Optimizing compliant gripper mechanism design by employing an effective bi-algorithm: fuzzy logic and ANFIS

Abstract This investigation confronts the note-worthy improvement configuration gap in which such a design method could be better focused on the multi-objective optimization design of a compliant gripper mechanism as a robot arm through an effective hybrid algorithm of fuzzy logic and adaptive neuro...
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Autor*in:	Nguyen, Tien V. T. [verfasserIn] Huynh, Ngoc-Thai [verfasserIn] Vu, Ngoc-Chien [verfasserIn] Kieu, Vu N. D. [verfasserIn] Huang, Shyh-Chour [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Anmerkung:	© Springer-Verlag GmbH Germany, part of Springer Nature 2021

Übergeordnetes Werk:	Enthalten in: Microsystem technologies - Berlin : Springer, 1994, 27(2021), 9 vom: 02. Jan., Seite 3389-3412
Übergeordnetes Werk:	volume:27 ; year:2021 ; number:9 ; day:02 ; month:01 ; pages:3389-3412

Links:	Volltext

DOI / URN:	10.1007/s00542-020-05132-w

Katalog-ID:	SPR044664125

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allfields	10.1007/s00542-020-05132-w doi (DE-627)SPR044664125 (SPR)s00542-020-05132-w-e DE-627 ger DE-627 rakwb eng 510 ASE 50.94 bkl Nguyen, Tien V. T. verfasserin aut Optimizing compliant gripper mechanism design by employing an effective bi-algorithm: fuzzy logic and ANFIS 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract This investigation confronts the note-worthy improvement configuration gap in which such a design method could be better focused on the multi-objective optimization design of a compliant gripper mechanism as a robot arm through an effective hybrid algorithm of fuzzy logic and adaptive neuro-fuzzy inference system (ANFIS). We found that the proposed bi-algorithm approach is more compelling than theoretical ideas like auxiliary shape changes, materials, and directors of mechanisms when designing the compliant gripper mechanism with a set of novel multi-objective optimization design recently. In particular, it explores whether the compliant gripper mechanism shapes affect picking things up. In this unique study, we considered displacement values and the frequency values as response parameters during the simulation and the optimization design process. To test the effectiveness of the optimal design method, we proposed an initial compliant gripper mechanism carried out through the numerically experimental matrix—the Box–Behnken design. After that, we simulated the numerical model by utilizing the finite element method incorporating the approaches of desirability function, fuzzy logic system, and ANFIS. The results turn larger than those of the previous approaches. Moreover, numerical results reveal that the suggested hybrid method has a computational exactness more conspicuous than that of the Taguchi method. In short, the principle accomplishments with variables to the compliant gripper mechanism optimization design can be summarized up as follows: (i) the promising and potential proposed approach could meet the clients’ prerequisite, (ii) the idea of multi-objective optimization design ought to be re-considered when designing compliant gripper mechanism as well as applying related designing fields at the diminished expenses and the shortage time. Huynh, Ngoc-Thai verfasserin aut Vu, Ngoc-Chien verfasserin aut Kieu, Vu N. D. verfasserin aut Huang, Shyh-Chour verfasserin aut Enthalten in Microsystem technologies Berlin : Springer, 1994 27(2021), 9 vom: 02. Jan., Seite 3389-3412 (DE-627)270128182 (DE-600)1476561-5 1432-1858 nnns volume:27 year:2021 number:9 day:02 month:01 pages:3389-3412 https://dx.doi.org/10.1007/s00542-020-05132-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.94 ASE AR 27 2021 9 02 01 3389-3412
spelling	10.1007/s00542-020-05132-w doi (DE-627)SPR044664125 (SPR)s00542-020-05132-w-e DE-627 ger DE-627 rakwb eng 510 ASE 50.94 bkl Nguyen, Tien V. T. verfasserin aut Optimizing compliant gripper mechanism design by employing an effective bi-algorithm: fuzzy logic and ANFIS 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract This investigation confronts the note-worthy improvement configuration gap in which such a design method could be better focused on the multi-objective optimization design of a compliant gripper mechanism as a robot arm through an effective hybrid algorithm of fuzzy logic and adaptive neuro-fuzzy inference system (ANFIS). We found that the proposed bi-algorithm approach is more compelling than theoretical ideas like auxiliary shape changes, materials, and directors of mechanisms when designing the compliant gripper mechanism with a set of novel multi-objective optimization design recently. In particular, it explores whether the compliant gripper mechanism shapes affect picking things up. In this unique study, we considered displacement values and the frequency values as response parameters during the simulation and the optimization design process. To test the effectiveness of the optimal design method, we proposed an initial compliant gripper