Cooperative Control for Multi-Agent Systems with Deception Attack Based on an Attack Detection Mechanism

This study highlights the security control challenge for multi-agent systems (MASs) with integrated attack detectors under deception attacks (DAs). We develop an adaptive backstepping security control strategy designed to simultaneously detect DAs and maintain cooperative system performance. First, a DA detection mechanism is proposed using a state observer. The analytical results reveal that observer errors grow unbounded under DAs but converge to zero in attack-free scenarios, enabling effective attack identification. Following detection, we integrate a Nussbaum function into the backstepping control framework to manage unknown time-varying output gains. Additionally, adaptive parameters, dynamically adjusted based on DA signals, are designed to compensate for actuator and sensor deviations induced by attacks. Rigorous Lyapunov-based analysis proves that the proposed controller ensures output tracking under deception attacks, the timely detection of attack signals, and the boundedness of all closed-loop signals. Numerical simulations further confirm the theoretical findings and demonstrate the effectiveness of the proposed method.