文章基本信息

标题：RBF network based integral backstepping sliding mode control for USV
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作者：Renqiang Wanga ; Hua Deng ; Keyin Miao 等
期刊名称：MATEC Web of Conferences
电子版ISSN：2261-236X
出版年度：2017
卷号：139
页码：1-5
DOI：10.1051/matecconf/201713900143
语种：English
出版社：EDP Sciences
摘要：A kind of USV course RBF network control algorithm is putted forward, which is on the basis of integral backstepping sliding mode. First of all, an integrator sliding surface were designed with the sliding mode variable structure control technology. Secondly, radial basis function neural network was applied to approximate the system nonlinear function and uncertain parameters. Furthermore, a nonlinear damping law was introduced to overcome the bounded outside interference. Finally, on the basis of the above, the system control law was deduced by using the backstepping method. The simulation results show that the neural network can accurately approximate the nonlinear function and uncertain parameters, and the controller output is smooth and the output is not sensitive to perturbation of parameters. Therefore, the proposed algorithm is effective for USV course control.