Decentralized finite-time adaptive fault-tolerant synchronization tracking control for multiple UAVs with prescribed performance
•A decentralized fault-tolerant control scheme is developed for multiple UAVs against actuator faults.•Finite-time synchronization tracking control is achieved by utilizing the fractional power of the synchronized errors.•The prescribed performance function is used to constrain the synchronization t...
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Veröffentlicht in: | Journal of the Franklin Institute 2020-11, Vol.357 (16), p.11830-11862 |
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creator | Yu, Ziquan Zhang, Youmin Liu, Zhixiang Qu, Yaohong Su, Chun-Yi Jiang, Bin |
description | •A decentralized fault-tolerant control scheme is developed for multiple UAVs against actuator faults.•Finite-time synchronization tracking control is achieved by utilizing the fractional power of the synchronized errors.•The prescribed performance function is used to constrain the synchronization tracking performance.•The norms of the weighting vectors are used for the estimation to reduce the computational burden.
This paper is concerned with the decentralized finite-time fault-tolerant attitude synchronization tracking control problem for multiple unmanned aerial vehicles (multi-UAVs) with prescribed performance. Failure to counteract actuator faults in the formation flight of multi-UAVs in a limited time may lead to catastrophic consequences. By integrating the prescribed performance functions into the synchronization tracking errors, a new set of errors is defined. Based on the transformed errors, a finite-time attitude synchronization tracking control scheme is developed by using neural networks and finite-time differentiator techniques. The neural networks are utilized to identify the unknown nonlinear terms induced by uncertainties and actuator faults. To reduce the computational burden caused by estimating the weight vectors, the norms of weight vectors are used for the estimation, such that the number of adaptive parameters is significantly reduced and independent from the number of neurons. The finite-time differentiators are utilized to estimate the intermediate control signals and their derivatives. Moreover, auxiliary dynamic signals with explicit consideration of differentiator estimation errors are introduced into the control scheme to guarantee the finite-time convergences of the synchronized tracking errors. Furthermore, it is shown that by using the Lyapunov method, all UAVs can track their individual attitude references, while the synchronized tracking errors among UAVs are all bounded in finite time and confined within the prescribed performance bounds. Finally, comparative simulation studies on multi-UAVs are conducted to verify the effectiveness of the proposed scheme. |
doi_str_mv | 10.1016/j.jfranklin.2019.11.056 |
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This paper is concerned with the decentralized finite-time fault-tolerant attitude synchronization tracking control problem for multiple unmanned aerial vehicles (multi-UAVs) with prescribed performance. Failure to counteract actuator faults in the formation flight of multi-UAVs in a limited time may lead to catastrophic consequences. By integrating the prescribed performance functions into the synchronization tracking errors, a new set of errors is defined. Based on the transformed errors, a finite-time attitude synchronization tracking control scheme is developed by using neural networks and finite-time differentiator techniques. The neural networks are utilized to identify the unknown nonlinear terms induced by uncertainties and actuator faults. To reduce the computational burden caused by estimating the weight vectors, the norms of weight vectors are used for the estimation, such that the number of adaptive parameters is significantly reduced and independent from the number of neurons. The finite-time differentiators are utilized to estimate the intermediate control signals and their derivatives. Moreover, auxiliary dynamic signals with explicit consideration of differentiator estimation errors are introduced into the control scheme to guarantee the finite-time convergences of the synchronized tracking errors. Furthermore, it is shown that by using the Lyapunov method, all UAVs can track their individual attitude references, while the synchronized tracking errors among UAVs are all bounded in finite time and confined within the prescribed performance bounds. Finally, comparative simulation studies on multi-UAVs are conducted to verify the effectiveness of the proposed scheme.</description><identifier>ISSN: 0016-0032</identifier><identifier>EISSN: 1879-2693</identifier><identifier>EISSN: 0016-0032</identifier><identifier>DOI: 10.1016/j.jfranklin.2019.11.056</identifier><language>eng</language><publisher>Elmsford: Elsevier Ltd</publisher><subject>Actuators ; Adaptive control ; Attitudes ; Catastrophic failure analysis ; Differentiators ; Fault detection ; Fault tolerance ; Finite element analysis ; Formation flying ; Neural networks ; Norms ; Synchronism ; Time synchronization ; Tracking control ; Tracking control systems ; Tracking errors ; Unmanned aerial vehicles ; Weight</subject><ispartof>Journal of the Franklin Institute, 2020-11, Vol.357 (16), p.11830-11862</ispartof><rights>2019 The Franklin Institute</rights><rights>Copyright Elsevier Science Ltd. Nov 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c343t-619b69c6aaa5308613e4aba9b80ea0a87f3f6da2a8d324aac768a1531e21cb2e3</citedby><cites>FETCH-LOGICAL-c343t-619b69c6aaa5308613e4aba9b80ea0a87f3f6da2a8d324aac768a1531e21cb2e3</cites><orcidid>0000-0002-1026-4195 ; 0000-0002-9731-5943</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jfranklin.2019.11.056$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3548,27923,27924,45994</link.rule.ids></links><search><creatorcontrib>Yu, Ziquan</creatorcontrib><creatorcontrib>Zhang, Youmin</creatorcontrib><creatorcontrib>Liu, Zhixiang</creatorcontrib><creatorcontrib>Qu, Yaohong</creatorcontrib><creatorcontrib>Su, Chun-Yi</creatorcontrib><creatorcontrib>Jiang, Bin</creatorcontrib><title>Decentralized finite-time adaptive fault-tolerant synchronization tracking control for multiple UAVs with prescribed performance</title><title>Journal of the Franklin Institute</title><description>•A decentralized fault-tolerant control scheme is developed for multiple UAVs against actuator faults.•Finite-time synchronization tracking control is achieved by utilizing the fractional power of the synchronized errors.•The prescribed performance function is used to constrain the synchronization tracking performance.•The norms of the weighting vectors are used for the estimation to reduce the computational burden.
