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.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China [Nos. 11372309, 61304017], Science and Technology Development Plan Key Project of Jilin Province [No. 20150204074GX], Science and Technology Special Fund Project of Provincial Academy Cooperation [No. 2014SYHZ0004].
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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: Deng, Z., Li, H. (eds) Proceedings of the 2015 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46466-3_8
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DOI: https://doi.org/10.1007/978-3-662-46466-3_8
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