Real-world engineering problems: Two surrogate methods for robust vibration control of moving mass-beam coupling systems with epistemic uncertainty

The dynamic responses and the vibration control of the moving mass-beam coupling systems are one of the real-world problems in engineering fields including vehicle-bridge coupling systems and missile-gun systems. There are many uncertainty factors in the real-world engineering applications. Analyzin...
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Autor*in:	Liu, Xiao-Xiao [verfasserIn] Xie, Qi-Zhi [verfasserIn] Du, Rui-Jie [verfasserIn] Zhang, Feng [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Robust control Evidence theory Kriging Lobatto polynomial Beam systems

Übergeordnetes Werk:	Enthalten in: Aerospace science and technology - Amsterdam [u.a.] : Elsevier Science, 1997, 130
Übergeordnetes Werk:	volume:130

DOI / URN:	10.1016/j.ast.2022.107916

Katalog-ID:	ELV008739749

Internformat


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245	1	0	\|a Real-world engineering problems: Two surrogate methods for robust vibration control of moving mass-beam coupling systems with epistemic uncertainty
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520			\|a The dynamic responses and the vibration control of the moving mass-beam coupling systems are one of the real-world problems in engineering fields including vehicle-bridge coupling systems and missile-gun systems. There are many uncertainty factors in the real-world engineering applications. Analyzing the effects of uncertainty on the state trajectory of the system is significant to realize the safe operation of the system. This paper develops two surrogate methods to research the evidence-theory-based robust adaptive fuzzy sliding mode control (ET-RAFSMC) of the moving mass-beam coupling systems. For the first approach, the active learning Kriging (ALK) is combined with the ET-RAFSMC to perform the evidence response analysis through an interval Monte Carlo simulation, and then a Karush-Kuhn-Tucker condition is utilized to alleviate the burden of searching the extreme responses. The other surrogate method is the Lobatto polynomial function, which integrates with a spare sampling method for improving the computational efficiency and accuracy when running the extreme value analysis of the ET-RAFSMC. The accuracy and the efficiency of the proposed methods are studied by comparing with Monte Carlo simulations as well as Legendre expansion model. Finally, the performance of the ET-RAFSMC is studied through comparing with the traditional sliding mode control.
650		4	\|a Robust control
650		4	\|a Evidence theory
650		4	\|a Kriging
650		4	\|a Lobatto polynomial
650		4	\|a Beam systems
700	1		\|a Xie, Qi-Zhi \|e verfasserin \|4 aut
700	1		\|a Du, Rui-Jie \|e verfasserin \|4 aut
700	1		\|a Zhang, Feng \|e verfasserin \|0 (orcid)0000-0003-2987-8418 \|4 aut
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912			\|a GBV_ILN_74
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912			\|a GBV_ILN_105
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912			\|a GBV_ILN_151
912			\|a GBV_ILN_224
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_702
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936	b	k	\|a 55.60 \|j Raumfahrttechnik
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952			\|d 130

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author_variant	x x l xxl q z x qzx r j d rjd f z fz
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publishDate	2022
allfields	10.1016/j.ast.2022.107916 doi (DE-627)ELV008739749 (ELSEVIER)S1270-9638(22)00590-9 DE-627 ger DE-627 rda eng 620 DE-600 55.50 bkl 55.60 bkl 55.60 bkl Liu, Xiao-Xiao verfasserin aut Real-world engineering problems: Two surrogate methods for robust vibration control of moving mass-beam coupling systems with epistemic uncertainty 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The dynamic responses and the vibration control of the moving mass-beam coupling systems are one of the real-world problems in engineering fields including vehicle-bridge coupling systems and missile-gun systems. There are many uncertainty factors in the real-world engineering applications. Analyzing the effects of uncertainty on the state trajectory of the system is significant to realize the safe operation of the system. This paper develops two surrogate methods to research the evidence-theory-based robust adaptive