DocumentCode
691494
Title
A Research on Adaptive Neural Network Control Strategy of Vehicle Yaw Stability
Author
Li Yue-lin ; Huang Ping-Wen ; Xie Tao
Author_Institution
Sch. of Automotive & Mech. Eng., Changsha Univ. of Sci. & Technol., Changsha, China
fYear
2013
fDate
6-7 Nov. 2013
Firstpage
48
Lastpage
51
Abstract
An adaptive neural network control lerwitn both feed-forward and feedback is designed to improve the yaw stability of vehicle by compound control of direct yaw moment and active front steering. The feedback controller takes the deviation of actual yaw rate from objective yaw rate as its input by PD control strategy,whereas the feed-forward controller uses the output of feedback controller as the error for study through RBF neural network,so as to achieve adaptive control.The simulations show that using above mentioned compound control can effectively track the objective yaw rate and reduce the sideslip angle of mass center,enhancing the stability of vehicle in high-speed sharp turns.
Keywords
PD control; adaptive control; feedback; feedforward; mechanical stability; neurocontrollers; radial basis function networks; steering systems; vehicle dynamics; PD control strategy; RBF neural network; active front steering; actual yaw rate deviation; adaptive neural network control strategy; compound control; direct yaw moment; feedback controller; feedforward controller; high-speed sharp turns; objective yaw rate; sideslip angle of mass center; vehicle yaw stability; Adaptive systems; Control systems; Mathematical model; Neural networks; Stability analysis; Vehicles; Wheels; Game Theory; Reference; Sports Teaching; the PE Teaching Reform;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems Design and Engineering Applications, 2013 Fourth International Conference on
Conference_Location
Zhangjiajie
Print_ISBN
978-1-4799-2791-3
Type
conf
DOI
10.1109/ISDEA.2013.418
Filename
6843395
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