Fixed-time hierarchical game-based unmanned aerial-ground vehicle docking control

This letter presents a novel fixed-time Stackelberg game-based adaptive dynamic programming (FxT-SG-ADP) control scheme for UAV-UGV docking control. The docking problem is formulated as a Stackelberg game, where the UGV acts as a leader navigating 2-dimensional space while being tracked by a UAV required to dock with it. The docking performance is optimized by pursuing Stackelberg equilibrium of the Stackelberg game. To enable fixed-time learning and control, a fixed-time concurrent learning law is developed to update the neural network weights, ensuring both game equilibrium and learning process converge within guaranteed time bounds. Lyapunov stability analysis proves the fixed-time convergence properties. Experimental validation on an aerial-ground vehicle system demonstrates the effectiveness of our approach in achieving optimal tracking and safe landing capabilities.

Recommended citation: Tan, Junkai and Xue, Shuangsi and Guo, Zihang and Cao, Hui and Chen, Badong (2025). Fixed-time hierarchical game-based unmanned aerial-ground vehicle docking control. IEEE/CAA Journal of Automatica Sinica.