Robust Adaptive Neural Fault-Tolerant Control of Hypersonic Flight Vehicle

被引：0
|
作者：
Guo, Yuyan [1 ]
Wang, Qiang [1 ]
Xu, Bin [1 ]
机构：
[1] Northwestern Polytech Univ, Sch Automat, Xian, Shaanxi, Peoples R China
来源：
COGNITIVE SYSTEMS AND SIGNAL PROCESSING, ICCSIP 2016 | 2017年 / 710卷
基金：
中国国家自然科学基金;
关键词：
Hypersonic flight vehicle; Fault-tolerant control; Neural networks; DYNAMIC SURFACE CONTROL; SYSTEMS;
D O I：
10.1007/978-981-10-5230-9_5
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper proposes a fault-tolerant back-stepping control method for the hypersonic flight vehicle. An adaptive law is proposed to make sure that the normal actuators could compensate the ineffective actuators while failure exists. Meanwhile, the RBF NN is employed to estimate the unknown nonlinearity of the model. The simulation results verify the effectiveness of the proposed approach.
引用
收藏
页码：44 / 51
页数：8
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