A Control Method for Nonlinear Systems Using Combined Sliding Mode Control and RBF Neural Network

International Journal of Electrical and Electronics Engineering
© 2018 by SSRG - IJEEE Journal
Volume 5 Issue 6
Year of Publication : 2018
Authors : Ngoc Trung Dang and Huyen Linh Le Thi
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How to Cite?

Ngoc Trung Dang and Huyen Linh Le Thi, "A Control Method for Nonlinear Systems Using Combined Sliding Mode Control and RBF Neural Network," SSRG International Journal of Electrical and Electronics Engineering, vol. 5,  no. 6, pp. 11-15, 2018. Crossref, https://doi.org/10.14445/23488379/IJEEE-V5I6P103

Abstract:

AIn general, the industrial systems are uncertain nonlinear systems with the influence of external disturbance factors. This paper has developed a control method for nonlinear systems combining Sliding Mode Control with Radial Basic Function (RBF) Neural Network to ensure robustness and interference resistance. This paper has developed a control method for nonlinear systems with external measureless disturbance by combining Sliding Mode Control with RBF Neural Network to ensure robustness and interference resistance. The obtained Sliding Mode Control algorithms and weight update rules of the Network have ensured the existence and stability of the Sliding Mode system. The efficiency and feasibility of the proposed method have verified by simulation results in Matlab-Simulink.

Keywords:

RBF Neural Network, Sliding Mode Control, Lyapunov stability, nonlinear systems, adaptive control.

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