Course control of air cushion vehicle based on adaptive backstepping sliding mode control

被引：0

作者：

Ding, Fuguang ^{[1
]}

Zhu, Chao ^{[1
]}

Fang, Sheng ^{[1
]}

Wang, Chenglong ^{[1
]}

Ma, Yanqin ^{[2
]}

机构：

[1] College of Automation, Harbin University of Engineering, Harbin

[2] Institute of Acoustics, Chinese Academy of Sciences, Qingdao Branch, Qingdao

来源：

Journal of Computational Information Systems | 2015年 / 11卷 / 20期

基金：

中国国家自然科学基金;

关键词：

Adaptive control; Air cushion vehicle; Backstepping sliding mode control; Course control; RBF neural network;

D O I：

10.12733/jcis15657

中图分类号：

学科分类号：

摘要：

An adaptive backstepping sliding mode control approach is proposed to realize the course control accurately of air cushion vehicle (ACV). First, a robust backstepping control system combined with sliding mode control technique is designed. Then in order to reduce the error and chattering, an adaptive law is introduced to estimate the upper bound value of the lumped external disturbance in the backstepping sliding mode control. Consider the nonlinearities and uncertainties of ACV, a radial basis function (RBF) neural network is introduced to approximate the uncertain nonlinear function online because the dynamics of ACV are highly nonlinear nature and the hydrodynamic coefficients will change with the motion parameters that it is difficult to be estimated accurately. Simulation results indicate that the proposed control method has perfect control performance. Copyright © 2015 Binary Information Press.

引用

页码：7405 / 7412

页数：7

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