Distributed Adaptive Cooperative Control for Human-in-the-Loop Heterogeneous UAV-UGV Systems with Prescribed Performance

This paper focuses on the distributed adaptive cooperative control problem for human-in-the-loop (HiTL) heterogeneous unmanned aerial vehicle-unmanned ground vehicle (UAV-UGV) systems via an improved prescribed performance approach. A novel human motion recognition system (HMRS) is designed and integrated into the HiTL strategy. Specifically, the leader trajectory can be changed in real time based on HMRS and the leader signal library to cope with various unexpected situations. This HiTL strategy solves the discontinuity and non-differentiability problems that may exist before and after human modification of leader signals within the extremely short time in conventional HiTL strategies. Moreover, an improved predefined-time prescribed performance approach is proposed, in which the performance function only needs to be first-order continuous differentiable instead of infinite-order continuous differentiable. This approach can greatly broaden the selection range of performance functions. Furthermore, a unified model of heterogeneous UAV-UGV systems is established to avoid designing UAV and UGV systems separately, which improves the universality of the control algorithm. Finally, the proposed HiTL control scheme is applied to a simulation example to verify its feasibility and effectiveness.