Investigation of feasible controller for position control of flexible joint manipulator using multiple control techniques
Abstract With the advancement in technology, industries are moving from automation to robotics in the era of robotization. Different control techniques are being used in a different sector of production to control the whole machinery with special attention towards control the position and vibrations...
Ausführliche Beschreibung
Autor*in: |
Kumar, Subodh [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2019 |
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Schlagwörter: |
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Anmerkung: |
© Springer Nature Switzerland AG 2019 |
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Übergeordnetes Werk: |
Enthalten in: SN applied sciences - [Cham] : Springer International Publishing, 2019, 1(2019), 12 vom: 19. Nov. |
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Übergeordnetes Werk: |
volume:1 ; year:2019 ; number:12 ; day:19 ; month:11 |
Links: |
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DOI / URN: |
10.1007/s42452-019-1667-x |
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Katalog-ID: |
SPR038568446 |
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520 | |a Abstract With the advancement in technology, industries are moving from automation to robotics in the era of robotization. Different control techniques are being used in a different sector of production to control the whole machinery with special attention towards control the position and vibrations. In this research article, the feasible controller has been investigated for position control of flexible joint manipulator. For this, an effective version of a single linked flexible joint robotic manipulator has been used as a platform to control the position of manipulator using different control approaches. Euler’s–Lagrange equations have been used to obtain the effective version of the system and the position control has been performed by proportional-integral-derivative (PID) controller, pole –placement and linear quadratic regulator (LQR) methods. The main target of this research work is to maintain the rotational angle of the joint at an appropriate position and to remove the fluctuations at a specific robotic tool which is known as end effectors. The gains of PID controller have been delineated with the help of genetic algorithm and tuned for obtaining the most suitable gains to control the position of flexible joint manipulator and vibrations. As the settling time of the system was high so genetic algorithm has been used to optimize it. The $ Matlab^{®} $/simulation results depict that genetic algorithm tuned PID controller performed better correlated to both pole placement and LQR method of control. | ||
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700 | 1 | |a Kothari, D. P. |4 aut | |
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10.1007/s42452-019-1667-x doi (DE-627)SPR038568446 (SPR)s42452-019-1667-x-e DE-627 ger DE-627 rakwb eng Kumar, Subodh verfasserin (orcid)0000-0001-7311-6571 aut Investigation of feasible controller for position control of flexible joint manipulator using multiple control techniques 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Nature Switzerland AG 2019 Abstract With the advancement in technology, industries are moving from automation to robotics in the era of robotization. Different control techniques are being used in a different sector of production to control the whole machinery with special attention towards control the position and vibrations. In this research article, the feasible controller has been investigated for position control of flexible joint manipulator. For this, an effective version of a single linked flexible joint robotic manipulator has been used as a platform to control the position of manipulator using different control approaches. Euler’s–Lagrange equations have been used to obtain the effective version of the system and the position control has been performed by proportional-integral-derivative (PID) controller, pole –placement and linear quadratic regulator (LQR) methods. The main target of this research work is to maintain the rotational angle of the joint at an appropriate position and to remove the fluctuations at a specific robotic tool which is known as end effectors. The gains of PID controller have been delineated with the help of genetic algorithm and tuned for obtaining the most suitable gains to control the position of flexible joint manipulator and vibrations. As the settling time of the system was high so genetic algorithm has been used to optimize it. The $ Matlab^{®} $/simulation results depict that genetic algorithm tuned PID controller performed better correlated to both pole placement and LQR method of control. Flexible joint manipulator (FJM) (dpeaa)DE-He213 PID (dpeaa)DE-He213 Pole-placement (dpeaa)DE-He213 Linear quadratic regulator (LQR) (dpeaa)DE-He213 Jayaswal, Kuldeep (orcid)0000-0002-8959-1163 aut Kothari, D. P. aut Enthalten in SN applied sciences [Cham] : Springer International Publishing, 2019 1(2019), 12 vom: 19. Nov. (DE-627)103761139X (DE-600)2947292-1 2523-3971 nnns volume:1 year:2019 number:12 day:19 month:11 https://dx.doi.org/10.1007/s42452-019-1667-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 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_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_2007 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_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_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 1 2019 12 19 11 |
spelling |
10.1007/s42452-019-1667-x doi (DE-627)SPR038568446 (SPR)s42452-019-1667-x-e DE-627 ger DE-627 rakwb eng Kumar, Subodh verfasserin (orcid)0000-0001-7311-6571 aut Investigation of feasible controller for position control of flexible joint manipulator using multiple control techniques 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Nature Switzerland AG 2019 Abstract With the advancement in technology, industries are moving from automation to robotics in the era of robotization. Different control techniques are being used in a different sector of production to control the whole machinery with special attention towards control the position and vibrations. In this research article, the feasible controller has been investigated for position control of flexible joint manipulator. For this, an effective version of a single linked flexible joint robotic manipulator has been used as a platform to control the position of manipulator using different control approaches. Euler’s–Lagrange equations have been used to obtain the effective version of the system and the position control has been