NDLI: Fuzzy Iterative Learning Control for Nonlinear Systems with Missing Data

Content Provider	IEEE Xplore Digital Library
Author	Fenghuang Cai Wu Wang Fuwen Yang
Copyright Year	2006
Description	Author affiliation: Coll. of Electr. Eng. & Autom., Fuzhou Univ. (Fenghuang Cai; Wu Wang; Fuwen Yang)
Abstract	For packet-based transmission of data over a network, or temporary sensor failure, etc., data samples may be missing in the measured signals. The missing measurements will happen at any sample time, and the probability of the occurrence of missing data was assumed to be known. The series which fulfils Bernoulli distribution was used to describe the missing measurements. Based on the Takagi-Sugeno fuzzy model, nonlinear system was represent by T-S fuzzy model via the so-called parallel distributed compensation (PDC) approach. The fuzzy iterative learning controller was developed to guarantee the expected convergence of the tracking error and with quadratic performance index. A numerical example was provided to demonstrate the validity of the proposed design approach
Sponsorship	IEEE ICIC Int. National Natural Sci. Found. of China Beijing Jiaotong Univ. Kaosiung Univ. of Appl. Sci
Starting Page	428
Ending Page	432
File Size	133260
Page Count	5
File Format	PDF
ISBN	0769526160
DOI	10.1109/ICICIC.2006.87
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy control Nonlinear control systems Control systems Time measurement Takagi-Sugeno model Error correction Performance analysis Nonlinear systems Fuzzy systems Convergence
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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