DocumentCode
3392660
Title
Investigation of the use of neural networks for anti-skid brake system design
Author
Cheng Chew Lim
fYear
1995
fDate
27-29 Aug 1995
Firstpage
505
Lastpage
510
Abstract
A neural network based model reference adaptive control approach to anti-skid brake system (ABS) design is investigated in this paper. The principal benefit of using neural networks in an ABS is their ability to adapt to changes in the environmental conditions without significant degradation in performance. In the proposed approach, the controller neural network is designed to produce a braking torque which regulates the wheel slip for the vehicle-brake system to a prespecified level. Simulation studies are performed to demonstrate the effectiveness of the proposed neural network based anti-skid brake system
Keywords
adaptive control; automobiles; braking; dynamics; model reference adaptive control systems; neurocontrollers; anti-skid brake system; automobiles; braking torque; dynamics; model reference adaptive control; neural networks; neurocontrol; wheel slip; Australia; Design engineering; Differential equations; Friction; Neural networks; Optimal control; Road vehicles; Tires; Vehicle dynamics; Wheels;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control, 1995., Proceedings of the 1995 IEEE International Symposium on
Conference_Location
Monterey, CA
ISSN
2158-9860
Print_ISBN
0-7803-2722-5
Type
conf
DOI
10.1109/ISIC.1995.525106
Filename
525106
Link To Document