NDLI: Online adaptive control of robot manipulators using dynamic fuzzy neural networks

Content Provider	IEEE Xplore Digital Library
Author	Yang Gao Meng Joo Er Leithead, W.E. Leith, D.J.
Copyright Year	2001
Description	Author affiliation: Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore (Yang Gao)
Abstract	This paper presents a robust adaptive fuzzy neural controller suitable for motion control of a multi-link robot manipulator. The proposed controller has the following salient features: (1) the dynamic fuzzy neural networks structure, i.e. fuzzy control rules, can be generated or deleted automatically; (2) adaptive learning; (3) online learning of the robot dynamics; (4) fast learning speed; and (5) fast convergence of tracking error. The global stability of the system is established using the Lyapunov approach. Computer simulation studies of a two-link robot manipulator demonstrate that an excellent tracking performance can be achieved under external disturbances.
Sponsorship	American Autom. Control Council
Starting Page	4828
Ending Page	4833
File Size	483246
Page Count	6
File Format	PDF
ISBN	0780364953
ISSN	07431619
DOI	10.1109/ACC.2001.945747
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-06-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Manipulator dynamics Adaptive control Robots Fuzzy control Robotics and automation Programmable control Motion control Robust control Automatic control Motion planning
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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