Abstract
This paper investigates the adaptive finite-time stabilization of a class of switched nonlinear systems via backstepping technique, where unknown nonlinear functions are only required to be continuous. At each step of backstepping, neural network is used to appropriate the unknown continuous function, an adaptive law and a virtual controller are constructed simultaneously. By using the Lyapunov function method, it is shown that, under the designed controller and adaptive laws, the state of the closed-loop system is semi-globally uniformly finite-time bounded. An example is provided to show the effectiveness of the proposed method.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
