Identification and control of four-wheel-steering vehicles based on neural network

Author

Qiang, Lu ; Huiyi, Wang ; Konghui, Guo

Author_Institution

Armoured Force Eng. Inst., China

fYear

1999

fDate

1999

Firstpage

250

Abstract

Vehicle dynamics are influenced by various nonlinear factors, such as tire characteristics, road conditions, etc. Hence, it is difficult to represent the vehicle dynamics by means of a two-degrees-of-freedom linear model perfectly. This paper presents a new four-wheel-steering (4WS) control system with a neural network that has the abilities of nonlinear modeling and control. A vehicle model of the RBF network is identified from the vehicle dynamics firstly. Next, the authors design a radial basis function (RBF) network controller with this vehicle model of the RBF network. The effectiveness of the proposed method is demonstrated with computer simulations

Keywords

control system analysis computing; control system synthesis; identification; motion control; neurocontrollers; nonlinear control systems; radial basis function networks; road traffic; road vehicles; traffic control; traffic engineering computing; computer simulation; control system; four-wheel-steering vehicles; neural network; nonlinear control; nonlinear modeling; radial basis function network; road conditions; tyre characteristics; vehicle dynamics; Automotive engineering; Control system synthesis; Mathematical model; Mathematics; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Road vehicles; Tires; Vehicle dynamics;

fLanguage

English

Publisher

ieee

Conference_Titel

Vehicle Electronics Conference, 1999. (IVEC '99) Proceedings of the IEEE International

Conference_Location

Changchun

Print_ISBN

0-7803-5296-3

Type

conf

DOI

10.1109/IVEC.1999.830677

Filename

830677