NDLI: Robust neuro-fuzzy controller design via sliding-mode approach

Content Provider	IEEE Xplore Digital Library
Author	Chun-Fei Hsu Tsu-Tian Lee Chih-Min Lin Li-Yang Chen
Copyright Year	2004
Description	Author affiliation: Dept. of Electr. Eng. & Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan (Chun-Fei Hsu)
Abstract	The computed torque or inverse dynamics control techniques are based on a good understanding of the system dynamics and even its environment. For the real-time applications, the system dynamics is always difficult to obtain. To tackle this drawback, the goal of this paper is to develop a model-free control method which is referred to as the robust neuro-fuzzy sliding-mode control (RNFSMC) system. The proposed RNFSMC system is comprised of a fuzzy controller and a robust controller. The fuzzy controller is utilized to approximate an ideal controller by the developed tuning algorithms, and the robust controller is designed to achieve H/sup /spl infin// tracking performance index. To investigate the effectiveness of the proposed RNFSMC system, it is applied to control a Chua's chaotic circuit system. Finally, simulation results demonstrate that the effect of the fuzzy approximation error on the tracking error can be attenuated efficiently by the proposed method without any knowledge of the controlled systems.
Starting Page	917
Ending Page	922
File Size	330590
Page Count	6
File Format	PDF
ISBN	0780383532
ISSN	10987584
DOI	10.1109/FUZZY.2004.1375530
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-07-25
Publisher Place	Hungary
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robust control Sliding mode control Control systems Fuzzy control Fuzzy systems Torque control Real time systems Circuit optimization Algorithm design and analysis Performance analysis
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence Theoretical Computer Science Software

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