Design of An Advanced Time Delay Measurement and A Smart Adaptive Unequal Interval Grey Predictor for Real-Time Nonlinear Control Systems
This paper is a generation step for developing a novel control methodology based on a variable sampling period (VSP) approach to deal with nonlinear systems containing random delays. The proposed VSP is constructed from an advanced time delay measurement (TDM) method and a novel time delay predictio...
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Veröffentlicht in: | IEEE transactions on industrial electronics (1982) 2013-10, Vol.60 (10), p.4574-4589 |
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description | This paper is a generation step for developing a novel control methodology based on a variable sampling period (VSP) approach to deal with nonlinear systems containing random delays. The proposed VSP is constructed from an advanced time delay measurement (TDM) method and a novel time delay prediction (TDP) method. The TDM is built to measure real working time of the controlled system, consequently observing a set of actual system delays. Next, the TDP is based on a so-called Smart Adaptive Unequal Interval Grey Model with single-variable first-order - SAUIGM(1,1) to forecast the system delay in the next working step for adjusting the sampling period in order to eliminate bad effects of time delays on the control performance. The SAUIGM(1,1) model was developed from the GM(1,1) model with four significant improvements. It can be easily applied to any practical prediction problem and achieve high prediction accuracy even in case of sparse or largely noisy data. Real-time delay measurements and predictions have been carried out with several examples to verify the proposed TDM and TDP methods. The results indicate that the designed TDM and TDP have strong potential to be applied to the suggested VSP methodology for nonlinear control systems. |
doi_str_mv | 10.1109/TIE.2012.2213552 |
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The proposed VSP is constructed from an advanced time delay measurement (TDM) method and a novel time delay prediction (TDP) method. The TDM is built to measure real working time of the controlled system, consequently observing a set of actual system delays. Next, the TDP is based on a so-called Smart Adaptive Unequal Interval Grey Model with single-variable first-order - SAUIGM(1,1) to forecast the system delay in the next working step for adjusting the sampling period in order to eliminate bad effects of time delays on the control performance. The SAUIGM(1,1) model was developed from the GM(1,1) model with four significant improvements. It can be easily applied to any practical prediction problem and achieve high prediction accuracy even in case of sparse or largely noisy data. Real-time delay measurements and predictions have been carried out with several examples to verify the proposed TDM and TDP methods. The results indicate that the designed TDM and TDP have strong potential to be applied to the suggested VSP methodology for nonlinear control systems.</description><identifier>ISSN: 0278-0046</identifier><identifier>EISSN: 1557-9948</identifier><identifier>DOI: 10.1109/TIE.2012.2213552</identifier><identifier>CODEN: ITIED6</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Adaptation models ; Background value ; Control systems ; Delay ; Delay effects ; error correction ; grey predictor ; Intervals ; Mathematical models ; Nonlinearity ; Predictive models ; quasi-smooth condition ; Real time systems ; real-time measurement ; Robots ; Sampling ; Studies ; Time delay ; Time division multiplexing</subject><ispartof>IEEE transactions on industrial electronics (1982), 2013-10, Vol.60 (10), p.4574-4589</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Oct 2013</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c324t-50f919562e39408ce9e0a9fb6a2ae739913c995c3593c3b7cd9cae040a1be2c73</citedby><cites>FETCH-LOGICAL-c324t-50f919562e39408ce9e0a9fb6a2ae739913c995c3593c3b7cd9cae040a1be2c73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6269994$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27922,27923,54756</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6269994$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Truong, Dinh Quang</creatorcontrib><creatorcontrib>Ahn, Kyoung Kwan</creatorcontrib><creatorcontrib>Trung, Nguyen Thanh</creatorcontrib><title>Design of An Advanced Time Delay Measurement and A Smart Adaptive Unequal Interval Grey Predictor for Real-Time Nonlinear Control Systems</title><title>IEEE transactions on industrial electronics (1982)</title><addtitle>TIE</addtitle><description>This paper is a generation step for developing a novel control methodology based on a variable sampling period (VSP) approach to deal with nonlinear systems containing random delays. The proposed VSP is constructed from an advanced time delay measurement (TDM) method and a novel time delay prediction (TDP) method. The TDM is built to measure real working time of the controlled system, consequently observing a set of actual system delays. Next, the TDP is based on a so-called Smart Adaptive Unequal Interval Grey Model with single-variable first-order - SAUIGM(1,1) to forecast the system delay in the next working step for adjusting the sampling period in order to eliminate bad effects of time delays on the control performance. The SAUIGM(1,1) model was developed from the GM(1,1) model with four significant improvements. It can be easily applied to any practical prediction problem and achieve high prediction accuracy even in case of sparse or largely noisy data. Real-time delay measurements and predictions have been carried out with several examples to verify the proposed TDM and TDP methods. The results indicate that the designed TDM and TDP have strong potential to be applied to the suggested VSP methodology for nonlinear control systems.