The Self-Tuning Fuzzy Logic Controller
碩士 === 國立臺灣大學 === 化學工程學系 === 85 === This article aims to present a systematic methodology for on-line tuning of a fuzzy logic controller. First, we introduce the basic structure and inference mechanisms of the crisp-type fuzzy logic contro...
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ndltd-TW-085NTU000630022015-10-13T18:05:37Z http://ndltd.ncl.edu.tw/handle/50644510191069177876 The Self-Tuning Fuzzy Logic Controller 自我調諧模糊邏輯控制器 Huang, Yuan-Sheng 黃淵聖 碩士 國立臺灣大學 化學工程學系 85 This article aims to present a systematic methodology for on-line tuning of a fuzzy logic controller. First, we introduce the basic structure and inference mechanisms of the crisp-type fuzzy logic controller in use. The initial values of the fuzzy logic controller parameters are given by choosing equally-spaced triangles as the input membership functions, and simple control rule mapping as the control rules. Then a method of evaluating process response performance is proposed according to three characteristics --- percentage overshoot, rising time and oscillation amplitude. The performance evaluation will decide whether the tuning procedure is necessary or not. This evaluation will also be used as a stopping criterion in each stage of the subsequent tuning work. Parameters being tuned can be divided into two parts:scaling factors and control rules. Linquistic tuning guides for scaling factors are inferred from the analogy of the fuzzy logic controller and the conventional PI controller. The control rules being fired will be further adjusted according to the discrepancy between the true response and the target response, while the later is determined by the above-mentioned response characteristics. Some numerical examples are supplied to demonstrate the adequacy and efficiency of the proposed self-tuning fuzzy logic controller. Chen, Cheng-Liang 陳誠亮 --- 1997 學位論文 ; thesis 71 zh-TW |
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Others
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碩士 === 國立臺灣大學 === 化學工程學系 === 85 === This article aims to present a systematic methodology for on-line tuning
of a fuzzy logic controller.
First, we introduce the basic structure and inference
mechanisms of the crisp-type fuzzy logic controller in use.
The initial values of the fuzzy logic controller parameters are given
by choosing equally-spaced triangles as the input membership
functions, and simple control rule mapping as the control rules.
Then a method of evaluating process response performance is proposed according
to three characteristics --- percentage overshoot, rising time and
oscillation amplitude.
The performance evaluation will decide whether the tuning procedure is
necessary or not.
This evaluation will also be used as a stopping criterion
in each stage of the subsequent tuning work.
Parameters being tuned can be divided into two parts:scaling factors
and control rules.
Linquistic tuning guides for scaling factors are inferred from the analogy
of the fuzzy logic controller and the conventional PI controller.
The control rules being fired will be further adjusted according to the
discrepancy between the true response and the target response, while the later
is determined by the above-mentioned response characteristics.
Some numerical examples are supplied to demonstrate the
adequacy and efficiency
of the proposed self-tuning fuzzy logic controller.
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author2 |
Chen, Cheng-Liang |
author_facet |
Chen, Cheng-Liang Huang, Yuan-Sheng 黃淵聖 |
author |
Huang, Yuan-Sheng 黃淵聖 |
spellingShingle |
Huang, Yuan-Sheng 黃淵聖 The Self-Tuning Fuzzy Logic Controller |
author_sort |
Huang, Yuan-Sheng |
title |
The Self-Tuning Fuzzy Logic Controller |
title_short |
The Self-Tuning Fuzzy Logic Controller |
title_full |
The Self-Tuning Fuzzy Logic Controller |
title_fullStr |
The Self-Tuning Fuzzy Logic Controller |
title_full_unstemmed |
The Self-Tuning Fuzzy Logic Controller |
title_sort |
self-tuning fuzzy logic controller |
publishDate |
1997 |
url |
http://ndltd.ncl.edu.tw/handle/50644510191069177876 |
work_keys_str_mv |
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