|
|||||
|
|
Dynamic Friction Control Using Dynamic Structured RFNN and Friction Parameter Estimator |
|
| Authors: | Seong-ik HAN Kwon-soon LEE Dae-yeon YEO Sang-ok HAN Kyung-wan KOO |
| Affiliation: | 1. Dept. of Electrical Engineering, Dong-A Univsersity,Busan 604-714, Korea 2. Dept. of Electrical Engineering, Chungnam National Unitersity,Cheonan 305-764, Korea 3. Dept. of Defense Science of Technology, Hoseo Unitersity, Cheonan 330-713, Korea |
| Abstract: | A nonlinear dynamic friction control is dealt with using dynamic friction observer and intelligent control.The adaptive dynamic friction observer based on the LuGre friction is proposed to estimate the friction parameters and a directly immeasurable friction state variable.The dynamic structured Recurrent Fuzzy Neural Network(RFNN)is designed to give additional robustness 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. |
| Keywords: | LuGre friction model adaptive friction observer dy-namic structured RFNN servo system control |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |