Robust control using self recurrent wavelet neural network for a coaxial eight-rotor UAV with uncertainties

2Citations
Citations of this article
3Readers
Mendeley users who have this article in their library.
Get full text

Abstract

This paper focuses on the robust control of a coaxial eight-rotor UAV in the presence of model uncertainties and external disturbances. The dynamical and kinematical model of the eight-rotor with high drive capability is established. On account of the uncertainties, a robust back-stepping sliding mode control (BSMC) with self-recurrent wavelet neural network (SRWNN) method is proposed as the attitude controller of the eight-rotor. SRWNN as the uncertainty observer can effectively estimate the lumped uncertainties. All weights of SRWNN can be trained online by the adaptation laws based on Lyapunov stability theorem. Then the uniformly ultimate stability of the eight-rotor system is proved. Finally, simulation results demonstrate the validity of the proposed robust control method adopted in the eight-rotor under model uncertainties and external disturbances.

Cite

CITATION STYLE

APA

Peng, C., Bai, Y., Gong, X., & Tian, Y. (2015). Robust control using self recurrent wavelet neural network for a coaxial eight-rotor UAV with uncertainties. In Lecture Notes in Electrical Engineering (Vol. 338, pp. 71–80). Springer Verlag. https://doi.org/10.1007/978-3-662-46466-3_8

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free