Fixed-Time Hierarchical Game-Based Unmanned Aerial-Ground Vehicle Docking Control

Dear Editor, 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 (FxT) learning and control, a FxT concurrent learning law is developed to update. neural network weights, ensuring both game equilibnum and learning process converge within guaranteed time bounds. Lyapunov stability analysis proves the FxT convergence properties. Experimental validation on an aerial-ground vehicle system demonstrates the effectiveness of our approach in achieving optimal tracking and docking capabilities.