This paper is concerned with the decentralized finite-time fault-tolerant attitude synchronization tracking control problem for multiple unmanned aerial vehicles (multi-UAVs) with prescribed performance. Failure to counteract actuator faults in the formation flight of multi-UAVs in a limited time may lead to catastrophic consequences. By integrating the prescribed performance functions into the synchronization tracking errors, a new set of errors is defined. Based on the transformed errors, a finite-time attitude synchronization tracking control scheme is developed by using neural networks and finite-time differentiator techniques. The neural networks are utilized to identify the unknown nonlinear terms induced by uncertainties and actuator faults. To reduce the computational burden caused by estimating the weight vectors, the norms of weight vectors are used for the estimation, such that the number of adaptive parameters is significantly reduced and independent from the number of neurons. The finite-time differentiators are utilized to estimate the intermediate control signals and their derivatives. Moreover, auxiliary dynamic signals with explicit consideration of differentiator estimation errors are introduced into the control scheme to guarantee the finite-time convergences of the synchronized tracking errors. Furthermore, it is shown that by using the Lyapunov method, all UAVs can track their individual attitude references, while the synchronized tracking errors among UAVs are all bounded in finite time and confined within the prescribed performance bounds. Finally, comparative simulation studies on multi-UAVs are conducted to verify the effectiveness of the proposed scheme.</description><subject>Actuators</subject><subject>Adaptive control</subject><subject>Attitudes</subject><subject>Catastrophic failure analysis</subject><subject>Differentiators</subject><subject>Fault detection</subject><subject>Fault tolerance</subject><subject>Finite element analysis</subject><subject>Formation flying</subject><subject>Neural networks</subject><subject>Norms</subject><subject>Synchronism</subject><subject>Time synchronization</subject><subject>Tracking control</subject><subject>Tracking control systems</subject><subject>Tracking errors</subject><subject>Unmanned aerial vehicles</subject><subject>Weight</subject><issn>0016-0032</issn><issn>1879-2693</issn><issn>0016-0032</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNqFkEFr3DAQhUVpoNskvyGCnu1KlleWj0uSpoVAL02uYiyPm3G8kitpU5JTf3oUtvTa0zDwvvd4j7ELKWoppP481_MUwT8u5OtGyL6WshZb_Y5tpOn6qtG9es82okgrIVTzgX1MaS5vJ4XYsD9X6NDnCAu94Mgn8pSxyrRHDiOsmZ6QT3BYcpXDgiUn8_Ts3UMMnl4gU_C8wO6R_E_uQjEKC59C5PuC0Logv9vdJ_6b8gNfIyYXaSgxK8Yi2oN3eMZOJlgSnv-9p-zuy_WPy6_V7febb5e728qpVuVKy37QvdMAsFXCaKmwhQH6wQgEAaab1KRHaMCMqmkBXKcNyK2S2Eg3NKhO2aej7xrDrwOmbOdwiL5E2qbVRhtj-raouqPKxZBSxMmukfYQn60U9m1uO9t_c9u3ua2UtsxdyN2RxFLiiTDa5AhLwZEiumzHQP_1eAWeDpGK</recordid><startdate>202011</startdate><enddate>202011</enddate><creator>Yu, Ziquan</creator><creator>Zhang, Youmin</creator><creator>Liu, Zhixiang</creator><creator>Qu, Yaohong</creator><creator>Su, Chun-Yi</creator><creator>Jiang, Bin</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><orcidid>https://orcid.org/0000-0002-1026-4195</orcidid><orcidid>https://orcid.org/0000-0002-9731-5943</orcidid></search><sort><creationdate>202011</creationdate><title>Decentralized finite-time adaptive fault-tolerant synchronization tracking control for multiple UAVs with prescribed performance</title><author>Yu, Ziquan ; Zhang, Youmin ; Liu, Zhixiang ; Qu, Yaohong ; Su, Chun-Yi ; Jiang, Bin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c343t-619b69c6aaa5308613e4aba9b80ea0a87f3f6da2a8d324aac768a1531e21cb2e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Actuators</topic><topic>Adaptive control</topic><topic>Attitudes</topic><topic>Catastrophic failure analysis</topic><topic>Differentiators</topic><topic>Fault detection</topic><topic>Fault tolerance</topic><topic>Finite element analysis</topic><topic>Formation flying</topic><topic>Neural networks</topic><topic>Norms</topic><topic>Synchronism</topic><topic>Time