A Study of Maneuvering Control for an Air Cushion Vehicle Based on Back Propagation Neural Network

A back propagation （BP） neural network mathematical model was established to investigate the maneuvering control of an air cushion vehicle （ACV）. The calculation was based on four-freedom-degree model experiments of hydrodynamics and aerodynamics. It is necessary for the ACV to control the velocity...

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Bibliographic Details
Published inShanghai jiao tong da xue xue bao Vol. 14; no. 4; pp. 482 - 485
Main Author 卢军 黄国樑 李姝芝
Format Journal Article
LanguageEnglish
Published Heidelberg Shanghai Jiaotong University Press 01.08.2009
Subjects
Architecture
BP神经网络
Computer Science
Electrical Engineering
Engineering
Life Sciences
Materials Science
PID参数
奥地利
机动控制
气垫车辆
空气动力学
计算结果
车辆控制
U 661.33
PID control
four degree of freedom
back propagation (BP) neural network
air cushion vehicle
Online AccessGet full text
ISSN1007-1172
1995-8188
DOI10.1007/s12204-009-0482-8

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Summary:A back propagation （BP） neural network mathematical model was established to investigate the maneuvering control of an air cushion vehicle （ACV）. The calculation was based on four-freedom-degree model experiments of hydrodynamics and aerodynamics. It is necessary for the ACV to control the velocity and the yaw rate as well as the velocity angle at the same time. The yaw rate and the velocity angle must be controlled correspondingly because of the whipping, which is a special characteristic for the ACV. The calculation results show that it is an efficient way for the ACV＇s maneuvering control by using a BP neural network to adjust PID parameters online.
Bibliography:TU855
31-1943/U
air cushion vehicle, four degree of freedom, back propagation （BP） neural network. PID control
TP183
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1007-1172
1995-8188
DOI:10.1007/s12204-009-0482-8