Abstract

In this paper, we develop an observer-based indirect adaptive fuzzy-neural controller with supervisory mode for a certain class of high order unknown nonlinear dynamical system. The free parameters of the adaptive fuzzy-neural controller with supervisory mode can be tuned on-line by an observer-based output feedback control law and adaptive law, based on the Lyapunov synthesis approach. The fuzzy controller is appended with a supervisory controller. If the fuzzy control system tends to unstable, the supervisory controller starts working to guarantee stability. From the energy point of view, this is a very economical design methodology. The overall adaptive scheme guarantees the global stability of the resulting closed-loop system in the sense that all signals involved are uniformly bounded.

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 call

Disclaimer: 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.