Adaptive Event-Triggered Fixed-Time Fault-Tolerant Consensus Control for a Class of Multiagent Systems
针对一类多智能体系统，提出自适应事件触发固定时间容错一致性控制方案，利用神经网络处理未知非线性项，通过反步法和命令滤波技术保证系统信号有界和一致性误差固定时间收敛。
This article investigates an adaptive event-triggered fixed-time fault-tolerant consensus control for a category of multiagent systems (MASs). First, radial basis function (RBF) neural networks (NNs) are applied to handle unknown nonlinear terms. Furthermore, the backstepping technique is employed to construct the fixed-time event-triggered consensus control scheme by utilizing the command filter technique. The proposed scheme can guarantee the boundedness of all signals in the closed-loop system and the fixed-time convergence of consensus error. Additionally, a simulation example is presented to verify the validity of the presented results.