Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1713992 | Nonlinear Analysis: Hybrid Systems | 2008 | 13 Pages |
Abstract
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. A numerical example is provided to demonstrate the efficacy of the proposed hybrid adaptive stabilization approach.
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Tomohisa Hayakawa, Wassim M. Haddad, Konstantin Y. Volyanskyy,