Adaptive neural network vibration control of a flexible aircraft wing system with input signal quantization

被引：43

作者：

Gao, Shiqi ^{[1
]}

Liu, Jinkun ^{[1
]}

机构：

[1] Beihang Univ, Sch Automat Sci & Elect Engn, Xueyuan Rd 37, Beijing 100191, Peoples R China

来源：

AEROSPACE SCIENCE AND TECHNOLOGY | 2020年 / 96卷

基金：

中国国家自然科学基金;

关键词：

Input quantization; Vibration control; Boundary control; Adaptive neural network control; Distributed parameter system; INTERCONNECTED NONLINEAR-SYSTEMS; OUTPUT-FEEDBACK CONTROL; BOUNDARY CONTROL; TRACKING CONTROL; MAGNITUDE;

D O I：

10.1016/j.ast.2019.105593

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

In this paper, we study a boundary vibration control problem for a flexible aircraft wing system with input signal quantization and unknown input disturbances. The wing system is a distributed parameter system with coupled bending and torsional deformations. The dynamic behavior of the flexible wing is represented by partial differential equations (PDEs) and several ordinary differential equations (ODEs). The control methods that already exist for similar PDE systems, which is suitable for general situations, will reduce the control precision of the system after control input quantization and may generate stability losses in serious cases. To suppress the elastic deformation of the wing after input quantization, an adaptive quantitative control scheme based on a radial basis function (RBF) neural network is proposed. The new controller can restrain the wing vibration deformation successfully and the stability of the closed-loop system is verified via the Lyapunov's direct method. Finally, numerical simulations illustrate the effectiveness and superiority of the control system. (C) 2019 Elsevier Masson SAS. All rights reserved.

引用

页数：19

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