Loading…

Regulating Control of In-Pipe Intelligent Isolation Plugging Tool Based on Adaptive Dynamic Programming

AbstractIn-pipe intelligent isolation plugging tools (IPTs) are crucial in pipeline maintenance. During the plugging process, the flow field around the IPT changes drastically, resulting in vibration and instability of the plugging process. Therefore, three foldable spoilers were designed at the tai...

Full description

Saved in:
Bibliographic Details
Published in:Journal of pipeline systems 2022-05, Vol.13 (2)
Main Authors: Miao, Xingyuan, Zhao, Hong
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-a388t-dc8de854eaf47b64f17a5c5ee8f4cead9c431d189d05ce766efe20ff88672da33
cites cdi_FETCH-LOGICAL-a388t-dc8de854eaf47b64f17a5c5ee8f4cead9c431d189d05ce766efe20ff88672da33
container_end_page
container_issue 2
container_start_page
container_title Journal of pipeline systems
container_volume 13
creator Miao, Xingyuan
Zhao, Hong
description AbstractIn-pipe intelligent isolation plugging tools (IPTs) are crucial in pipeline maintenance. During the plugging process, the flow field around the IPT changes drastically, resulting in vibration and instability of the plugging process. Therefore, three foldable spoilers were designed at the tail of the IPT to reduce the vibration of the IPT. First, a disturbing flow experiment of IPT with spoilers was designed. A mathematical model of the pneumatic spoiler control system was established to regulate the spoiler angles. Second, based on the experimental data, a bidirectional long short-term memory (Bi-LSTM) neural network predictor between the plugging states, the spoiler angles, and the pressure gradient was established. Then, an adaptive dynamic programming controller was designed to select the optimal control action for each plugging state, thereby reducing the pressure gradient. Finally, Python and MATLAB/Simulink were used for simulation. The results showed that prediction errors were controlled within 9%, and the controller could reduce the pressure gradient during the plugging process by an average of 25.94%, which alleviated the vibration of the IPT and achieved a smooth plugging operation.
doi_str_mv 10.1061/(ASCE)PS.1949-1204.0000635
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2622293094</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2622293094</sourcerecordid><originalsourceid>FETCH-LOGICAL-a388t-dc8de854eaf47b64f17a5c5ee8f4cead9c431d189d05ce766efe20ff88672da33</originalsourceid><addsrcrecordid>eNp1kFFLwzAQx4MoOOa-Q9AXfehM0jRtfZt16mBgcfM5xPZSOtqmJq2wb2_LNn3yXu44fv87-CF0TcmcEkHvbxebZHmXbuY05rFHGeFzMpTwgzM0-d2dn2Yak0s0c243Qj7ljNMJKt6h6CvVlU2BE9N01lTYaLxqvLRsYegdVFVZQNPhlTMjaBqcVn1RjImtGfBH5SDHw3qRq7YrvwE_7RtVlxlOrSmsqusBvUIXWlUOZsc-RR_Py23y6q3fXlbJYu0pP4o6L8-iHKKAg9I8_BRc01AFWQAQaZ6ByuOM-zSnUZyTIINQCNDAiNZRJEKWK9-fopvD3daarx5cJ3emt83wUjLBGIt9EvOBejhQmTXOWdCytWWt7F5SIke3Uo5uZbqRozs5epRHt0NYHMLKZfB3_pT8P_gDRbp-9A</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2622293094</pqid></control><display><type>article</type><title>Regulating Control of In-Pipe Intelligent Isolation Plugging Tool Based on Adaptive Dynamic Programming</title><source>American Society Of Civil Engineers (ASCE) Journals</source><creator>Miao, Xingyuan ; Zhao, Hong</creator><creatorcontrib>Miao, Xingyuan ; Zhao, Hong</creatorcontrib><description>AbstractIn-pipe intelligent isolation plugging tools (IPTs) are crucial in pipeline maintenance. During the plugging process, the flow field around the IPT changes drastically, resulting in vibration and instability of the plugging process. Therefore, three foldable spoilers were designed at the tail of the IPT to reduce the vibration of the IPT. First, a disturbing flow experiment of IPT with spoilers was designed. A mathematical model of the pneumatic spoiler control system was established to regulate the spoiler angles. Second, based on the experimental data, a bidirectional long short-term memory (Bi-LSTM) neural network predictor between the plugging states, the spoiler angles, and the pressure gradient was established. Then, an adaptive dynamic programming controller was designed to select the optimal control action for each plugging state, thereby reducing the pressure gradient. Finally, Python and MATLAB/Simulink were used for simulation. The results showed that prediction errors were controlled within 9%, and the controller could reduce the pressure gradient during the plugging process by an average of 25.94%, which alleviated the vibration of the IPT and achieved a smooth plugging operation.