fuzzy sliding mode control (ET-RAFSMC) of the moving mass-beam coupling systems. For the first approach, the active learning Kriging (ALK) is combined with the ET-RAFSMC to perform the evidence response analysis through an interval Monte Carlo simulation, and then a Karush-Kuhn-Tucker condition is utilized to alleviate the burden of searching the extreme responses. The other surrogate method is the Lobatto polynomial function, which integrates with a spare sampling method for improving the computational efficiency and accuracy when running the extreme value analysis of the ET-RAFSMC. The accuracy and the efficiency of the proposed methods are studied by comparing with Monte Carlo simulations as well as Legendre expansion model. Finally, the performance of the ET-RAFSMC is studied through comparing with the traditional sliding mode control. Robust control Evidence theory Kriging Lobatto polynomial Beam systems Xie, Qi-Zhi verfasserin aut Du, Rui-Jie verfasserin aut Zhang, Feng verfasserin (orcid)0000-0003-2987-8418 aut Enthalten in Aerospace science and technology Amsterdam [u.a.] : Elsevier Science, 1997 130 Online-Ressource (DE-627)320521486 (DE-600)2014638-3 (DE-576)255630425 1626-3219 nnns volume:130 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-AST GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 55.50 Luftfahrzeugtechnik 55.60 Raumfahrttechnik 55.60 Raumfahrttechnik AR 130
spelling	10.1016/j.ast.2022.107916 doi (DE-627)ELV008739749 (ELSEVIER)S1270-9638(22)00590-9 DE-627 ger DE-627 rda eng 620 DE-600 55.50 bkl 55.60 bkl 55.60 bkl Liu, Xiao-Xiao verfasserin aut Real-world engineering problems: Two surrogate methods for robust vibration control of moving mass-beam coupling systems with epistemic uncertainty 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The dynamic responses and the vibration control of the moving mass-beam coupling systems are one of the real-world problems in engineering fields including vehicle-bridge coupling systems and missile-gun systems. There are many uncertainty factors in the real-world engineering applications. Analyzing the effects of uncertainty on the state trajectory of the system is significant to realize the safe operation of the system. This paper develops two surrogate methods to research the evidence-theory-based robust adaptive fuzzy sliding mode control (ET-RAFSMC) of the moving mass-beam coupling systems. For the first approach, the active learning Kriging (ALK) is combined with the ET-RAFSMC to perform the evidence response analysis through an interval Monte Carlo simulation, and then a Karush-Kuhn-Tucker condition is utilized to alleviate the burden of searching the extreme responses. The other surrogate method is the Lobatto polynomial function, which integrates with a spare sampling method for improving the computational efficiency and accuracy when running the extreme value analysis of the ET-RAFSMC. The accuracy and the efficiency of the proposed methods are studied by comparing with Monte Carlo simulations as well as Legendre expansion model. Finally, the performance of the ET-RAFSMC is studied through comparing with the traditional sliding mode control. Robust control Evidence theory Kriging Lobatto polynomial Beam systems Xie, Qi-Zhi verfasserin aut Du, Rui-Jie verfasserin aut Zhang, Feng verfasserin (orcid)0000-0003-2987-8418 aut Enthalten in Aerospace science and technology Amsterdam [u.a.] : Elsevier Science, 1997 130 Online-Ressource (DE-627)320521486 (DE-600)2014638-3 (DE-576)255630425 1626-3219 nnns volume:130 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-AST GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 55.50 Luftfahrzeugtechnik 55.60 Raumfahrttechnik 55.60 Raumfahrttechnik AR 130
allfields_unstemmed	10.1016/j.ast.2022.107916 doi (DE-627)ELV008739749 (ELSEVIER)S1270-9638(22)00590-9 DE-627 ger DE-627 rda eng 620 DE-600 55.50 bkl 55.60 bkl 55.60 bkl Liu, Xiao-Xiao verfasserin aut Real-world engineering problems: Two surrogate methods for robust vibration control of moving mass-beam coupling systems with epistemic uncertainty 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The dynamic responses and the vibration control of the moving mass-beam coupling systems are one of the real-world problems in engineering fields including vehicle-bridge coupling systems and missile-gun systems. There are many uncertainty factors in the real-world engineering applications. Analyzing the effects of