Hierarchical Event-Triggered Predictive Control for Cross-Domain Unmanned Systems with Mixed Constraints

Dear Editor, This letter investigates the problem of multi-dimension formation tracking (MDFT) for the cross-domain unmanned systems, including several interconnected agents, namely, unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs). We assume that each agent suffers from by the mixed constraints on its velocity, control input and Euler angle. Solving the MDFT problem implies that 1) The virtual state of each USV is determined in the earth coordinate by expanding its 2D work space to the 3D space; 2) The UAVs and the virtual states of the USVs form a user-defined geometric formation asymptotically in the 3D local coordinate; 3) The geometric center of the UAVs and the virtual states of the USVs tracks a reference trajectory asymptotically in the 3D earth coordinate. Therefore, a new hierarchical event-triggered predictive control (HETPC) algorithm is proposed to solve the MDFT problem, including the event-triggere cooperation layer and local 1ayer. The former solves the cooperative estimation problem of cross-domain systems with different dimensions, and the latter solves the trajectory tracking control problem under mixed constraints.