IIUM Repository

Support vector regression based friction modeling and compensation in motion control system

Tijani, Ismaila and Akmeliawati, Rini (2012) Support vector regression based friction modeling and compensation in motion control system. Engineering Applications of Artificial Intelligence, 25 (5). pp. 1043-1052. ISSN 0952-1976

[img] PDF - Published Version
Restricted to Repository staff only

Download (779kB) | Request a copy


Friction has been experimentally shown to be one of the major sources of performance degradation in motion control system. Although for model-based friction compensation, several sophisticated friction models have been proposed in the literatures, there exists no universally agreed parametric friction model, which by implication has made selection of an appropriate parametric model difficult. More so, accurate determination of the parameters of these sophisticated parametric friction models has been challenging due to complexity of friction nonlinearities. Motivated by the need for a simple,non-parametric based, and yet effective friction compensation in motion control system, an Artificial Intelligent(AI)-based(non-parametric) friction model using v-Support Vector Regression(v-SVR) is proposed in this work to estimate the non-linear friction in a motion control system. Unlike conventional SVR technique, v-SVR is characterized with fewer parameters for its development, and requires less development time. The effectiveness of the developed model in representing and compensating for the frictional effects is evaluated experimentally on a rotary experimental motion system. The performance is benchmarked with three parametric based (Coulomb, Tustin, and Lorentzian) friction models. The results show the v-SVR as a viable and efficient alternative to the parametric-based techniques in representing and compensating friction effects.

Item Type: Article (Journal)
Additional Information: 5806/25613
Uncontrolled Keywords: SVR; Friction model; Coulomb; Tustin; Lorentzian; Motion control system
Subjects: T Technology > TJ Mechanical engineering and machinery > TJ212 Control engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User: Prof. Dr. Rini Akmeliawati
Date Deposited: 09 Nov 2012 15:19
Last Modified: 17 Jul 2014 14:27
URI: http://irep.iium.edu.my/id/eprint/25613

Actions (login required)

View Item View Item


Downloads per month over past year