LabVIEW Implementation of an Auto-tuning PID Regulator via Grey-predictor

Chien-Ming Lee, Yao-Lun Liu, Hong-Wei Shieh, Chia-Chang Tong
{"title":"LabVIEW Implementation of an Auto-tuning PID Regulator via Grey-predictor","authors":"Chien-Ming Lee, Yao-Lun Liu, Hong-Wei Shieh, Chia-Chang Tong","doi":"10.1109/ICCIS.2006.252318","DOIUrl":null,"url":null,"abstract":"The purpose of this paper is to design and implement a grey prediction controller (GPC) via LabVIEW as a test platform. Grey prediction model GM(1,1) is used with the aid of first-order, digital low-pass alpha filter to refine the estimation of the system response in advance. The prediction is then utilized to modify the parameters of PID controller. Hence, an auto-tuning PID controller according to the forecasting of system response is achieved. LabVIEW software programming with a data acquisition card (model DAQPad-6015) from National Instruments Co. is chosen to provide a high-resolution, however, time-saving solution for developing this auto-tuning control system. One temperature regulation example is arranged and tested to confirm this auto-tuning controller scheme. Test results of this novel grey prediction controller are derived and compared with traditional PID controller. The Grey prediction controller is far better than PID controller in the prospect of both the transient response and steady state response. Best of all, this auto-tuning regulator eliminates the hassle of human interference","PeriodicalId":296028,"journal":{"name":"2006 IEEE Conference on Cybernetics and Intelligent Systems","volume":"30 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE Conference on Cybernetics and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIS.2006.252318","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18

Abstract

The purpose of this paper is to design and implement a grey prediction controller (GPC) via LabVIEW as a test platform. Grey prediction model GM(1,1) is used with the aid of first-order, digital low-pass alpha filter to refine the estimation of the system response in advance. The prediction is then utilized to modify the parameters of PID controller. Hence, an auto-tuning PID controller according to the forecasting of system response is achieved. LabVIEW software programming with a data acquisition card (model DAQPad-6015) from National Instruments Co. is chosen to provide a high-resolution, however, time-saving solution for developing this auto-tuning control system. One temperature regulation example is arranged and tested to confirm this auto-tuning controller scheme. Test results of this novel grey prediction controller are derived and compared with traditional PID controller. The Grey prediction controller is far better than PID controller in the prospect of both the transient response and steady state response. Best of all, this auto-tuning regulator eliminates the hassle of human interference
基于灰色预测器的PID调节器自整定的LabVIEW实现
本文的目的是通过LabVIEW作为测试平台,设计并实现一个灰色预测控制器(GPC)。利用灰色预测模型GM(1,1),借助于一阶数字低通alpha滤波器,对系统响应进行预先细化估计。然后利用预测结果修改PID控制器的参数。从而实现了基于系统响应预测的自整定PID控制器。采用美国国家仪器公司的数据采集卡(型号DAQPad-6015)的LabVIEW软件编程,为开发这种自动调谐控制系统提供了高分辨率,节省时间的解决方案。最后安排了一个温度调节实例并进行了测试,验证了该自整定控制器方案。给出了该灰色预测控制器的实验结果,并与传统PID控制器进行了比较。无论从暂态响应还是稳态响应来看,灰色预测控制器都远远优于PID控制器。最重要的是,这种自动调节调节器消除了人为干扰的麻烦
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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