Self-tuning controller with fuzzy filtered-X algorithm
A fuzzy filtered-X algorithm is proposed which has self-tuning organisation 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 in | Electronics letters Vol. 36; no. 2; p. 1 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Stevenage
John Wiley & Sons, Inc
20.01.2000
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0013-5194 1350-911X |
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| Abstract | A fuzzy filtered-X algorithm is proposed which has self-tuning organisation 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. |
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| AbstractList | A fuzzy filtered-X algorithm is proposed which has self-tuning organisation 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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| Copyright | Copyright The Institution of Engineering & Technology Jan 20, 2000 |
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| SubjectTerms | Active noise control Algorithms Fuzzy Fuzzy logic Fuzzy set theory Human Learning Noise |
| Title | Self-tuning controller with fuzzy filtered-X algorithm |
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