uncertainty on the state trajectory of the system is significant to realize the safe operation of the system. This paper develops two surrogate methods to research the evidence-theory-based robust adaptive fuzzy sliding mode control (ET-RAFSMC) of the moving mass-beam coupling systems. For the first approach, the active learning Kriging (ALK) is combined with the ET-RAFSMC to perform the evidence response analysis through an interval Monte Carlo simulation, and then a Karush-Kuhn-Tucker condition is utilized to alleviate the burden of searching the extreme responses. The other surrogate method is the Lobatto polynomial function, which integrates with a spare sampling method for improving the computational efficiency and accuracy when running the extreme value analysis of the ET-RAFSMC. The accuracy and the efficiency of the proposed methods are studied by comparing with Monte Carlo simulations as well as Legendre expansion model. Finally, the performance of the ET-RAFSMC is studied through comparing with the traditional sliding mode control. Robust control Evidence theory Kriging Lobatto polynomial Beam systems Xie, Qi-Zhi verfasserin aut Du, Rui-Jie verfasserin aut Zhang, Feng verfasserin (orcid)0000-0003-2987-8418 aut Enthalten in Aerospace science and technology Amsterdam [u.a.] : Elsevier Science, 1997 130 Online-Ressource (DE-627)320521486 (DE-600)2014638-3 (DE-576)255630425 1626-3219 nnns volume:130 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-AST GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 55.50 Luftfahrzeugtechnik 55.60 Raumfahrttechnik 55.60 Raumfahrttechnik AR 130
allfieldsGer	10.1016/j.ast.2022.107916 doi (DE-627)ELV008739749 (ELSEVIER)S1270-9638(22)00590-9 DE-627 ger DE-627 rda eng 620 DE-600 55.50 bkl 55.60 bkl 55.60 bkl Liu, Xiao-Xiao verfasserin aut Real-world engineering problems: Two surrogate methods for robust vibration control of moving mass-beam coupling systems with epistemic uncertainty 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The dynamic responses and the vibration control of the moving mass-beam coupling systems are one of the real-world problems in engineering fields including vehicle-bridge coupling systems and missile-gun systems. There are many uncertainty factors in the real-world engineering applications. Analyzing the effects of uncertainty on the state trajectory of the system is significant to realize the safe operation of the system. This paper develops two surrogate methods to research the evidence-theory-based robust adaptive fuzzy sliding mode control (ET-RAFSMC) of the moving mass-beam coupling systems. For the first approach, the active learning Kriging (ALK) is combined with the ET-RAFSMC to perform the evidence response analysis through an interval Monte Carlo simulation, and then a Karush-Kuhn-Tucker condition is utilized to alleviate the burden of searching the extreme responses. The other surrogate method is the Lobatto polynomial function, which integrates with a spare sampling method for improving the computational efficiency and accuracy when running the extreme value analysis of the ET-RAFSMC. The accuracy and the efficiency of the proposed methods are studied by comparing with Monte Carlo simulations as well as Legendre expansion model. Finally, the performance of the ET-RAFSMC is studied through comparing with the traditional sliding mode control. Robust control Evidence theory Kriging Lobatto polynomial Beam systems Xie, Qi-Zhi verfasserin aut Du, Rui-Jie verfasserin aut Zhang, Feng verfasserin (orcid)0000-0003-2987-8418 aut Enthalten in Aerospace science and technology Amsterdam [u.a.] : Elsevier Science, 1997 130 Online-Ressource (DE-627)320521486 (DE-600)2014638-3 (DE-576)255630425 1626-3219 nnns volume:130 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-AST GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 55.50 Luftfahrzeugtechnik 55.60 Raumfahrttechnik 55.60 Raumfahrttechnik AR 130
