比例加导数模糊控制器的简单多染色体遗传算法优化

NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2008-05-19 DOI:10.1109/NAFIPS.2008.4531273

N. Baine

{"title":"比例加导数模糊控制器的简单多染色体遗传算法优化","authors":"N. Baine","doi":"10.1109/NAFIPS.2008.4531273","DOIUrl":null,"url":null,"abstract":"In this paper, a genetic algorithm is used to optimize the input and output fuzzy sets of a proportional-plus-derivative fuzzy logic controller (PDFLC). The center points of these sets are organized into \"chromosomes,\" and then bred and mutated in a genetic algorithm to produce a population of offspring. The offspring are then put through a fitness algorithm to determine which of them survive to breed the next generation. This iterative process results in a solution optimized toward the definition of a \"fit\" design. This design method is illustrated with a numerical example.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A simple multi-chromosome genetic algorithm optimization of a Proportional-plus-Derivative Fuzzy Logic Controller\",\"authors\":\"N. Baine\",\"doi\":\"10.1109/NAFIPS.2008.4531273\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a genetic algorithm is used to optimize the input and output fuzzy sets of a proportional-plus-derivative fuzzy logic controller (PDFLC). The center points of these sets are organized into \\\"chromosomes,\\\" and then bred and mutated in a genetic algorithm to produce a population of offspring. The offspring are then put through a fitness algorithm to determine which of them survive to breed the next generation. This iterative process results in a solution optimized toward the definition of a \\\"fit\\\" design. This design method is illustrated with a numerical example.\",\"PeriodicalId\":430770,\"journal\":{\"name\":\"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAFIPS.2008.4531273\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2008.4531273","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 5

摘要

本文采用遗传算法对比例加导数模糊控制器的输入和输出模糊集进行优化。这些集合的中心点被组织成“染色体”，然后在遗传算法中繁殖和突变，以产生一个后代群体。然后将这些后代放入一个适合度算法中，以确定哪一个能够存活下来繁殖下一代。这个迭代过程产生了一个朝着“适合”设计的定义优化的解决方案。最后用数值算例说明了这种设计方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A simple multi-chromosome genetic algorithm optimization of a Proportional-plus-Derivative Fuzzy Logic Controller

In this paper, a genetic algorithm is used to optimize the input and output fuzzy sets of a proportional-plus-derivative fuzzy logic controller (PDFLC). The center points of these sets are organized into "chromosomes," and then bred and mutated in a genetic algorithm to produce a population of offspring. The offspring are then put through a fitness algorithm to determine which of them survive to breed the next generation. This iterative process results in a solution optimized toward the definition of a "fit" design. This design method is illustrated with a numerical example.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society

自引率

0.00%

发文量