Finite-Time RBFNN-Based Observer for Cooperative Multi-Missile Tracking Control under Dynamic Event-Triggered Mechanism

This paper proposes a hierarchical cooperative tracking control method for multi-missile formations under dynamic event-triggered mechanisms, addressing parameter uncer-tainties and saturated overload constraints. The proposed hierarchical structure consists of a reference trajectory generator and a trajectory tracking controller. The reference tra-jectory generator considers communication and collaboration among multiple intercep-tors, imposes saturation constraints on virtual control inputs, and generates reference trajectories for each receptor, effectively suppressing aggressive motions caused by overload saturation. On this basis, a Radial Basis Function Neural Network (RBFNN) combined with a sliding mode disturbance observer is adopted to estimate unknown external disturbances and unmodeled dynamics, and the finite-time convergence of the disturbance observer is proved. A tracking controller is then designed to ensure precise tracking of the reference trajectory by missile. This approach not only reduces commu-nication and computational burdens but also effectively avoids Zeno behavior, enhancing the practical feasibility and robustness of the proposed method in engineering applica-tions. Simulation results verify the effectiveness and superiority of the proposed method.