Evolution of tracking error over time.
<div><p>Floating offshore platforms (FOPs) face the challenge of anchor chain failures due to their unique operating environments. This directly impacts the platform’s safety and stability. Traditional control methods are often ineffective in addressing anchor chain failures. Therefore,...
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2025
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| _version_ | 1849927641807716352 |
|---|---|
| author | Chengliang Chao (22676651) |
| author2 | Yang Liu (4829) Zongkai Wang (20488603) |
| author2_role | author author |
| author_facet | Chengliang Chao (22676651) Yang Liu (4829) Zongkai Wang (20488603) |
| author_role | author |
| dc.creator.none.fl_str_mv | Chengliang Chao (22676651) Yang Liu (4829) Zongkai Wang (20488603) |
| dc.date.none.fl_str_mv | 2025-11-24T18:33:03Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0337290.g006 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Evolution_of_tracking_error_over_time_/30697511 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biophysics Biotechnology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified unique operating environments strategic parameter scheduling platform &# 8217 multiple performance metrics extreme performance optimization traditional control methods rigorous stability analysis real fop system fault handling capabilities edf dual finite triggered dynamic mechanism time convergence paradigm control system time convergence fop systems driven mechanism control design tolerant strategy time learning study proposes study introduces study designs results demonstrate preset finite often ineffective offline phase nonlinear error mixed uncertainties directly impacts based generator asymptotic stability achieve finite |
| dc.title.none.fl_str_mv | Evolution of tracking error over time. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <div><p>Floating offshore platforms (FOPs) face the challenge of anchor chain failures due to their unique operating environments. This directly impacts the platform’s safety and stability. Traditional control methods are often ineffective in addressing anchor chain failures. Therefore, this study proposes a novel event-triggered, self-tuning integrated PID control strategy based on finite-time learning to improve the stability and fault handling capabilities of FOP systems. This study introduces a preset finite-time convergence function based on a time-based generator (TBG) in the control design, combined with a nonlinear error-driven mechanism to achieve finite-time convergence. By integrating a composite variable construction method with neural network approximation techniques, a state mapping mechanism adaptable to mixed uncertainties is established. Furthermore, this study designs a control system that integrates an event-triggered dynamic mechanism with a finite-time convergence paradigm. Through strategic parameter scheduling, this control strategy achieves coordinated optimal configuration and extreme performance optimization under multiple performance metrics in an offline phase. A rigorous stability analysis of the designed control strategy using Lyapunov stability theory demonstrates its effectiveness in terms of asymptotic stability and finite-time convergence. Simulations are conducted on a real FOP system. Results demonstrate that the control strategy effectively addresses anchor chain failures and internal and external uncertain dynamics.</p></div> |
| eu_rights_str_mv | openAccess |
| id | Manara_54c9ae2705b0235858782fa4b67f150c |
| identifier_str_mv | 10.1371/journal.pone.0337290.g006 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30697511 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Evolution of tracking error over time.Chengliang Chao (22676651)Yang Liu (4829)Zongkai Wang (20488603)BiophysicsBiotechnologyBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedunique operating environmentsstrategic parameter schedulingplatform &# 8217multiple performance metricsextreme performance optimizationtraditional control methodsrigorous stability analysisreal fop systemfault handling capabilitiesedf dual finitetriggered dynamic mechanismtime convergence paradigmcontrol systemtime convergencefop systemsdriven mechanismcontrol designtolerant strategytime learningstudy proposesstudy introducesstudy designsresults demonstratepreset finiteoften ineffectiveoffline phasenonlinear errormixed uncertaintiesdirectly impactsbased generatorasymptotic stabilityachieve finite<div><p>Floating offshore platforms (FOPs) face the challenge of anchor chain failures due to their unique operating environments. This directly impacts the platform’s safety and stability. Traditional control methods are often ineffective in addressing anchor chain failures. Therefore, this study proposes a novel event-triggered, self-tuning integrated PID control strategy based on finite-time learning to improve the stability and fault handling capabilities of FOP systems. This study introduces a preset finite-time convergence function based on a time-based generator (TBG) in the control design, combined with a nonlinear error-driven mechanism to achieve finite-time convergence. By integrating a composite variable construction method with neural network approximation techniques, a state mapping mechanism adaptable to mixed uncertainties is established. Furthermore, this study designs a control system that integrates an event-triggered dynamic mechanism with a finite-time convergence paradigm. Through strategic parameter scheduling, this control strategy achieves coordinated optimal configuration and extreme performance optimization under multiple performance metrics in an offline phase. A rigorous stability analysis of the designed control strategy using Lyapunov stability theory demonstrates its effectiveness in terms of asymptotic stability and finite-time convergence. Simulations are conducted on a real FOP system. Results demonstrate that the control strategy effectively addresses anchor chain failures and internal and external uncertain dynamics.</p></div>2025-11-24T18:33:03ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0337290.g006https://figshare.com/articles/figure/Evolution_of_tracking_error_over_time_/30697511CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/306975112025-11-24T18:33:03Z |
| spellingShingle | Evolution of tracking error over time. Chengliang Chao (22676651) Biophysics Biotechnology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified unique operating environments strategic parameter scheduling platform &# 8217 multiple performance metrics extreme performance optimization traditional control methods rigorous stability analysis real fop system fault handling capabilities edf dual finite triggered dynamic mechanism time convergence paradigm control system time convergence fop systems driven mechanism control design tolerant strategy time learning study proposes study introduces study designs results demonstrate preset finite often ineffective offline phase nonlinear error mixed uncertainties directly impacts based generator asymptotic stability achieve finite |
| status_str | publishedVersion |
| title | Evolution of tracking error over time. |
| title_full | Evolution of tracking error over time. |
| title_fullStr | Evolution of tracking error over time. |
| title_full_unstemmed | Evolution of tracking error over time. |
| title_short | Evolution of tracking error over time. |
| title_sort | Evolution of tracking error over time. |
| topic | Biophysics Biotechnology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified unique operating environments strategic parameter scheduling platform &# 8217 multiple performance metrics extreme performance optimization traditional control methods rigorous stability analysis real fop system fault handling capabilities edf dual finite triggered dynamic mechanism time convergence paradigm control system time convergence fop systems driven mechanism control design tolerant strategy time learning study proposes study introduces study designs results demonstrate preset finite often ineffective offline phase nonlinear error mixed uncertainties directly impacts based generator asymptotic stability achieve finite |