模糊建模和控制使用参数化线性滤波器

Z. Papp
{"title":"模糊建模和控制使用参数化线性滤波器","authors":"Z. Papp","doi":"10.1109/IMTC.1997.610182","DOIUrl":null,"url":null,"abstract":"The paper presents a nonlinear identification scheme, which consists of a linear dynamical section (filter) and a nonlinear zero-memory section (implemented by a fuzzy mapping). Only the filter section is on the primary signal path. The nonlinear mapping (depending on the system input and state) delivers the filter parameters. The identification assumes structural knowledge about the process with proper parameterisation. An adaption procedure is introduced, which tunes the nonlinear mapping (e.g. membership function parameters) to minimize identification error. The adaption procedure is driven by the approximate dynamical sensitivity model of the system thus the method is very effective with respect to the number of training steps necessary to reach the accuracy required. The scheme proposed can incorporate a priori knowledge on two levels (structure and fuzzy rule set). One of the most distinctive features of the scheme is that it directly supports controller design and/or (on-line) tuning.","PeriodicalId":124893,"journal":{"name":"IEEE Instrumentation and Measurement Technology Conference Sensing, Processing, Networking. IMTC Proceedings","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Fuzzy modelling and control using parameterised linear filters\",\"authors\":\"Z. Papp\",\"doi\":\"10.1109/IMTC.1997.610182\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a nonlinear identification scheme, which consists of a linear dynamical section (filter) and a nonlinear zero-memory section (implemented by a fuzzy mapping). Only the filter section is on the primary signal path. The nonlinear mapping (depending on the system input and state) delivers the filter parameters. The identification assumes structural knowledge about the process with proper parameterisation. An adaption procedure is introduced, which tunes the nonlinear mapping (e.g. membership function parameters) to minimize identification error. The adaption procedure is driven by the approximate dynamical sensitivity model of the system thus the method is very effective with respect to the number of training steps necessary to reach the accuracy required. The scheme proposed can incorporate a priori knowledge on two levels (structure and fuzzy rule set). One of the most distinctive features of the scheme is that it directly supports controller design and/or (on-line) tuning.\",\"PeriodicalId\":124893,\"journal\":{\"name\":\"IEEE Instrumentation and Measurement Technology Conference Sensing, Processing, Networking. IMTC Proceedings\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Instrumentation and Measurement Technology Conference Sensing, Processing, Networking. IMTC Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMTC.1997.610182\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Instrumentation and Measurement Technology Conference Sensing, Processing, Networking. IMTC Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMTC.1997.610182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

本文提出了一种非线性辨识方案,该方案由线性动态部分(滤波器)和非线性零记忆部分(模糊映射实现)组成。只有滤波器部分在主信号路径上。非线性映射(取决于系统输入和状态)提供过滤器参数。这种识别假定了有关过程的结构知识和适当的参数化。引入了一种自适应过程,对非线性映射(如隶属函数参数)进行自适应,使识别误差最小化。自适应过程由系统的近似动态灵敏度模型驱动,因此该方法在达到所需精度所需的训练步数方面是非常有效的。该方案可以在两个层次(结构和模糊规则集)上包含先验知识。该方案最显著的特点之一是它直接支持控制器设计和/或(在线)调谐。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fuzzy modelling and control using parameterised linear filters
The paper presents a nonlinear identification scheme, which consists of a linear dynamical section (filter) and a nonlinear zero-memory section (implemented by a fuzzy mapping). Only the filter section is on the primary signal path. The nonlinear mapping (depending on the system input and state) delivers the filter parameters. The identification assumes structural knowledge about the process with proper parameterisation. An adaption procedure is introduced, which tunes the nonlinear mapping (e.g. membership function parameters) to minimize identification error. The adaption procedure is driven by the approximate dynamical sensitivity model of the system thus the method is very effective with respect to the number of training steps necessary to reach the accuracy required. The scheme proposed can incorporate a priori knowledge on two levels (structure and fuzzy rule set). One of the most distinctive features of the scheme is that it directly supports controller design and/or (on-line) tuning.
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
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信