Adaptive neural network control of an uncertain 2-DOF helicopter system with input backlash and output constraints

被引:11
|
作者
Zhao, Zhijia [1 ]
He, Weitian [1 ]
Yang, Jingfeng [2 ,3 ]
Li, ZhiFu [1 ]
机构
[1] Guangzhou Univ, Sch Mech & Elect Engn, Guangzhou 510006, Peoples R China
[2] Guangzhou Inst Ind Intelligence, Guangzhou 511458, Peoples R China
[3] Chinese Acad Sci, Shenyang 110016, Peoples R China
来源
NEURAL COMPUTING & APPLICATIONS | 2022年 / 34卷 / 20期
关键词
2-DOF helicopter system; Neural network control; Input backlash; Output constraint; TRACKING CONTROL;
D O I
10.1007/s00521-022-07463-3
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This study considers an adaptive neural control for a two degrees of freedom helicopter nonlinear system preceded by system uncertainties, input backlash, and output constraints. First, a neural network is adopted to handle the hybrid effects of input backlash nonlinearities and system uncertainties. Subsequently, a barrier Lyapunov function is introduced to limit the output signals for further ensuring the safe operation of the system. The bounded stability of the closed-loop system is analyzed employing the direct Lyapunov approach. In the end, the simulation and experiment results are provided to demonstrate the validity and efficacy of the derived control.
引用
收藏
页码:18143 / 18154
页数:12
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