mechanism carried out through the numerically experimental matrix—the Box–Behnken design. After that, we simulated the numerical model by utilizing the finite element method incorporating the approaches of desirability function, fuzzy logic system, and ANFIS. The results turn larger than those of the previous approaches. Moreover, numerical results reveal that the suggested hybrid method has a computational exactness more conspicuous than that of the Taguchi method. In short, the principle accomplishments with variables to the compliant gripper mechanism optimization design can be summarized up as follows: (i) the promising and potential proposed approach could meet the clients’ prerequisite, (ii) the idea of multi-objective optimization design ought to be re-considered when designing compliant gripper mechanism as well as applying related designing fields at the diminished expenses and the shortage time. Huynh, Ngoc-Thai verfasserin aut Vu, Ngoc-Chien verfasserin aut Kieu, Vu N. D. verfasserin aut Huang, Shyh-Chour verfasserin aut Enthalten in Microsystem technologies Berlin : Springer, 1994 27(2021), 9 vom: 02. Jan., Seite 3389-3412 (DE-627)270128182 (DE-600)1476561-5 1432-1858 nnns volume:27 year:2021 number:9 day:02 month:01 pages:3389-3412 https://dx.doi.org/10.1007/s00542-020-05132-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.94 ASE AR 27 2021 9 02 01 3389-3412
allfields_unstemmed	10.1007/s00542-020-05132-w doi (DE-627)SPR044664125 (SPR)s00542-020-05132-w-e DE-627 ger DE-627 rakwb eng 510 ASE 50.94 bkl Nguyen, Tien V. T. verfasserin aut Optimizing compliant gripper mechanism design by employing an effective bi-algorithm: fuzzy logic and ANFIS 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract This investigation confronts the note-worthy improvement configuration gap in which such a design method could be better focused on the multi-objective optimization design of a compliant gripper mechanism as a robot arm through an effective hybrid algorithm of fuzzy logic and adaptive neuro-fuzzy inference system (ANFIS). We found that the proposed bi-algorithm approach is more compelling than theoretical ideas like auxiliary shape changes, materials, and directors of mechanisms when designing the compliant gripper mechanism with a set of novel multi-objective optimization design recently. In particular, it explores whether the compliant gripper mechanism shapes affect picking things up. In this unique study, we considered displacement values and the frequency values as response parameters during the simulation and the optimization design process. To test the effectiveness of the optimal design method, we proposed an initial compliant gripper mechanism carried out through the numerically experimental matrix—the Box–Behnken design. After that, we simulated the numerical model by utilizing the finite element method incorporating the approaches of desirability function, fuzzy logic system, and ANFIS. The results turn larger than those of the previous approaches. Moreover, numerical results reveal that the suggested hybrid method has a computational exactness more conspicuous than that of the Taguchi method. In short, the principle accomplishments with variables to the compliant gripper mechanism optimization design can be summarized up as follows: (i) the promising and potential proposed approach could meet the clients’ prerequisite, (ii) the idea of multi-objective optimization design ought to be re-considered when designing compliant gripper mechanism as well as applying related designing fields at the diminished expenses and the shortage time. Huynh, Ngoc-Thai verfasserin aut Vu, Ngoc-Chien verfasserin aut Kieu, Vu N. D. verfasserin aut Huang, Shyh-Chour verfasserin aut Enthalten in Microsystem technologies Berlin : Springer, 1994 27(2021), 9 vom: 02. Jan., Seite 3389-3412 (DE-627)270128182 (DE-600)1476561-5 1432-1858 nnns volume:27 year:2021 number:9 day:02 month:01 pages:3389-3412 https://dx.doi.org/10.1007/s00542-020-05132-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.94 ASE AR 27 2021 9 02 01 3389-3412
allfieldsGer	10.1007/s00542-020-05132-w doi (DE-627)SPR044664125 (SPR)s00542-020-05132-w-e DE-627 ger DE-627 rakwb eng 510 ASE 50.94 bkl Nguyen, Tien V. T. verfasserin aut Optimizing compliant gripper mechanism design by employing an effective bi-algorithm: fuzzy logic and ANFIS 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract This investigation confronts the note-worthy improvement configuration gap in which such a design method could be better focused on the multi-objective optimization design of a compliant gripper mechanism as a robot arm through an effective hybrid algorithm of fuzzy logic and adaptive neuro-fuzzy inference system (ANFIS). We found that the proposed bi-algorithm approach is more compelling than theoretical ideas like auxiliary shape changes, materials, and directors of mechanisms when designing the compliant gripper mechanism with a set of novel multi-objective optimization design recently. In particular, it explores whether the compliant gripper