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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...
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Published in: | Journal of pipeline systems 2022-05, Vol.13 (2) |
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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 |
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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 & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & 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> |
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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 |
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