DocumentCode
295891
Title
The application of neural networks to anti-skid brake system design
Author
Mazumdar, Sanjay K. ; Chew Lim, Cheng
Author_Institution
Weapons Syst. Div., Defence Sci. & Technol. Organ., Salisbury, SA, Australia
Volume
5
fYear
1995
fDate
Nov/Dec 1995
Firstpage
2409
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 (NN-ABS)
Keywords
brakes; model reference adaptive control systems; neurocontrollers; road vehicles; anti-skid brake system; braking torque; controller neural network; environmental conditions; neural network based model reference adaptive control; vehicle-brake system; wheel slip; Australia; Control systems; Friction; Neural networks; Roads; Tires; Torque control; Vehicle dynamics; Vehicles; Wheels;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.487739
Filename
487739
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