Fault-Tolerant Control for Dynamic Positioning Vessel With Thruster Faults Based on the Neural Modified Extended State Observer
A new fault-tolerant control (FTC) method based on the neural modified extended state observer (NMESO) is proposed for dynamic positioning (DP) vessel with thruster faults in this article. Through incorporating a compound orthogonal neural network (CONN) into the design process of the modified exten...
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Veröffentlicht in: | IEEE transactions on systems, man, and cybernetics. Systems man, and cybernetics. Systems, 2021-09, Vol.51 (9), p.5905-5917 |
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description | A new fault-tolerant control (FTC) method based on the neural modified extended state observer (NMESO) is proposed for dynamic positioning (DP) vessel with thruster faults in this article. Through incorporating a compound orthogonal neural network (CONN) into the design process of the modified extended state observer (MESO), the NMESO is developed to estimate the uncertainties in the DP control system, such as the environmental disturbances and the unknown dynamics, as well as the thruster faults simultaneously without knowing any prior information of them. With the help of the accurate estimation of the total uncertainties by NMESO, a PD-like feedback controller is established to realize the FTC of the DP vessel toward the thruster faults. By utilizing the Lyapunov stability analysis, it is proved that all the error signals in the closed-loop cascade system formed by the NMESO and PD-like feedback controller are uniformly ultimately bounded (UUB) and the bounds could be arbitrarily small by choosing appropriate parameters. Simulation experiments on two typical thruster fault scenarios are carried out to validate the effectiveness and the performance of the proposed NMESO-FTC compared with the conventional ESO-FTC. The simulation results show the proposed approach has better fault-tolerant performance. |
doi_str_mv | 10.1109/TSMC.2019.2956806 |
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Through incorporating a compound orthogonal neural network (CONN) into the design process of the modified extended state observer (MESO), the NMESO is developed to estimate the uncertainties in the DP control system, such as the environmental disturbances and the unknown dynamics, as well as the thruster faults simultaneously without knowing any prior information of them. With the help of the accurate estimation of the total uncertainties by NMESO, a PD-like feedback controller is established to realize the FTC of the DP vessel toward the thruster faults. By utilizing the Lyapunov stability analysis, it is proved that all the error signals in the closed-loop cascade system formed by the NMESO and PD-like feedback controller are uniformly ultimately bounded (UUB) and the bounds could be arbitrarily small by choosing appropriate parameters. Simulation experiments on two typical thruster fault scenarios are carried out to validate the effectiveness and the performance of the proposed NMESO-FTC compared with the conventional ESO-FTC. The simulation results show the proposed approach has better fault-tolerant performance.</description><identifier>ISSN: 2168-2216</identifier><identifier>EISSN: 2168-2232</identifier><identifier>DOI: 10.1109/TSMC.2019.2956806</identifier><identifier>CODEN: ITSMFE</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Attitude control ; Compound orthogonal neural network (CONN) ; Control systems ; Design modifications ; dynamic positioning (DP) ; Error signals ; Fault tolerance ; Fault tolerant systems ; fault-tolerant control (FTC) ; Faults ; Feedback control ; neural modified extended state observer (NMESO) ; Neural networks ; Observers ; Stability analysis ; State observers ; thruster faults ; Uncertainty ; Vessels</subject><ispartof>IEEE transactions on systems, man, and cybernetics. Systems, 2021-09, Vol.51 (9), p.5905-5917</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-8934c8deac3b23005dd2717643d91ba293496f538f97dd3dc278f75e947dc7263</citedby><cites>FETCH-LOGICAL-c293t-8934c8deac3b23005dd2717643d91ba293496f538f97dd3dc278f75e947dc7263</cites><orcidid>0000-0001-6598-3413 ; 0000-0003-3723-468X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8936559$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8936559$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Yu, Wenzhao</creatorcontrib><creatorcontrib>Xu, Haixiang</creatorcontrib><creatorcontrib>Han, Xin</creatorcontrib><creatorcontrib>Chen, Yahao</creatorcontrib><creatorcontrib>Zhu, Mengfei</creatorcontrib><title>Fault-Tolerant Control for Dynamic Positioning Vessel With Thruster Faults Based on the Neural Modified Extended State Observer</title><title>IEEE transactions on systems, man, and cybernetics. Systems</title><addtitle>TSMC</addtitle><description>A new fault-tolerant control (FTC) method based on the neural modified extended state observer (NMESO) is proposed for dynamic positioning (DP) vessel with thruster faults in this article. Through incorporating a compound orthogonal neural network (CONN) into the design process of the modified extended state observer (MESO), the NMESO is developed to estimate the uncertainties in the DP control system, such as the environmental disturbances and the unknown dynamics, as well as the thruster faults simultaneously without knowing any prior information of them. With the help of the accurate estimation of the total uncertainties by NMESO, a PD-like feedback controller is established to realize the FTC of the DP vessel toward the thruster faults. By utilizing the Lyapunov stability analysis, it is proved that all the error signals in the closed-loop cascade system formed by the NMESO and PD-like feedback controller are uniformly ultimately bounded (UUB) and the bounds could be arbitrarily small by choosing appropriate parameters. Simulation experiments on two typical thruster fault scenarios are carried out to validate the effectiveness and the performance of the proposed NMESO-FTC compared with the conventional ESO-FTC. The simulation results show the proposed approach has better fault-tolerant performance.