MATEC Web Conf.
Volume 214, 20182018 2nd International Conference on Information Processing and Control Engineering (ICIPCE 2018)
|Number of page(s)||4|
|Section||Electronic Information Technology and Control Engineering|
|Published online||15 October 2018|
RBF NN-Based Backstepping Adaptive Control for a Class of Nonlinear Systems
Engineering Technology Research Center of Optoelectronic Appliance, Tongling University, Tongling Anhui, 244061, China
2 Sichuan Institute of Aerospace System Engineering, Chengdu Sichuan, 610100, China
There are many control methods for nonlinear systems, but some of them can not control nonlinear mismatched systems very well. Backstepping control has obvious advantages in controlling nonlinear mismatched systems. Thus we proposed a new radial-basis-function (RBF) neural network-based backstepping adaptive controller combining RBF neural network (RBF NN) and backstepping control for a class of nonlinear mismatched systems. We adopted RBF NN to approximate the system uncertainty. And we analyzed the controller stability using Lyapunov stability theory. Finally we chose sine signal as simulation input signal, simulation results show that the proposed control strategy has better adaptive ability and robustness than PID control, validating the effectivess of the proposed control strategy.
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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