Seong-ik HAN1, Kwon-soon LEE1, Dae-yeon YEO1, Sang-ok HAN 2, Kyung-wan KOO3
Dept. of Electrical Engineering, Dong-A Univsersity, Busan 604- 714, Korea;2. Dept. of Electrical Engineering, Chungnam National University, Cheonan 30 5-764, Korea;3. Dept. of Defense Science of Technology, Hoseo University, Cheonan 330-71 3, Korea
Abstract-A nonlinear dynamic friction control is dealt with us ing dynamic friction observer and intelligent control. The adaptive dynamic fric tion observer based on the LuGre friction is proposed to estimate the friction p arameters and a directly immeasurable friction state variable. The dynamic struc tured Recurrent Fuzzy Neural Network(RFNN) is designed to give additional robust ness to the control system under the presence of the friction model uncertainty. A proposed composite control scheme is applied to the position tracking control of the servo system. The performances of the proposed friction observer and the friction controller are demonstrated by simulation.
Key words-LuGre friction model; adaptive friction obser ver; dynamic structured RFNN; servo system control
Manuscript Number: 1674-8042(2011)02-0191-04
dio: 10.3969/j.issn.1674-8042.2011.02.22
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