A Discrete Iterative Learning Controller Using Fuzzy Network Design
碩士 === 華梵大學 === 機電工程研究所 === 87 === This thesis discuss the design of iterative learning controller for discrete time nonlinear system and propose a new technique for stability analysis. As we know ,λ-norm approach is widely used to prove the convergence and robustness for traditional iterative learn...
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ndltd-TW-087HCHT06570102016-02-03T04:32:42Z http://ndltd.ncl.edu.tw/handle/22056349963844404459 A Discrete Iterative Learning Controller Using Fuzzy Network Design 利用模糊網路所設計的離散型反覆式學習控制器 Yu-Sheng Liao 廖佑笙 碩士 華梵大學 機電工程研究所 87 This thesis discuss the design of iterative learning controller for discrete time nonlinear system and propose a new technique for stability analysis. As we know ,λ-norm approach is widely used to prove the convergence and robustness for traditional iterative learning systems. However , convergence in the sense of λ-norm can not guarantee a reasonable error convergence in the final iterate. The first contribution of this thesis is to propose a new sup-norm approach for analysis of convergence and robustness , which can ensure the reasonable performance in the final iterate. The convergence of learning systems highly depends on the design of learning gain. In most of the works , we know that the choice of learning gain will depend on input-output coupling matrix of the nonlinear system. However , how to get the formation of input-output coupling matrix is not discussed in most of the works. The second contribution of this thesis is to apply the Adaptive Network Based Fuzzy Inference System (ANFIS) for identification of input-output coupling matrix. It is shown via computer simulation that the convergence performance can be greatly improved by using the ANFIS based iterative learning controller. Chiang-Ju Chien 簡江儒 1999 學位論文 ; thesis 68 zh-TW |
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碩士 === 華梵大學 === 機電工程研究所 === 87 === This thesis discuss the design of iterative learning controller for discrete time nonlinear system and propose a new technique for stability analysis. As we know ,λ-norm approach is widely used to prove the convergence and robustness for traditional iterative learning systems. However , convergence in the sense of λ-norm can not guarantee a reasonable error convergence in the final iterate. The first contribution of this thesis is to propose a new sup-norm approach for analysis of convergence and robustness , which can ensure the reasonable performance in the final iterate. The convergence of learning systems highly depends on the design of learning gain. In most of the works , we know that the choice of learning gain will depend on input-output coupling matrix of the nonlinear system. However , how to get the formation of input-output coupling matrix is not discussed in most of the works. The second contribution of this thesis is to apply the Adaptive Network Based Fuzzy Inference System (ANFIS) for identification of input-output coupling matrix. It is shown via computer simulation that the convergence performance can be greatly improved by using the ANFIS based iterative learning controller.
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Chiang-Ju Chien |
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Chiang-Ju Chien Yu-Sheng Liao 廖佑笙 |
author |
Yu-Sheng Liao 廖佑笙 |
spellingShingle |
Yu-Sheng Liao 廖佑笙 A Discrete Iterative Learning Controller Using Fuzzy Network Design |
author_sort |
Yu-Sheng Liao |
title |
A Discrete Iterative Learning Controller Using Fuzzy Network Design |
title_short |
A Discrete Iterative Learning Controller Using Fuzzy Network Design |
title_full |
A Discrete Iterative Learning Controller Using Fuzzy Network Design |
title_fullStr |
A Discrete Iterative Learning Controller Using Fuzzy Network Design |
title_full_unstemmed |
A Discrete Iterative Learning Controller Using Fuzzy Network Design |
title_sort |
discrete iterative learning controller using fuzzy network design |
publishDate |
1999 |
url |
http://ndltd.ncl.edu.tw/handle/22056349963844404459 |
work_keys_str_mv |
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