Issue |
MATEC Web Conf.
Volume 104, 2017
2017 2nd International Conference on Mechanical, Manufacturing, Modeling and Mechatronics (IC4M 2017) – 2017 2nd International Conference on Design, Engineering and Science (ICDES 2017)
|
|
---|---|---|
Article Number | 02007 | |
Number of page(s) | 9 | |
Section | Chapter 2: Engineering Simulation, Modeling and Mechatronics | |
DOI | https://doi.org/10.1051/matecconf/201710402007 | |
Published online | 14 April 2017 |
Backstepping Adaptive Fuzzy Control of Servo System With LuGre Friction
1 Engineering Technology Research Center of Optoelectronic Appliance, Tongling University, Tongling Anhui, 244061, China
2 Department of Electrical Engineering, Tongling University, Tongling Anhui, 244061, China
3 Sichuan Institute of Aerospace System Engineering, Chengdu Sichuan, 610100, China
a Corresponding author: happyzhaohaibo@126.com
Aiming at the control problem of servo system with friction nonlinearity, we introduced the improved LuGre friction model of system. We used adaptive fuzzy system to approximate the nonlinear part and unknown parameters in system online. The purpose is to avoid the complex calculation in deducing the adaptive law of each unknown parameter. By using backstepping approach and recursively selecting the Lyapunov function, introducing the virtual control quantity, we designed an adaptive fuzzy controller with state feedback. Then we analyzed the stability of adaptive fuzzy controller. We carried out the system response analysis and system robustness analysis. We used sinusoidal signal as simulation input signal. Two cases were considered in simulation test comparing backstepping control with conventional PID control. Simulation results show that the proposed backstepping control has better position tracking performance and robustness than conventional PID control.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.