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 :
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