data-driven adaptive fault-tolerant control improves consensus tracking in multi-agent systems with sensor and actuator faults, suggesting resilience against system failures.
Key Points
Consensus tracking error remains bounded under the designed fault-tolerant controller, improving system reliability.
Adaptive fault compensation successfully mitigates both sensor and actuator faults, enhancing control performance.
The proposed data-driven method uses locally dynamic linearization for accurate modeling of multi-agent systems.
Stability analysis confirms that tuning parameters can effectively decrease the consensus error bound.