执行器故障下无人机-无人车异构编队控制

针对存在执行器故障的无人机-无人车异构系统，研究了编队跟踪容错控制问题。首先，异构系统采用有向图的拓扑结构，且并非所有无人机/车都能接收到参考信号，故在充分考虑无人机/车运动学模型存在较大差异的前提下，设计了一种针对两类系统都通用的分布式信号估计器来获取参考信号的信息。然后，基于参考信号估计值，利用鲁棒自适应控制理论，提出了形式统一的分布式容错控制协议。该协议无需获取精准故障信息，就能有效地补偿故障对异构系统性能的影响，确保异构系统在故障情况下仍能按照预先设定的编队构型跟踪上外界参考信号。最后，通过仿真试验验证了所提算法的有效性。

Formation Tracking Control for Heterogeneous Unmanned Aerial Vehicle-Unmanned Ground Vehicle Systems under Actuator Faults

The fault-tolerant formation tracking control problem for heterogeneous unmanned aerial vehicle-unmanned ground vehicle (UAV-UGV) systems under actuator faults is studied in this paper. First, since the topology of UAV-UGV systems is considered as directed spanning tree and only a few vehicles can receive the information of reference signals, distributed estimators which are universal for both UAV and UGV systems are designed to obtain the unknown reference signals by fully considering the apparent distinction between UAV dynamics and UGV dynamics. Then, based on the estimation results, universal distributed fault tolerant protocols are proposed for UAV-UGV systems by utilizing robust adaptive control theory. The proposed protocols can effectively compensate for the fault effects on the system performance without obtaining accurate fault information, as a result, the UAV-UGV systems are guaranteed to maintain a predesigned formation while tracking the reference signals even in the presence of actuator faults. Finally, the effectiveness of the proposed protocols is verified by the simulations.