mechanism shapes affect picking things up. In this unique study, we considered displacement values and the frequency values as response parameters during the simulation and the optimization design process. To test the effectiveness of the optimal design method, we proposed an initial compliant gripper mechanism carried out through the numerically experimental matrix—the Box–Behnken design. After that, we simulated the numerical model by utilizing the finite element method incorporating the approaches of desirability function, fuzzy logic system, and ANFIS. The results turn larger than those of the previous approaches. Moreover, numerical results reveal that the suggested hybrid method has a computational exactness more conspicuous than that of the Taguchi method. In short, the principle accomplishments with variables to the compliant gripper mechanism optimization design can be summarized up as follows: (i) the promising and potential proposed approach could meet the clients’ prerequisite, (ii) the idea of multi-objective optimization design ought to be re-considered when designing compliant gripper mechanism as well as applying related designing fields at the diminished expenses and the shortage time. Huynh, Ngoc-Thai verfasserin aut Vu, Ngoc-Chien verfasserin aut Kieu, Vu N. D. verfasserin aut Huang, Shyh-Chour verfasserin aut Enthalten in Microsystem technologies Berlin : Springer, 1994 27(2021), 9 vom: 02. Jan., Seite 3389-3412 (DE-627)270128182 (DE-600)1476561-5 1432-1858 nnns volume:27 year:2021 number:9 day:02 month:01 pages:3389-3412 https://dx.doi.org/10.1007/s00542-020-05132-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.94 ASE AR 27 2021 9 02 01 3389-3412
allfieldsSound	10.1007/s00542-020-05132-w doi (DE-627)SPR044664125 (SPR)s00542-020-05132-w-e DE-627 ger DE-627 rakwb eng 510 ASE 50.94 bkl Nguyen, Tien V. T. verfasserin aut Optimizing compliant gripper mechanism design by employing an effective bi-algorithm: fuzzy logic and ANFIS 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract This investigation confronts the note-worthy improvement configuration gap in which such a design method could be better focused on the multi-objective optimization design of a compliant gripper mechanism as a robot arm through an effective hybrid algorithm of fuzzy logic and adaptive neuro-fuzzy inference system (ANFIS). We found that the proposed bi-algorithm approach is more compelling than theoretical ideas like auxiliary shape changes, materials, and directors of mechanisms when designing the compliant gripper mechanism with a set of novel multi-objective optimization design recently. In particular, it explores whether the compliant gripper mechanism shapes affect picking things up. In this unique study, we considered displacement values and the frequency values as response parameters during the simulation and the optimization design process. To test the effectiveness of the optimal design method, we proposed an initial compliant gripper mechanism carried out through the numerically experimental matrix—the Box–Behnken design. After that, we simulated the numerical model by utilizing the finite element method incorporating the approaches of desirability function, fuzzy logic system, and ANFIS. The results turn larger than those of the previous approaches. Moreover, numerical results reveal that the suggested hybrid method has a computational exactness more conspicuous than that of the Taguchi method. In short, the principle accomplishments with variables to the compliant gripper mechanism optimization design can be summarized up as follows: (i) the promising and potential proposed approach could meet the clients’ prerequisite, (ii) the idea of multi-objective optimization design ought to be re-considered when designing compliant gripper mechanism as well as applying related designing fields at the diminished expenses and the shortage time. Huynh, Ngoc-Thai verfasserin aut Vu, Ngoc-Chien verfasserin aut Kieu, Vu N. D. verfasserin aut Huang, Shyh-Chour verfasserin aut Enthalten in Microsystem technologies Berlin : Springer, 1994 27(2021), 9 vom: 02. Jan., Seite 3389-3412 (DE-627)270128182 (DE-600)1476561-5 1432-1858 nnns volume:27 year:2021 number:9 day:02 month:01 pages:3389-3412 https://dx.doi.org/10.1007/s00542-020-05132-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.94 ASE AR 27 2021 9 02 01 3389-3412
language	English
source	Enthalten in Microsystem technologies 27(2021), 9 vom: 02. Jan., Seite 3389-3412 volume:27 year:2021 number:9 day:02 month:01 pages:3389-3412
sourceStr	Enthalten in Microsystem technologies 27(2021), 9 vom: 02. Jan., Seite 3389-3412 volume:27 year:2021 number:9 day:02 month:01 pages:3389-3412
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container_title	Microsystem technologies
authorswithroles_txt_mv	Nguyen, Tien V. T. @@aut@@ Huynh, Ngoc-Thai @@aut@@ Vu, Ngoc-Chien @@aut@@ Kieu, Vu N. D. @@aut@@ Huang, Shyh-Chour @@aut@@
publishDateDaySort_date	2021-01-02T00:00:00Z
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author	Nguyen, Tien V. T.
