DocumentCode
2843577
Title
Grey prediction in the application of friction compensation
Author
Weihong, Wang ; Xiyang, Wang
Author_Institution
Autom. Dept., Beihang Univ., Beijing, China
fYear
2009
fDate
17-19 June 2009
Firstpage
5405
Lastpage
5408
Abstract
A method of combining GM (0, N) model with BP neural network is proposed and used in friction compensation. Firstly BP neural networks compensate the friction, then BP network is replaced with GM (0, N) model in a certain moment. With this method the neural network can apperceive the friction torque by online self learning and compensate. The results of both simulation and experiment show that the method is feasible and effective on the friction compensation, it has well prospect for engineering application.
Keywords
compensation; control engineering computing; grey systems; learning (artificial intelligence); neural nets; servomotors; torque control; BP neural network; GM (0, N) model; friction compensation; friction torque; grey prediction; online self learning; servo system; Control systems; Data mining; Electronic mail; Friction; Monitoring; Neural networks; Predictive models; Servomechanisms; Torque; Uncertainty; BP neural networks; Friction compensation; Grey prediction; Servo system; Simulator;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location
Guilin
Print_ISBN
978-1-4244-2722-2
Electronic_ISBN
978-1-4244-2723-9
Type
conf
DOI
10.1109/CCDC.2009.5195181
Filename
5195181
Link To Document