Neural-based adaptive fixed-time prescribed performance control for the flexible-joint robot with actuator failures
Abstract In this paper, a fixed-time prescribed performance fault-tolerant control scheme is presented for the n-link flexible joint robot with actuator failures. Firstly, a modified prescribed performance control method is proposed to enhance the robustness of the system against input perturbations...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Li, Tandong [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
Modified-prescribed performance |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Nonlinear dynamics - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990, 111(2023), 17 vom: 26. Juli, Seite 16187-16214 |
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| Übergeordnetes Werk: |
volume:111 ; year:2023 ; number:17 ; day:26 ; month:07 ; pages:16187-16214 |
| Links: |
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| DOI / URN: |
10.1007/s11071-023-08714-1 |
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| Katalog-ID: |
SPR05273949X |
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| 520 | |a Abstract In this paper, a fixed-time prescribed performance fault-tolerant control scheme is presented for the n-link flexible joint robot with actuator failures. Firstly, a modified prescribed performance control method is proposed to enhance the robustness of the system against input perturbations and to ensure that the tracking error converges in a predetermined time, and the constrained system is transferred into an unconstrained system. Secondly, an adaptive-based passive fault-tolerant controller is constructed to counteract the actuator failures in the system. Then, the uncertainty problem in the flexible-joint robot system is solved by incorporating the radial basis function neural networks and adaptive techniques into the fixed-time backstepping framework. After that, the “complexity explosion” issue is well handled by creating the fixed-time second-order filter, in which the filtering errors are eliminated by the devised compensation mechanism. The stability analysis proves that the closed-loop system is fixed-time stable, and the tracking error is limited to the predefined range. Finally, simulations have been performed on a two-link FJR and a three-link flexible joint robot, respectively. Via the three conditions: actuators operating normally, actuators losing 50% of effectiveness instantaneously, and actuators losing 50% of effectiveness gradually, the results show that the tracking error of each joint of the system is less than 0.2 rad, and the tracking time is limited to the specified time (0.8 s), which proves the effectiveness of the proposed control scheme. | ||
| 650 | 4 | |a Neural adaptive approximation |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Modified-prescribed performance |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Fault-tolerant control |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Fixed-time second-order filter |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Compensation mechanism |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a The |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a -link flexible-joint robot |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Zhang, Junxing |4 aut | |
| 700 | 1 | |a Li, Shaobo |4 aut | |
| 700 | 1 | |a Zhou, Peng |4 aut | |
| 700 | 1 | |a Lv, Dongchao |4 aut | |
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10.1007/s11071-023-08714-1 doi (DE-627)SPR05273949X (SPR)s11071-023-08714-1-e DE-627 ger DE-627 rakwb eng Li, Tandong verfasserin aut Neural-based adaptive fixed-time prescribed performance control for the flexible-joint robot with actuator failures 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In this paper, a fixed-time prescribed performance fault-tolerant control scheme is presented for the n-link flexible joint robot with actuator failures. Firstly, a modified prescribed performance control method is proposed to enhance the robustness of the system against input perturbations and to ensure that the tracking error converges in a predetermined time, and the constrained system is transferred into an unconstrained system. Secondly, an adaptive-based passive fault-tolerant controller is constructed to counteract the actuator failures in the system. Then, the uncertainty problem in the flexible-joint robot system is solved by incorporating the radial basis function neural networks and adaptive techniques into the fixed-time backstepping framework. After that, the “complexity explosion” issue is well handled by creating the fixed-time second-order filter, in which the filtering errors are eliminated by the devised compensation mechanism. The stability analysis proves that the closed-loop system is fixed-time stable, and the tracking error is limited to the predefined range. Finally, simulations have been performed on a two-link FJR and a three-link flexible joint robot, respectively. Via the three conditions: actuators operating normally, actuators losing 50% of effectiveness instantaneously, and actuators losing 50% of effectiveness gradually, the results show that the tracking error of each joint of the system is less than 0.2 rad, and the tracking time is limited to the specified time (0.8 s), which proves the effectiveness of the proposed control scheme. Neural adaptive approximation (dpeaa)DE-He213 Modified-prescribed performance (dpeaa)DE-He213 Fault-tolerant control (dpeaa)DE-He213 Fixed-time second-order filter (dpeaa)DE-He213 Compensation mechanism (dpeaa)DE-He213 The (dpeaa)DE-He213 -link flexible-joint robot (dpeaa)DE-He213 Zhang, Junxing aut Li, Shaobo aut Zhou, Peng aut Lv, Dongchao aut Enthalten in Nonlinear dynamics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 111(2023), 17 vom: 26. Juli, Seite 16187-16214 (DE-627)315297034 (DE-600)2012600-1 1573-269X nnns volume:111 year:2023 number:17 day:26 month:07 pages:16187-16214 https://dx.doi.org/10.1007/s11071-023-08714-1 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_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_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 AR 111 2023 17 26 07 16187-16214 |
| spelling |
