Design of Linguistic Hedge Fuzzy Logic Controller with Heuristic-Algorithm Enhancements

碩士 === 國立雲林科技大學 === 電機工程系碩士班 === 96 === In this thesis, four heuristic algorithms are applied to design the linguistic-hedge fuzzy logic controller. These algorithms include genetic algorithm, guided simulated annealing algorithm, guided ant algorithm, particle swarm optimization algorithm. For th...

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Main Authors: Bo-yu Syu, 許博喻
Other Authors: Chuen-Yau Chen
Format: Others
Language:zh-TW
Published: 2008
Online Access:http://ndltd.ncl.edu.tw/handle/2w84g6
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spelling ndltd-TW-096YUNT54420502018-06-25T06:05:26Z http://ndltd.ncl.edu.tw/handle/2w84g6 Design of Linguistic Hedge Fuzzy Logic Controller with Heuristic-Algorithm Enhancements 以啟發式演算法優化之語意修辭模糊邏輯控制器設計 Bo-yu Syu 許博喻 碩士 國立雲林科技大學 電機工程系碩士班 96 In this thesis, four heuristic algorithms are applied to design the linguistic-hedge fuzzy logic controller. These algorithms include genetic algorithm, guided simulated annealing algorithm, guided ant algorithm, particle swarm optimization algorithm. For the controller, we apply different partition strategies on the input-variable domains and analyze the effects on the performance of the controller. The input-variable domains are partitioned in the following manners: the uniform sub-intervals, the more uniform sub-intervals, the fewer uniform sub-intervals, and the non-uniform sub-intervals. The simulation results on the truck-backer upper control system show better performance of the linguistic-hedge fuzzy logic controller. Consider the performances of different strategies. The linguistic-hedge fuzzy logic controller having the input-variable domains with 16 uniform sub-intervals associated with guided simulated annealing algorithm has the best performance. The number of iterations is 1028; the docking error is 0.04. Chuen-Yau Chen Chorng-Sii Hwang 陳春僥 黃崇禧 2008 學位論文 ; thesis 94 zh-TW
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description 碩士 === 國立雲林科技大學 === 電機工程系碩士班 === 96 === In this thesis, four heuristic algorithms are applied to design the linguistic-hedge fuzzy logic controller. These algorithms include genetic algorithm, guided simulated annealing algorithm, guided ant algorithm, particle swarm optimization algorithm. For the controller, we apply different partition strategies on the input-variable domains and analyze the effects on the performance of the controller. The input-variable domains are partitioned in the following manners: the uniform sub-intervals, the more uniform sub-intervals, the fewer uniform sub-intervals, and the non-uniform sub-intervals. The simulation results on the truck-backer upper control system show better performance of the linguistic-hedge fuzzy logic controller. Consider the performances of different strategies. The linguistic-hedge fuzzy logic controller having the input-variable domains with 16 uniform sub-intervals associated with guided simulated annealing algorithm has the best performance. The number of iterations is 1028; the docking error is 0.04.
author2 Chuen-Yau Chen
author_facet Chuen-Yau Chen
Bo-yu Syu
許博喻
author Bo-yu Syu
許博喻
spellingShingle Bo-yu Syu
許博喻
Design of Linguistic Hedge Fuzzy Logic Controller with Heuristic-Algorithm Enhancements
author_sort Bo-yu Syu
title Design of Linguistic Hedge Fuzzy Logic Controller with Heuristic-Algorithm Enhancements
title_short Design of Linguistic Hedge Fuzzy Logic Controller with Heuristic-Algorithm Enhancements
title_full Design of Linguistic Hedge Fuzzy Logic Controller with Heuristic-Algorithm Enhancements
title_fullStr Design of Linguistic Hedge Fuzzy Logic Controller with Heuristic-Algorithm Enhancements
title_full_unstemmed Design of Linguistic Hedge Fuzzy Logic Controller with Heuristic-Algorithm Enhancements
title_sort design of linguistic hedge fuzzy logic controller with heuristic-algorithm enhancements
publishDate 2008
url http://ndltd.ncl.edu.tw/handle/2w84g6
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