Intelligent nonlinear friction compensation using friction observer and backstepping control

Authors:
Seong Ik Han;Chan Se Jeong;Sung Hee Park;Young Man Jeong;Chang Don Lee;Soon Yong Yang
Affiliations:
Dept. of Electrical Automation, Suncheon First College, Cheonnam, Korea;Graduate School of Mechanical and Automotive Engineering, University of Ulsan, Ulsan, Korea;Graduate School of Mechanical and Automotive Engineering, University of Ulsan, Ulsan, Korea;Graduate School of Mechanical and Automotive Engineering, University of Ulsan, Ulsan, Korea;Graduate School of Mechanical and Automotive Engineering, University of Ulsan, Ulsan, Korea;School of Mechanical and Automotive Eng., Ulsan University, Ulsan, Korea
Venue:
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
Year:
2009

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Abstract

In this article, a robust nonlinear friction control strategy is developed using friction observer and recurrent fuzzy neural network. The adaptive dynamic friction observer based on the LuGre friction model is proposed to estimates the friction parameters and a directly immeasurable friction state variable. A RFNN approximator and reconstructed error compensator is also designed to give additional robustness to the control system due to the presence of the friction model uncertainty. A proposed composite control scheme with basic basckstepping controller is applied to the position tracking control of the servo mechanical system.