Abstract
This paper presents a new robust adaptive control method for a class of nonlinear systems subject to uncertainties. The proposed approach is based on an adaptive dynamic surface control, where the system uncertainties are approximately modeled by interval type-2 fuzzy neural networks. In this paper, the robust stability of the closed-loop system is guaranteed by the Lyapunov theorem, and all error signals are shown to be uniformly ultimately bounded. In addition to simulations, the proposed method is applied to a real ball-and-beam system for performance evaluations. To highlight the system robustness, different initial settings of ball-and-beam parameters are considered. Simulation and experimental results indicate that the proposed control scheme has superior responses, compared to conventional dynamic surface control.
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.