spellingShingle	Nguyen, Tien V. T. ddc 510 bkl 50.94 Optimizing compliant gripper mechanism design by employing an effective bi-algorithm: fuzzy logic and ANFIS
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topic_title	510 ASE 50.94 bkl Optimizing compliant gripper mechanism design by employing an effective bi-algorithm: fuzzy logic and ANFIS
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title	Optimizing compliant gripper mechanism design by employing an effective bi-algorithm: fuzzy logic and ANFIS
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title_full	Optimizing compliant gripper mechanism design by employing an effective bi-algorithm: fuzzy logic and ANFIS
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author_browse	Nguyen, Tien V. T. Huynh, Ngoc-Thai Vu, Ngoc-Chien Kieu, Vu N. D. Huang, Shyh-Chour
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title_sort	optimizing compliant gripper mechanism design by employing an effective bi-algorithm: fuzzy logic and anfis
title_auth	Optimizing compliant gripper mechanism design by employing an effective bi-algorithm: fuzzy logic and ANFIS
abstract	Abstract This investigation confronts the note-worthy improvement configuration gap in which such a design method could be better focused on the multi-objective optimization design of a compliant gripper mechanism as a robot arm through an effective hybrid algorithm of fuzzy logic and adaptive neuro-fuzzy inference system (ANFIS). We found that the proposed bi-algorithm approach is more compelling than theoretical ideas like auxiliary shape changes, materials, and directors of mechanisms when designing the compliant gripper mechanism with a set of novel multi-objective optimization design recently. In particular, it explores whether the compliant gripper mechanism shapes affect picking things up. In this unique study, we considered displacement values and the frequency values as response parameters during the simulation and the optimization design process. To test the effectiveness of the optimal design method, we proposed an initial compliant gripper mechanism carried out through the numerically experimental matrix—the Box–Behnken design. After that, we simulated the numerical model by utilizing the finite element method incorporating the approaches of desirability function, fuzzy logic system, and ANFIS. The results turn larger than those of the previous approaches. Moreover, numerical results reveal that the suggested hybrid method has a computational exactness more conspicuous than that of the Taguchi method. In short, the principle accomplishments with variables to the compliant gripper mechanism optimization design can be summarized up as follows: (i) the promising and potential proposed approach could meet the clients’ prerequisite, (ii) the idea of multi-objective optimization design ought to be re-considered when designing compliant gripper mechanism as well as applying related designing fields at the diminished expenses and the shortage time. © Springer-Verlag GmbH Germany, part of Springer Nature 2021
abstractGer	Abstract This investigation confronts the note-worthy improvement configuration gap in which such a design method could be better focused on the multi-objective optimization design of a compliant gripper mechanism as a robot arm through an effective hybrid algorithm of fuzzy logic and adaptive neuro-fuzzy inference system (ANFIS). We found that the proposed bi-algorithm approach is more compelling than theoretical ideas like auxiliary shape changes, materials, and directors of mechanisms when designing the compliant gripper mechanism with a set of novel multi-objective optimization design recently. In particular, it explores whether the compliant gripper mechanism shapes affect picking things up. In this unique study, we considered displacement values and the frequency values as response parameters during the simulation and the optimization design process. To test the effectiveness of the optimal design method, we proposed an initial compliant gripper mechanism carried out through the numerically experimental matrix—the Box–Behnken design. After that, we simulated the numerical model by utilizing the finite element method incorporating the approaches of desirability function, fuzzy logic system, and ANFIS. The results turn larger than those of the previous approaches. Moreover, numerical results reveal that the suggested hybrid method has a computational exactness more conspicuous than that of the Taguchi method. In short, the principle accomplishments with variables to the compliant gripper mechanism optimization design can be summarized up as follows: (i) the promising and potential proposed approach could meet the clients’ prerequisite, (ii) the idea of multi-objective optimization design ought to be re-considered when designing compliant gripper mechanism as well as applying related designing fields at the diminished expenses and the shortage time. © Springer-Verlag GmbH Germany, part of Springer Nature 2021