synchronization</topic><topic>Tracking control</topic><topic>Tracking control systems</topic><topic>Tracking errors</topic><topic>Unmanned aerial vehicles</topic><topic>Weight</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yu, Ziquan</creatorcontrib><creatorcontrib>Zhang, Youmin</creatorcontrib><creatorcontrib>Liu, Zhixiang</creatorcontrib><creatorcontrib>Qu, Yaohong</creatorcontrib><creatorcontrib>Su, Chun-Yi</creatorcontrib><creatorcontrib>Jiang, Bin</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Journal of the Franklin Institute</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yu, Ziquan</au><au>Zhang, Youmin</au><au>Liu, Zhixiang</au><au>Qu, Yaohong</au><au>Su, Chun-Yi</au><au>Jiang, Bin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Decentralized finite-time adaptive fault-tolerant synchronization tracking control for multiple UAVs with prescribed performance</atitle><jtitle>Journal of the Franklin Institute</jtitle><date>2020-11</date><risdate>2020</risdate><volume>357</volume><issue>16</issue><spage>11830</spage><epage>11862</epage><pages>11830-11862</pages><issn>0016-0032</issn><eissn>1879-2693</eissn><eissn>0016-0032</eissn><abstract>•A decentralized fault-tolerant control scheme is developed for multiple UAVs against actuator faults.•Finite-time synchronization tracking control is achieved by utilizing the fractional power of the synchronized errors.•The prescribed performance function is used to constrain the synchronization tracking performance.•The norms of the weighting vectors are used for the estimation to reduce the computational burden.
This paper is concerned with the decentralized finite-time fault-tolerant attitude synchronization tracking control problem for multiple unmanned aerial vehicles (multi-UAVs) with prescribed performance. Failure to counteract actuator faults in the formation flight of multi-UAVs in a limited time may lead to catastrophic consequences. By integrating the prescribed performance functions into the synchronization tracking errors, a new set of errors is defined. Based on the transformed errors, a finite-time attitude synchronization tracking control scheme is developed by using neural networks and finite-time differentiator techniques. The neural networks are utilized to identify the unknown nonlinear terms induced by uncertainties and actuator faults. To reduce the computational burden caused by estimating the weight vectors, the norms of weight vectors are used for the estimation, such that the number of adaptive parameters is significantly reduced and independent from the number of neurons. The finite-time differentiators are utilized to estimate the intermediate control signals and their derivatives. Moreover, auxiliary dynamic signals with explicit consideration of differentiator estimation errors are introduced into the control scheme to guarantee the finite-time convergences of the synchronized tracking errors. Furthermore, it is shown that by using the Lyapunov method, all UAVs can track their individual attitude references, while the synchronized tracking errors among UAVs are all bounded in finite time and confined within the prescribed performance bounds. Finally, comparative simulation studies on multi-UAVs are conducted to verify the effectiveness of the proposed scheme.</abstract><cop>Elmsford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.jfranklin.2019.11.056</doi><tpages>33</tpages><orcidid>https://orcid.org/0000-0002-1026-4195</orcidid><orcidid>https://orcid.org/0000-0002-9731-5943</orcidid></addata></record> |
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subjects | Actuators Adaptive control Attitudes Catastrophic failure analysis Differentiators Fault detection Fault tolerance Finite element analysis Formation flying Neural networks Norms Synchronism Time synchronization Tracking control Tracking control systems Tracking errors Unmanned aerial vehicles Weight |
title | Decentralized finite-time adaptive fault-tolerant synchronization tracking control for multiple UAVs with prescribed performance |
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