performed by proportional-integral-derivative (PID) controller, pole –placement and linear quadratic regulator (LQR) methods. The main target of this research work is to maintain the rotational angle of the joint at an appropriate position and to remove the fluctuations at a specific robotic tool which is known as end effectors. The gains of PID controller have been delineated with the help of genetic algorithm and tuned for obtaining the most suitable gains to control the position of flexible joint manipulator and vibrations. As the settling time of the system was high so genetic algorithm has been used to optimize it. The $ Matlab^{®} $/simulation results depict that genetic algorithm tuned PID controller performed better correlated to both pole placement and LQR method of control. Flexible joint manipulator (FJM) (dpeaa)DE-He213 PID (dpeaa)DE-He213 Pole-placement (dpeaa)DE-He213 Linear quadratic regulator (LQR) (dpeaa)DE-He213 Jayaswal, Kuldeep (orcid)0000-0002-8959-1163 aut Kothari, D. P. aut Enthalten in SN applied sciences [Cham] : Springer International Publishing, 2019 1(2019), 12 vom: 19. Nov. (DE-627)103761139X (DE-600)2947292-1 2523-3971 nnns volume:1 year:2019 number:12 day:19 month:11 https://dx.doi.org/10.1007/s42452-019-1667-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 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_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_2007 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_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_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 1 2019 12 19 11 |
allfields_unstemmed |
10.1007/s42452-019-1667-x doi (DE-627)SPR038568446 (SPR)s42452-019-1667-x-e DE-627 ger DE-627 rakwb eng Kumar, Subodh verfasserin (orcid)0000-0001-7311-6571 aut Investigation of feasible controller for position control of flexible joint manipulator using multiple control techniques 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Nature Switzerland AG 2019 Abstract With the advancement in technology, industries are moving from automation to robotics in the era of robotization. Different control techniques are being used in a different sector of production to control the whole machinery with special attention towards control the position and vibrations. In this research article, the feasible controller has been investigated for position control of flexible joint manipulator. For this, an effective version of a single linked flexible joint robotic manipulator has been used as a platform to control the position of manipulator using different control approaches. Euler’s–Lagrange equations have been used to obtain the effective version of the system and the position control has been performed by proportional-integral-derivative (PID) controller, pole –placement and linear quadratic regulator (LQR) methods. The main target of this research work is to maintain the rotational angle of the joint at an appropriate position and to remove the fluctuations at a specific robotic tool which is known as end effectors. The gains of PID controller have been delineated with the help of genetic algorithm and tuned for obtaining the most suitable gains to control the position of flexible joint manipulator and vibrations. As the settling time of the system was high so genetic algorithm has been used to optimize it. The $ Matlab^{®} $/simulation results depict that genetic algorithm tuned PID controller performed better correlated to both pole placement and LQR method of control. Flexible joint manipulator (FJM) (dpeaa)DE-He213 PID (dpeaa)DE-He213 Pole-placement (dpeaa)DE-He213 Linear quadratic regulator (LQR) (dpeaa)DE-He213 Jayaswal, Kuldeep (orcid)0000-0002-8959-1163 aut Kothari, D. P. aut Enthalten in SN applied sciences [Cham] : Springer International Publishing, 2019 1(2019), 12 vom: 19. Nov. (DE-627)103761139X (DE-600)2947292-1 2523-3971 nnns volume:1 year:2019 number:12 day:19 month:11 https://dx.doi.org/10.1007/s42452-019-1667-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 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_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_2007 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_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_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 1 2019 12 19 11 |
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10.1007/s42452-019-1667-x doi (DE-627)SPR038568446 (SPR)s42452-019-1667-x-e DE-627 ger DE-627 rakwb eng Kumar, Subodh verfasserin (orcid)0000-0001-7311-6571 aut Investigation of feasible controller for position control of flexible joint manipulator using multiple control techniques 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Nature Switzerland AG 2019 Abstract With the advancement in technology, industries are moving from automation to robotics in the era of robotization. Different control techniques are being used in a different sector of production to control the whole machinery with special attention towards control the position and vibrations. In this research article, the feasible controller has been investigated for position control of flexible joint manipulator. For this, an effective version of a single linked flexible joint robotic manipulator has been used as a platform to control the position of manipulator using different control approaches. Euler’s–Lagrange equations have been used to obtain the effective version of the system and the position control has been performed by proportional-integral-derivative (PID) controller, pole –placement and linear quadratic regulator (LQR) methods. The main target of this research work is to maintain the rotational angle of the joint at an appropriate position and to remove the fluctuations at a specific robotic tool which is known as end effectors. The gains of PID controller have been delineated with the help of genetic algorithm and tuned for obtaining the most suitable gains to control the position of flexible joint manipulator and vibrations. As the settling time of the system was high so genetic algorithm has been used to optimize it. The $ Matlab^{®} $/simulation results depict that genetic algorithm tuned PID controller performed better correlated to both pole placement and LQR method of control. Flexible joint manipulator (FJM) (dpeaa)DE-He213 PID (dpeaa)DE-He213 Pole-placement (dpeaa)DE-He213 Linear quadratic regulator (LQR) (dpeaa)DE-He213 Jayaswal, Kuldeep (orcid)0000-0002-8959-1163 aut Kothari, D. P. aut Enthalten in SN applied sciences [Cham] : Springer International Publishing, 2019 1(2019), 12 vom: 19. Nov. (DE-627)103761139X (DE-600)2947292-1 2523-3971 nnns volume:1 year:2019 number:12 day:19 month:11 https://dx.doi.org/10.1007/s42452-019-1667-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 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_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_2007 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_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_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 1 2019 12 19 11 |