</description><identifier>ISSN: 1949-1190</identifier><identifier>EISSN: 1949-1204</identifier><identifier>DOI: 10.1061/(ASCE)PS.1949-1204.0000635</identifier><language>eng</language><publisher>Reston: American Society of Civil Engineers</publisher><subject>Adaptive control ; Control systems ; Control systems design ; Controllers ; Dynamic programming ; Flow stability ; Mathematical models ; Neural networks ; Optimal control ; Pipes ; Plugging ; Pressure gradients ; Submarine pipelines ; Technical Papers ; Vibration</subject><ispartof>Journal of pipeline systems, 2022-05, Vol.13 (2)</ispartof><rights>2022 American Society of Civil Engineers</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a388t-dc8de854eaf47b64f17a5c5ee8f4cead9c431d189d05ce766efe20ff88672da33</citedby><cites>FETCH-LOGICAL-a388t-dc8de854eaf47b64f17a5c5ee8f4cead9c431d189d05ce766efe20ff88672da33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttp://ascelibrary.org/doi/pdf/10.1061/(ASCE)PS.1949-1204.0000635$$EPDF$$P50$$Gasce$$H</linktopdf><linktohtml>$$Uhttp://ascelibrary.org/doi/abs/10.1061/(ASCE)PS.1949-1204.0000635$$EHTML$$P50$$Gasce$$H</linktohtml><link.rule.ids>314,780,784,3252,10068,27924,27925,76191,76199</link.rule.ids></links><search><creatorcontrib>Miao, Xingyuan</creatorcontrib><creatorcontrib>Zhao, Hong</creatorcontrib><title>Regulating Control of In-Pipe Intelligent Isolation Plugging Tool Based on Adaptive Dynamic Programming</title><title>Journal of pipeline systems</title><description>AbstractIn-pipe intelligent isolation plugging tools (IPTs) are crucial in pipeline maintenance. During the plugging process, the flow field around the IPT changes drastically, resulting in vibration and instability of the plugging process. Therefore, three foldable spoilers were designed at the tail of the IPT to reduce the vibration of the IPT. First, a disturbing flow experiment of IPT with spoilers was designed. A mathematical model of the pneumatic spoiler control system was established to regulate the spoiler angles. Second, based on the experimental data, a bidirectional long short-term memory (Bi-LSTM) neural network predictor between the plugging states, the spoiler angles, and the pressure gradient was established. Then, an adaptive dynamic programming controller was designed to select the optimal control action for each plugging state, thereby reducing the pressure gradient. Finally, Python and MATLAB/Simulink were used for simulation. The results showed that prediction errors were controlled within 9%, and the controller could reduce the pressure gradient during the plugging process by an average of 25.94%, which alleviated the vibration of the IPT and achieved a smooth plugging operation.</description><subject>Adaptive control</subject><subject>Control systems</subject><subject>Control systems design</subject><subject>Controllers</subject><subject>Dynamic programming</subject><subject>Flow stability</subject><subject>Mathematical models</subject><subject>Neural networks</subject><subject>Optimal control</subject><subject>Pipes</subject><subject>Plugging</subject><subject>Pressure gradients</subject><subject>Submarine pipelines</subject><subject>Technical Papers</subject><subject>Vibration</subject><issn>1949-1190</issn><issn>1949-1204</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp1kFFLwzAQx4MoOOa-Q9AXfehM0jRtfZt16mBgcfM5xPZSOtqmJq2wb2_LNn3yXu44fv87-CF0TcmcEkHvbxebZHmXbuY05rFHGeFzMpTwgzM0-d2dn2Yak0s0c243Qj7ljNMJKt6h6CvVlU2BE9N01lTYaLxqvLRsYegdVFVZQNPhlTMjaBqcVn1RjImtGfBH5SDHw3qRq7YrvwE_7RtVlxlOrSmsqusBvUIXWlUOZsc-RR_Py23y6q3fXlbJYu0pP4o6L8-iHKKAg9I8_BRc01AFWQAQaZ6ByuOM-zSnUZyTIINQCNDAiNZRJEKWK9-fopvD3daarx5cJ3emt83wUjLBGIt9EvOBejhQmTXOWdCytWWt7F5SIke3Uo5uZbqRozs5epRHt0NYHMLKZfB3_pT8P_gDRbp-9A</recordid><startdate>20220501</startdate><enddate>20220501</enddate><creator>Miao, Xingyuan</creator><creator>Zhao, Hong</creator><general>American Society of Civil