Self-tuning controller with fuzzy filtered-X algorithm

A fuzzy filtered-X algorithm is proposed which has sell-tuning organization under active noise control. By imitating human learning processes, the fuzzy control algorithm does not require a plant model to make its control rules. Instead, rules are generated by using the history of the input-output n...

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Published inElectronics letters Vol. 36; no. 2; pp. 182 - 184
Main Authors Shyu, Kuo-Kai, Chang, Cheng-Yuan, Kuo, Ming-Chu
Format Journal Article
LanguageEnglish
Published 20.01.2000
Online AccessGet full text
ISSN0013-5194
1350-911X
DOI10.1049/el:20000189

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Abstract A fuzzy filtered-X algorithm is proposed which has sell-tuning organization under active noise control. By imitating human learning processes, the fuzzy control algorithm does not require a plant model to make its control rules. Instead, rules are generated by using the history of the input-output noise pairs. The new approach not only provides better performance than the conventional filtered-X algorithm but also leads to a reduction in the complexity of the active noise control system.
AbstractList A fuzzy filtered-X algorithm is proposed which has sell-tuning organization under active noise control. By imitating human learning processes, the fuzzy control algorithm does not require a plant model to make its control rules. Instead, rules are generated by using the history of the input-output noise pairs. The new approach not only provides better performance than the conventional filtered-X algorithm but also leads to a reduction in the complexity of the active noise control system.
Author Chang, Cheng-Yuan
Kuo, Ming-Chu
Shyu, Kuo-Kai
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References Lee (10.1049/el:20000189_r4) 1990; SMMC-20
Kuo Wang (10.1049/el:20000189_r2) 1999; SP-47
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Park (10.1049/el:20000189_r3) 1996; EC-11
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