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Kumar, Subodh @@aut@@ Jayaswal, Kuldeep @@aut@@ Kothari, D. P. @@aut@@ |
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Kumar, Subodh |
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Kumar, Subodh misc Flexible joint manipulator (FJM) misc PID misc Pole-placement misc Linear quadratic regulator (LQR) Investigation of feasible controller for position control of flexible joint manipulator using multiple control techniques |
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Investigation of feasible controller for position control of flexible joint manipulator using multiple control techniques Flexible joint manipulator (FJM) (dpeaa)DE-He213 PID (dpeaa)DE-He213 Pole-placement (dpeaa)DE-He213 Linear quadratic regulator (LQR) (dpeaa)DE-He213 |
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Investigation of feasible controller for position control of flexible joint manipulator using multiple control techniques |
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Investigation of feasible controller for position control of flexible joint manipulator using multiple control techniques |
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investigation of feasible controller for position control of flexible joint manipulator using multiple control techniques |
title_auth |
Investigation of feasible controller for position control of flexible joint manipulator using multiple control techniques |
abstract |
Abstract With the advancement in technology, industries are moving from automation to robotics in the era of robotization. Different control techniques are being used in a different sector of production to control the whole machinery with special attention towards control the position and vibrations. In this research article, the feasible controller has been investigated for position control of flexible joint manipulator. For this, an effective version of a single linked flexible joint robotic manipulator has been used as a platform to control the position of manipulator using different control approaches. Euler’s–Lagrange equations have been used to obtain the effective version of the system and the position control has been performed by proportional-integral-derivative (PID) controller, pole –placement and linear quadratic regulator (LQR) methods. The main target of this research work is to maintain the rotational angle of the joint at an appropriate position and to remove the fluctuations at a specific robotic tool which is known as end effectors. The gains of PID controller have been delineated with the help of genetic algorithm and tuned for obtaining the most suitable gains to control the position of flexible joint manipulator and vibrations. As the settling time of the system was high so genetic algorithm has been used to optimize it. The $ Matlab^{®} $/simulation results depict that genetic algorithm tuned PID controller performed better correlated to both pole placement and LQR method of control. © Springer Nature Switzerland AG 2019 |
abstractGer |
Abstract With the advancement in technology, industries are moving from automation to robotics in the era of robotization. Different control techniques are being used in a different sector of production to control the whole machinery with special attention towards control the position and vibrations. In this research article, the feasible controller has been investigated for position control of flexible joint manipulator. For this, an effective version of a single linked flexible joint robotic manipulator has been used as a platform to control the position of manipulator using different control approaches. Euler’s–Lagrange equations have been used to obtain the effective version of the system and the position control has been performed by proportional-integral-derivative (PID) controller, pole –placement and linear quadratic regulator (LQR) methods. The main target of this research work is to maintain the rotational angle of the joint at an appropriate position and to remove the fluctuations at a specific robotic tool which is known as end effectors. The gains of PID controller have been delineated with the help of genetic algorithm and tuned for obtaining the most suitable gains to control the position of flexible joint manipulator and vibrations. As the settling time of the system was high so genetic algorithm has been used to optimize it. The $ Matlab^{®} $/simulation results depict that genetic algorithm tuned PID controller performed better correlated to both pole placement and LQR method of control. © Springer Nature Switzerland AG 2019 |
abstract_unstemmed |
Abstract With the advancement in technology, industries are moving from automation to robotics in the era of robotization. Different control techniques are being used in a different sector of production to control the whole machinery with special attention towards control the position and vibrations. In this research article, the feasible controller has been investigated for position control of flexible joint manipulator. For this, an effective version of a single linked flexible joint robotic manipulator has been used as a platform to control the position of manipulator using different control approaches. Euler’s–Lagrange equations have been used to obtain the effective version of the system and the position control has been performed by proportional-integral-derivative (PID) controller, pole –placement and linear quadratic regulator (LQR) methods. The main target of this research work is to maintain the rotational angle of the joint at an appropriate position and to remove the fluctuations at a specific robotic tool which is known as end effectors. The gains of PID controller have been delineated with the help of genetic algorithm and tuned for obtaining the most suitable gains to control the position of flexible joint manipulator and vibrations. As the settling time of the system was high so genetic algorithm has been used to optimize it. The $ Matlab^{®} $/simulation results depict that genetic algorithm tuned PID controller performed better correlated to both pole placement and LQR method of control. © Springer Nature Switzerland AG 2019 |
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Investigation of feasible controller for position control of flexible joint manipulator using multiple control techniques |
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