abstract_unstemmed	Abstract This investigation confronts the note-worthy improvement configuration gap in which such a design method could be better focused on the multi-objective optimization design of a compliant gripper mechanism as a robot arm through an effective hybrid algorithm of fuzzy logic and adaptive neuro-fuzzy inference system (ANFIS). We found that the proposed bi-algorithm approach is more compelling than theoretical ideas like auxiliary shape changes, materials, and directors of mechanisms when designing the compliant gripper mechanism with a set of novel multi-objective optimization design recently. In particular, it explores whether the compliant gripper mechanism shapes affect picking things up. In this unique study, we considered displacement values and the frequency values as response parameters during the simulation and the optimization design process. To test the effectiveness of the optimal design method, we proposed an initial compliant gripper mechanism carried out through the numerically experimental matrix—the Box–Behnken design. After that, we simulated the numerical model by utilizing the finite element method incorporating the approaches of desirability function, fuzzy logic system, and ANFIS. The results turn larger than those of the previous approaches. Moreover, numerical results reveal that the suggested hybrid method has a computational exactness more conspicuous than that of the Taguchi method. In short, the principle accomplishments with variables to the compliant gripper mechanism optimization design can be summarized up as follows: (i) the promising and potential proposed approach could meet the clients’ prerequisite, (ii) the idea of multi-objective optimization design ought to be re-considered when designing compliant gripper mechanism as well as applying related designing fields at the diminished expenses and the shortage time. © Springer-Verlag GmbH Germany, part of Springer Nature 2021
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title_short	Optimizing compliant gripper mechanism design by employing an effective bi-algorithm: fuzzy logic and ANFIS
url	https://dx.doi.org/10.1007/s00542-020-05132-w
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author2	Huynh, Ngoc-Thai Vu, Ngoc-Chien Kieu, Vu N. D. Huang, Shyh-Chour
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up_date	2024-07-04T01:47:40.998Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR044664125</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220110192009.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">210727s2021 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00542-020-05132-w</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR044664125</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s00542-020-05132-w-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">510</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">50.94</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Nguyen, Tien V. T.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Optimizing compliant gripper mechanism design by employing an effective bi-algorithm: fuzzy logic and ANFIS</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag GmbH Germany, part of Springer Nature 2021</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This investigation confronts the note-worthy improvement configuration gap in which such a design method could be better focused on the multi-objective optimization design of a compliant gripper mechanism as a robot arm through an effective hybrid algorithm of fuzzy logic and adaptive neuro-fuzzy inference system (ANFIS). We found that the proposed bi-algorithm approach is more compelling than theoretical ideas like auxiliary shape changes, materials, and directors of mechanisms when designing the compliant gripper mechanism with a set of novel multi-objective optimization design recently. In particular, it explores whether the compliant gripper mechanism shapes affect picking things up. In this unique study, we considered displacement values and the frequency values as response parameters during the simulation and the optimization design process. To test the effectiveness of the optimal design method, we proposed an initial compliant gripper mechanism carried out through the numerically experimental matrix—the Box–Behnken design. After that, we simulated the numerical model by utilizing the finite element method incorporating the approaches of desirability function, fuzzy logic system, and ANFIS. The results turn larger than those of the previous approaches. Moreover, numerical results reveal that the suggested hybrid method has a computational exactness more conspicuous than that of the Taguchi method. In short, the principle accomplishments with variables to the compliant gripper mechanism optimization design can be summarized up as follows: (i) the promising and potential proposed approach could meet the clients’ prerequisite, (ii) the idea of multi-objective optimization design ought to be re-considered when designing compliant gripper mechanism as well as applying related designing fields at the diminished expenses and the shortage time.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Huynh, Ngoc-Thai</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Vu, Ngoc-Chien</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kieu, Vu N. 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