Stable Neural Hybrid Adaptive Control for Nonlinear Uncertain Impulsive Dynamical Systems

A neural network hybrid adaptive control framework for nonlinear uncertain hybrid dynamical systems is developed. The proposed hybrid adaptive control framework is Lyapunov-based and guarantees partial asymptotic stability of the closed-loop hybrid system; that is, asymptotic stability with respect to part of the closed-loop system states associated with the hybrid plant states. Finally, a numerical example is provided to demonstrate the efficacy of the proposed hybrid adaptive stabilization approach.