Fuzzy Neural Networks-Based Prescribed-Time Fault-Tolerant Cooperative Control of Second-Order Nonlinear Heterogeneous Multiagent Systems
研究了二阶非线性异构多智能体系统在多种执行器故障下的预设时间容错协同控制问题，利用模糊神经网络逼近未知非线性动态，设计分布式控制协议实现预设时间跟踪与包含一致性。
This article investigates the prescribed-time fault-tolerant cooperative control problem for second-order nonlinear heterogeneous multiagent systems (MASs) subject to multiple actuator faults. A novel prescribed-time stability criterion, independent of time-varying gain functions, is established to facilitate convergence analysis. Fuzzy neural networks (FNNs) are employed to approximate the unknown heterogeneous nonlinear dynamics, and a unified fault-tolerant control framework is constructed to simultaneously address both actuator bias and loss-of-effectiveness (LOE) faults. Based on a nonsingular sliding-mode approach, a distributed control protocol is designed to achieve prescribed-time tracking and containment consensus. Finally, simulation results for both single-leader and multileader scenarios validate the theoretical findings.