NDLI: Adaptive neural fuzzy control for robot manipulator friction and disturbance compensator

Content Provider	IEEE Xplore Digital Library
Author	Vu Minh Hung Uhn Joo Na
Copyright Year	2008
Description	Author affiliation: Div. of Mech. Syst. & Autom. Eng., Kyungnam Univ., Masan (Vu Minh Hung; Uhn Joo Na)
Abstract	This paper presents an application of an adaptive neuro-fuzzy controller for compensating friction and disturbance effects on robot manipulators. The frictions and disturbances are important parts of the dynamic system of a robot manipulator. However, they are highly nonlinear and not easily modeled. Feedback linearization control combined with PD type fuzzy control and adaptive neural network control are proposed to control robot manipulators with unmodeled frictions. The feedback linearization control is designed to control the trajectory of the robot manipulator while the PD type fuzzy control is added as a parallel controller to control frictions and disturbances. This fuzzy control ensures that good tracking control is maintained even if some modeling error, disturbance, noises exist. The neural network can also be trained with experimental data for the frictions and disturbances. Simulations show that the joint positions are well controlled under wide variation of operation conditions and existences of uncertainties.
Starting Page	2569
Ending Page	2574
File Size	413227
Page Count	6
File Format	PDF
ISBN	9788995003893
DOI	10.1109/ICCAS.2008.4694289
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-14
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	ICROS
Subject Keyword	robot manipulator Fuzzy Control PD control Adaptive control Friction compensator Programmable control Fuzzy control Friction Linear feedback control systems Neural networks Feedback linearization Robots Manipulator dynamics Neurofeedback Neural
Content Type	Text
Resource Type	Article

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