</description><subject>Adaptation models</subject><subject>Background value</subject><subject>Control systems</subject><subject>Delay</subject><subject>Delay effects</subject><subject>error correction</subject><subject>grey predictor</subject><subject>Intervals</subject><subject>Mathematical models</subject><subject>Nonlinearity</subject><subject>Predictive models</subject><subject>quasi-smooth condition</subject><subject>Real time systems</subject><subject>real-time measurement</subject><subject>Robots</subject><subject>Sampling</subject><subject>Studies</subject><subject>Time delay</subject><subject>Time division multiplexing</subject><issn>0278-0046</issn><issn>1557-9948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkU1rGzEQhkVpoG7Se6EXQS-9rDv62l0djfNRQ5KWxjkLWTtbNuxKjqQ1-Cf0X1epQw89DDOHZ4bhfQj5yGDJGOiv283VkgPjS86ZUIq_IQumVFNpLdu3ZAG8aSsAWb8j71N6AmBSMbUgvy8xDb88DT1debrqDtY77Oh2mJBe4miP9A5tmiNO6DO1vqMr-jDZmAtr93k4IH30-DzbkW58xngow03EI_0RsRtcDpH2pX6iHau_R--DHwePNtJ18DmGkT4cU8YpXZCz3o4JP7z2c_J4fbVdf6tuv99s1qvbygkuc6Wg10yrmqPQElqHGsHqfldbbrERWjPhtFZOKC2c2DWu084iSLBsh9w14px8Od3dx_A8Y8pmGpLDcbQew5wMk6xpWxDAC_r5P_QpzNGX70zJWMi6lrUoFJwoF0NKEXuzj0OJ6GgYmBc3prgxL27Mq5uy8um0MiDiP7zmtS66xB8WX4pJ</recordid><startdate>20131001</startdate><enddate>20131001</enddate><creator>Truong, Dinh Quang</creator><creator>Ahn, Kyoung Kwan</creator><creator>Trung, Nguyen Thanh</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope><scope>F28</scope><scope>FR3</scope></search><sort><creationdate>20131001</creationdate><title>Design of An Advanced Time Delay Measurement and A Smart Adaptive Unequal Interval Grey Predictor for Real-Time Nonlinear Control Systems</title><author>Truong, Dinh Quang ; Ahn, Kyoung Kwan ; Trung, Nguyen Thanh</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c324t-50f919562e39408ce9e0a9fb6a2ae739913c995c3593c3b7cd9cae040a1be2c73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Adaptation models</topic><topic>Background value</topic><topic>Control systems</topic><topic>Delay</topic><topic>Delay effects</topic><topic>error correction</topic><topic>grey predictor</topic><topic>Intervals</topic><topic>Mathematical models</topic><topic>Nonlinearity</topic><topic>Predictive models</topic><topic>quasi-smooth condition</topic><topic>Real time systems</topic><topic>real-time measurement</topic><topic>Robots</topic><topic>Sampling</topic><topic>Studies</topic><topic>Time delay</topic><topic>Time division multiplexing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Truong, Dinh Quang</creatorcontrib><creatorcontrib>Ahn, Kyoung Kwan</creatorcontrib><creatorcontrib>Trung, Nguyen Thanh</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE transactions on industrial electronics (1982)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Truong, Dinh Quang</au><au>Ahn, Kyoung Kwan</au><au>Trung, Nguyen Thanh</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Design of An Advanced Time Delay Measurement and A Smart Adaptive Unequal Interval Grey Predictor for Real-Time Nonlinear Control Systems</atitle><jtitle>IEEE transactions on industrial electronics (1982)</jtitle><stitle>TIE</stitle><date>2013-10-01</date><risdate>2013</risdate><volume>60</volume><issue>10</issue><spage>4574</spage><epage>4589</epage><pages>4574-4589</pages><issn>0278-0046</issn><eissn>1557-9948</eissn><coden>ITIED6</coden><abstract>This paper is a generation step for developing a novel control methodology based on a variable sampling period (VSP) approach to deal with nonlinear systems containing random delays. The proposed VSP is constructed from an advanced time delay measurement (TDM) method and a novel time delay prediction (TDP) method. The TDM is built to measure real working time of the controlled system, consequently observing a set of actual system delays. Next, the TDP is based on a so-called Smart Adaptive Unequal Interval Grey Model with single-variable first-order - SAUIGM(1,1) to forecast the system delay in the next working step for adjusting the sampling period in order to eliminate bad effects of time delays on the control performance. The SAUIGM(1,1) model was developed from the GM(1,1) model with four significant improvements. It can be easily applied to any practical prediction problem and achieve high prediction accuracy even in case of sparse or largely noisy data. Real-time delay measurements and predictions have been carried out with several examples to verify the proposed TDM and TDP methods. The results indicate that the designed TDM and TDP have strong potential to be applied to the suggested VSP methodology for nonlinear control systems.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TIE.2012.2213552</doi><tpages>16</tpages></addata></record> |
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subjects | Adaptation models Background value Control systems Delay Delay effects error correction grey predictor Intervals Mathematical models Nonlinearity Predictive models quasi-smooth condition Real time systems real-time measurement Robots Sampling Studies Time delay Time division multiplexing |
title | Design of An Advanced Time Delay Measurement and A Smart Adaptive Unequal Interval Grey Predictor for Real-Time Nonlinear Control Systems |
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