</description><subject>Attitude control</subject><subject>Compound orthogonal neural network (CONN)</subject><subject>Control systems</subject><subject>Design modifications</subject><subject>dynamic positioning (DP)</subject><subject>Error signals</subject><subject>Fault tolerance</subject><subject>Fault tolerant systems</subject><subject>fault-tolerant control (FTC)</subject><subject>Faults</subject><subject>Feedback control</subject><subject>neural modified extended state observer (NMESO)</subject><subject>Neural networks</subject><subject>Observers</subject><subject>Stability analysis</subject><subject>State observers</subject><subject>thruster faults</subject><subject>Uncertainty</subject><subject>Vessels</subject><issn>2168-2216</issn><issn>2168-2232</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kF9PwjAUxRejiQT5AMaXJj4P-2fr1kdFURMQE6Y-LmW9k5LRYtsZefKrO4TwdE9uzjn35hdFlwQPCcHipphPR0OKiRhSkfIc85OoRwnPY0oZPT1qws-jgfcrjDGhOWeY96LfsWybEBe2ASdNQCNrgrMNqq1D91sj17pCr9broK3R5hO9g_fQoA8dlqhYutYHcOi_w6M76UEha1BYAnqB1skGTa3Ste7WDz8BjOrEPMgAaLbw4L7BXURntWw8DA6zH72NH4rRUzyZPT6PbidxRQULcS5YUuUKZMUWlGGcKkUzkvGEKUEWsvMkgtcpy2uRKcVURbO8zlIQSaaqjHLWj673vRtnv1rwoVzZ1pnuZElT3mHCKSadi-xdlbPeO6jLjdNr6bYlweUOdblDXe5QlwfUXeZqn9EAcPR3D_M0FewPPcx6zg</recordid><startdate>20210901</startdate><enddate>20210901</enddate><creator>Yu, Wenzhao</creator><creator>Xu, Haixiang</creator><creator>Han, Xin</creator><creator>Chen, Yahao</creator><creator>Zhu, Mengfei</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>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-6598-3413</orcidid><orcidid>https://orcid.org/0000-0003-3723-468X</orcidid></search><sort><creationdate>20210901</creationdate><title>Fault-Tolerant Control for Dynamic Positioning Vessel With Thruster Faults Based on the Neural Modified Extended State Observer</title><author>Yu, Wenzhao ; Xu, Haixiang ; Han, Xin ; Chen, Yahao ; Zhu, Mengfei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-8934c8deac3b23005dd2717643d91ba293496f538f97dd3dc278f75e947dc7263</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Attitude control</topic><topic>Compound orthogonal neural network (CONN)</topic><topic>Control systems</topic><topic>Design modifications</topic><topic>dynamic positioning (DP)</topic><topic>Error signals</topic><topic>Fault tolerance</topic><topic>Fault tolerant systems</topic><topic>fault-tolerant control (FTC)</topic><topic>Faults</topic><topic>Feedback control</topic><topic>neural modified extended state observer (NMESO)</topic><topic>Neural networks</topic><topic>Observers</topic><topic>Stability analysis</topic><topic>State observers</topic><topic>thruster faults</topic><topic>Uncertainty</topic><topic>Vessels</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yu, Wenzhao</creatorcontrib><creatorcontrib>Xu, Haixiang</creatorcontrib><creatorcontrib>Han, Xin</creatorcontrib><creatorcontrib>Chen, Yahao</creatorcontrib><creatorcontrib>Zhu, Mengfei</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>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on systems, man, and cybernetics. Systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yu, Wenzhao</au><au>Xu, Haixiang</au><au>Han, Xin</au><au>Chen, Yahao</au><au>Zhu, Mengfei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fault-Tolerant Control for Dynamic Positioning Vessel With Thruster Faults Based on the Neural Modified Extended State Observer</atitle><jtitle>IEEE transactions on systems, man, and cybernetics. Systems</jtitle><stitle>TSMC</stitle><date>2021-09-01</date><risdate>2021</risdate><volume>51</volume><issue>9</issue><spage>5905</spage><epage>5917</epage><pages>5905-5917</pages><issn>2168-2216</issn><eissn>2168-2232</eissn><coden>ITSMFE</coden><abstract>A new fault-tolerant control (FTC) method based on the neural modified extended state observer (NMESO) is proposed for dynamic positioning (DP) vessel with thruster faults in this article. Through incorporating a compound orthogonal neural network (CONN) into the design process of the modified extended state observer (MESO), the NMESO is developed to estimate the uncertainties in the DP control system, such as the environmental disturbances and the unknown dynamics, as well as the thruster faults simultaneously without knowing any prior information of them. With the help of the accurate estimation of the total uncertainties by NMESO, a PD-like feedback controller is established to realize the FTC of the DP vessel toward the thruster faults. By utilizing the Lyapunov stability analysis, it is proved that all the error signals in the closed-loop cascade system formed by the NMESO and PD-like feedback controller are uniformly ultimately bounded (UUB) and the bounds could be arbitrarily small by choosing appropriate parameters. Simulation experiments on two typical thruster fault scenarios are carried out to validate the effectiveness and the performance of the proposed NMESO-FTC compared with the conventional ESO-FTC. The simulation results show the proposed approach has better fault-tolerant performance.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TSMC.2019.2956806</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0001-6598-3413</orcidid><orcidid>https://orcid.org/0000-0003-3723-468X</orcidid></addata></record> |
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subjects | Attitude control Compound orthogonal neural network (CONN) Control systems Design modifications dynamic positioning (DP) Error signals Fault tolerance Fault tolerant systems fault-tolerant control (FTC) Faults Feedback control neural modified extended state observer (NMESO) Neural networks Observers Stability analysis State observers thruster faults Uncertainty Vessels |
title | Fault-Tolerant Control for Dynamic Positioning Vessel With Thruster Faults Based on the Neural Modified Extended State Observer |
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