allfieldsSound	10.1016/j.ast.2022.107916 doi (DE-627)ELV008739749 (ELSEVIER)S1270-9638(22)00590-9 DE-627 ger DE-627 rda eng 620 DE-600 55.50 bkl 55.60 bkl 55.60 bkl Liu, Xiao-Xiao verfasserin aut Real-world engineering problems: Two surrogate methods for robust vibration control of moving mass-beam coupling systems with epistemic uncertainty 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The dynamic responses and the vibration control of the moving mass-beam coupling systems are one of the real-world problems in engineering fields including vehicle-bridge coupling systems and missile-gun systems. There are many uncertainty factors in the real-world engineering applications. Analyzing the effects of uncertainty on the state trajectory of the system is significant to realize the safe operation of the system. This paper develops two surrogate methods to research the evidence-theory-based robust adaptive fuzzy sliding mode control (ET-RAFSMC) of the moving mass-beam coupling systems. For the first approach, the active learning Kriging (ALK) is combined with the ET-RAFSMC to perform the evidence response analysis through an interval Monte Carlo simulation, and then a Karush-Kuhn-Tucker condition is utilized to alleviate the burden of searching the extreme responses. The other surrogate method is the Lobatto polynomial function, which integrates with a spare sampling method for improving the computational efficiency and accuracy when running the extreme value analysis of the ET-RAFSMC. The accuracy and the efficiency of the proposed methods are studied by comparing with Monte Carlo simulations as well as Legendre expansion model. Finally, the performance of the ET-RAFSMC is studied through comparing with the traditional sliding mode control. Robust control Evidence theory Kriging Lobatto polynomial Beam systems Xie, Qi-Zhi verfasserin aut Du, Rui-Jie verfasserin aut Zhang, Feng verfasserin (orcid)0000-0003-2987-8418 aut Enthalten in Aerospace science and technology Amsterdam [u.a.] : Elsevier Science, 1997 130 Online-Ressource (DE-627)320521486 (DE-600)2014638-3 (DE-576)255630425 1626-3219 nnns volume:130 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-AST GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 55.50 Luftfahrzeugtechnik 55.60 Raumfahrttechnik 55.60 Raumfahrttechnik AR 130
language	English
source	Enthalten in Aerospace science and technology 130 volume:130
sourceStr	Enthalten in Aerospace science and technology 130 volume:130
format_phy_str_mv	Article
bklname	Luftfahrzeugtechnik Raumfahrttechnik
institution	findex.gbv.de
topic_facet	Robust control Evidence theory Kriging Lobatto polynomial Beam systems
dewey-raw	620
isfreeaccess_bool	false
container_title	Aerospace science and technology
authorswithroles_txt_mv	Liu, Xiao-Xiao @@aut@@ Xie, Qi-Zhi @@aut@@ Du, Rui-Jie @@aut@@ Zhang, Feng @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	320521486
dewey-sort	3620
id	ELV008739749
language_de	englisch
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author	Liu, Xiao-Xiao
spellingShingle	Liu, Xiao-Xiao ddc 620 bkl 55.50 bkl 55.60 misc Robust control misc Evidence theory misc Kriging misc Lobatto polynomial misc Beam systems Real-world engineering problems: Two surrogate methods for robust vibration control of moving mass-beam coupling systems with epistemic uncertainty
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topic_title	620 DE-600 55.50 bkl 55.60 bkl Real-world engineering problems: Two surrogate methods for robust vibration control of moving mass-beam coupling systems with epistemic uncertainty Robust control Evidence theory Kriging Lobatto polynomial Beam systems
topic	ddc 620 bkl 55.50 bkl 55.60 misc Robust control misc Evidence theory misc Kriging misc Lobatto polynomial misc Beam systems
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title	Real-world engineering problems: Two surrogate methods for robust vibration control of moving mass-beam coupling systems with epistemic uncertainty
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title_full	Real-world engineering problems: Two surrogate methods for robust vibration control of moving mass-beam coupling systems with epistemic uncertainty
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title_sort	real-world engineering problems: two surrogate methods for robust vibration control of moving mass-beam coupling systems with epistemic uncertainty
title_auth	Real-world engineering problems: Two surrogate methods for robust vibration control of moving mass-beam coupling systems with epistemic uncertainty