Engineers</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>F1W</scope><scope>FR3</scope><scope>H96</scope><scope>KR7</scope><scope>L.G</scope></search><sort><creationdate>20220501</creationdate><title>Regulating Control of In-Pipe Intelligent Isolation Plugging Tool Based on Adaptive Dynamic Programming</title><author>Miao, Xingyuan ; Zhao, Hong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a388t-dc8de854eaf47b64f17a5c5ee8f4cead9c431d189d05ce766efe20ff88672da33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Adaptive control</topic><topic>Control systems</topic><topic>Control systems design</topic><topic>Controllers</topic><topic>Dynamic programming</topic><topic>Flow stability</topic><topic>Mathematical models</topic><topic>Neural networks</topic><topic>Optimal control</topic><topic>Pipes</topic><topic>Plugging</topic><topic>Pressure gradients</topic><topic>Submarine pipelines</topic><topic>Technical Papers</topic><topic>Vibration</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Miao, Xingyuan</creatorcontrib><creatorcontrib>Zhao, Hong</creatorcontrib><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy &amp; Non-Living Resources</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><jtitle>Journal of pipeline systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Miao, Xingyuan</au><au>Zhao, Hong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Regulating Control of In-Pipe Intelligent Isolation Plugging Tool Based on Adaptive Dynamic Programming</atitle><jtitle>Journal of pipeline systems</jtitle><date>2022-05-01</date><risdate>2022</risdate><volume>13</volume><issue>2</issue><issn>1949-1190</issn><eissn>1949-1204</eissn><abstract>AbstractIn-pipe intelligent isolation plugging tools (IPTs) are crucial in pipeline maintenance. During the plugging process, the flow field around the IPT changes drastically, resulting in vibration and instability of the plugging process. Therefore, three foldable spoilers were designed at the tail of the IPT to reduce the vibration of the IPT. First, a disturbing flow experiment of IPT with spoilers was designed. A mathematical model of the pneumatic spoiler control system was established to regulate the spoiler angles. Second, based on the experimental data, a bidirectional long short-term memory (Bi-LSTM) neural network predictor between the plugging states, the spoiler angles, and the pressure gradient was established. Then, an adaptive dynamic programming controller was designed to select the optimal control action for each plugging state, thereby reducing the pressure gradient. Finally, Python and MATLAB/Simulink were used for simulation. The results showed that prediction errors were controlled within 9%, and the controller could reduce the pressure gradient during the plugging process by an average of 25.94%, which alleviated the vibration of the IPT and achieved a smooth plugging operation.</abstract><cop>Reston</cop><pub>American Society of Civil Engineers</pub><doi>10.1061/(ASCE)PS.1949-1204.0000635</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1949-1190
ispartof Journal of pipeline systems, 2022-05, Vol.13 (2)
issn 1949-1190
1949-1204
language eng
recordid cdi_proquest_journals_2622293094
source American Society Of Civil Engineers (ASCE) Journals
subjects Adaptive control
Control systems
Control systems design
Controllers
Dynamic programming
Flow stability
Mathematical models
Neural networks
Optimal control
Pipes
Plugging
Pressure gradients
Submarine pipelines
Technical Papers
Vibration
title Regulating Control of In-Pipe Intelligent Isolation Plugging Tool Based on Adaptive Dynamic Programming
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T08%3A30%3A59IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Regulating%20Control%20of%20In-Pipe%20Intelligent%20Isolation%20Plugging%20Tool%20Based%20on%20Adaptive%20Dynamic%20Programming&rft.jtitle=Journal%20of%20pipeline%20systems&rft.au=Miao,%20Xingyuan&rft.date=2022-05-01&rft.volume=13&rft.issue=2&rft.issn=1949-1190&rft.eissn=1949-1204&rft_id=info:doi/10.1061/(ASCE)PS.1949-1204.0000635&rft_dat=%3Cproquest_cross%3E2622293094%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-a388t-dc8de854eaf47b64f17a5c5ee8f4cead9c431d189d05ce766efe20ff88672da33%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2622293094&rft_id=info:pmid/&rfr_iscdi=true