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
Link To Document :
بازگشت