abstract	The dynamic responses and the vibration control of the moving mass-beam coupling systems are one of the real-world problems in engineering fields including vehicle-bridge coupling systems and missile-gun systems. There are many uncertainty factors in the real-world engineering applications. Analyzing the effects of uncertainty on the state trajectory of the system is significant to realize the safe operation of the system. This paper develops two surrogate methods to research the evidence-theory-based robust adaptive fuzzy sliding mode control (ET-RAFSMC) of the moving mass-beam coupling systems. For the first approach, the active learning Kriging (ALK) is combined with the ET-RAFSMC to perform the evidence response analysis through an interval Monte Carlo simulation, and then a Karush-Kuhn-Tucker condition is utilized to alleviate the burden of searching the extreme responses. The other surrogate method is the Lobatto polynomial function, which integrates with a spare sampling method for improving the computational efficiency and accuracy when running the extreme value analysis of the ET-RAFSMC. The accuracy and the efficiency of the proposed methods are studied by comparing with Monte Carlo simulations as well as Legendre expansion model. Finally, the performance of the ET-RAFSMC is studied through comparing with the traditional sliding mode control.
abstractGer	The dynamic responses and the vibration control of the moving mass-beam coupling systems are one of the real-world problems in engineering fields including vehicle-bridge coupling systems and missile-gun systems. There are many uncertainty factors in the real-world engineering applications. Analyzing the effects of uncertainty on the state trajectory of the system is significant to realize the safe operation of the system. This paper develops two surrogate methods to research the evidence-theory-based robust adaptive fuzzy sliding mode control (ET-RAFSMC) of the moving mass-beam coupling systems. For the first approach, the active learning Kriging (ALK) is combined with the ET-RAFSMC to perform the evidence response analysis through an interval Monte Carlo simulation, and then a Karush-Kuhn-Tucker condition is utilized to alleviate the burden of searching the extreme responses. The other surrogate method is the Lobatto polynomial function, which integrates with a spare sampling method for improving the computational efficiency and accuracy when running the extreme value analysis of the ET-RAFSMC. The accuracy and the efficiency of the proposed methods are studied by comparing with Monte Carlo simulations as well as Legendre expansion model. Finally, the performance of the ET-RAFSMC is studied through comparing with the traditional sliding mode control.
abstract_unstemmed	The dynamic responses and the vibration control of the moving mass-beam coupling systems are one of the real-world problems in engineering fields including vehicle-bridge coupling systems and missile-gun systems. There are many uncertainty factors in the real-world engineering applications. Analyzing the effects of uncertainty on the state trajectory of the system is significant to realize the safe operation of the system. This paper develops two surrogate methods to research the evidence-theory-based robust adaptive fuzzy sliding mode control (ET-RAFSMC) of the moving mass-beam coupling systems. For the first approach, the active learning Kriging (ALK) is combined with the ET-RAFSMC to perform the evidence response analysis through an interval Monte Carlo simulation, and then a Karush-Kuhn-Tucker condition is utilized to alleviate the burden of searching the extreme responses. The other surrogate method is the Lobatto polynomial function, which integrates with a spare sampling method for improving the computational efficiency and accuracy when running the extreme value analysis of the ET-RAFSMC. The accuracy and the efficiency of the proposed methods are studied by comparing with Monte Carlo simulations as well as Legendre expansion model. Finally, the performance of the ET-RAFSMC is studied through comparing with the traditional sliding mode control.
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title_short	Real-world engineering problems: Two surrogate methods for robust vibration control of moving mass-beam coupling systems with epistemic uncertainty
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author2	Xie, Qi-Zhi Du, Rui-Jie Zhang, Feng
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doi_str	10.1016/j.ast.2022.107916
up_date	2024-07-06T20:44:31.198Z
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Real-world engineering problems: Two surrogate methods for robust vibration control of moving mass-beam coupling systems with epistemic uncertainty

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