Event-Triggered Consensus Tracking Control of Nonlinear Multi-Agent Systems with Actuator Faults and Unknown Control Directions
Fan Zhang, Xiongfeng Deng · 2024
In this work, the consensus tracking control problem of leader-follower nonlinear multi-agent systems with actuator faults and unknown control directions is studied. Based on the application of neural network, the uncertain nonlinear dynamics appearing in the analysis process are approximated to attenuate the impact on the system performance. To deal with the unknown control directions in the system, the Nussbaum gain function technique is applied. Moreover, to reduce the communication burden of the system, a class of event-triggered control strategy is designed. Furthermore, a neural network-based on adaptive event-triggered control scheme is proposed to achieve the consensus tracking control of given multi-agent systems with actuator faults. By using the Lyapunov stability theory, the effectiveness of the proposed control scheme is analyzed. The results show that the proposed control scheme not only ensures that the follower agents can track the trajectory of the leader agent, but also proves that the proposed control scheme is not affected by Zeno phenomenon.