10.1007/s11071-023-08714-1 doi (DE-627)SPR05273949X (SPR)s11071-023-08714-1-e DE-627 ger DE-627 rakwb eng Li, Tandong verfasserin aut Neural-based adaptive fixed-time prescribed performance control for the flexible-joint robot with actuator failures 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In this paper, a fixed-time prescribed performance fault-tolerant control scheme is presented for the n-link flexible joint robot with actuator failures. Firstly, a modified prescribed performance control method is proposed to enhance the robustness of the system against input perturbations and to ensure that the tracking error converges in a predetermined time, and the constrained system is transferred into an unconstrained system. Secondly, an adaptive-based passive fault-tolerant controller is constructed to counteract the actuator failures in the system. Then, the uncertainty problem in the flexible-joint robot system is solved by incorporating the radial basis function neural networks and adaptive techniques into the fixed-time backstepping framework. After that, the “complexity explosion” issue is well handled by creating the fixed-time second-order filter, in which the filtering errors are eliminated by the devised compensation mechanism. The stability analysis proves that the closed-loop system is fixed-time stable, and the tracking error is limited to the predefined range. Finally, simulations have been performed on a two-link FJR and a three-link flexible joint robot, respectively. Via the three conditions: actuators operating normally, actuators losing 50% of effectiveness instantaneously, and actuators losing 50% of effectiveness gradually, the results show that the tracking error of each joint of the system is less than 0.2 rad, and the tracking time is limited to the specified time (0.8 s), which proves the effectiveness of the proposed control scheme. Neural adaptive approximation (dpeaa)DE-He213 Modified-prescribed performance (dpeaa)DE-He213 Fault-tolerant control (dpeaa)DE-He213 Fixed-time second-order filter (dpeaa)DE-He213 Compensation mechanism (dpeaa)DE-He213 The (dpeaa)DE-He213 -link flexible-joint robot (dpeaa)DE-He213 Zhang, Junxing aut Li, Shaobo aut Zhou, Peng aut Lv, Dongchao aut Enthalten in Nonlinear dynamics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 111(2023), 17 vom: 26. Juli, Seite 16187-16214 (DE-627)315297034 (DE-600)2012600-1 1573-269X nnns volume:111 year:2023 number:17 day:26 month:07 pages:16187-16214 https://dx.doi.org/10.1007/s11071-023-08714-1 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_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_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 AR 111 2023 17 26 07 16187-16214 |
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10.1007/s11071-023-08714-1 doi (DE-627)SPR05273949X (SPR)s11071-023-08714-1-e DE-627 ger DE-627 rakwb eng Li, Tandong verfasserin aut Neural-based adaptive fixed-time prescribed performance control for the flexible-joint robot with actuator failures 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In this paper, a fixed-time prescribed performance fault-tolerant control scheme is presented for the n-link flexible joint robot with actuator failures. Firstly, a modified prescribed performance control method is proposed to enhance the robustness of the system against input perturbations and to ensure that the tracking error converges in a predetermined time, and the constrained system is transferred into an unconstrained system. Secondly, an adaptive-based passive fault-tolerant controller is constructed to counteract the actuator failures in the system. Then, the uncertainty problem in the flexible-joint robot system is solved by incorporating the radial basis function neural networks and adaptive techniques into the fixed-time backstepping framework. After that, the “complexity explosion” issue is well handled by creating the fixed-time second-order filter, in which the filtering errors are eliminated by the devised compensation mechanism. The stability analysis proves that the closed-loop system is fixed-time stable, and the tracking error is limited to the predefined range. Finally, simulations have been performed on a two-link FJR and a three-link flexible joint robot, respectively. Via the three conditions: actuators operating normally, actuators losing 50% of effectiveness instantaneously, and actuators losing 50% of effectiveness gradually, the results show that the tracking error of each joint of the system is less than 0.2 rad, and the tracking time is limited to the specified time (0.8 s), which proves the effectiveness of the proposed control scheme. Neural adaptive approximation (dpeaa)DE-He213 Modified-prescribed performance (dpeaa)DE-He213 Fault-tolerant control (dpeaa)DE-He213 Fixed-time second-order filter (dpeaa)DE-He213 Compensation mechanism (dpeaa)DE-He213 The (dpeaa)DE-He213 -link flexible-joint robot (dpeaa)DE-He213 Zhang, Junxing aut Li, Shaobo aut Zhou, Peng aut Lv, Dongchao aut Enthalten in Nonlinear dynamics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 111(2023), 17 vom: 26. Juli, Seite 16187-16214 (DE-627)315297034 (DE-600)2012600-1 1573-269X nnns volume:111 year:2023 number:17 day:26 month:07 pages:16187-16214 https://dx.doi.org/10.1007/s11071-023-08714-1 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_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_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 AR 111 2023 17 26 07 16187-16214 |
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10.1007/s11071-023-08714-1 doi (DE-627)SPR05273949X (SPR)s11071-023-08714-1-e DE-627 ger DE-627 rakwb eng Li, Tandong verfasserin aut Neural-based adaptive fixed-time prescribed performance control for the flexible-joint robot with actuator failures 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In this paper, a fixed-time prescribed performance fault-tolerant control scheme is presented for the n-link flexible joint robot with actuator failures. Firstly, a modified prescribed performance control method is proposed to enhance the robustness of the system against input perturbations and to ensure that the tracking error converges in a predetermined time, and the constrained system is transferred into an unconstrained system. Secondly, an adaptive-based passive fault-tolerant controller is constructed to counteract the actuator failures in the system. Then, the uncertainty problem in the flexible-joint robot system is solved by incorporating the radial basis function neural networks and adaptive techniques into the fixed-time backstepping framework. After that, the “complexity explosion” issue is well handled by creating the fixed-time second-order filter, in which the filtering errors are eliminated by the devised compensation mechanism. The stability analysis proves that the closed-loop system is fixed-time stable, and the tracking error is limited to the predefined range. Finally, simulations have been performed on a two-link FJR and a three-link flexible joint robot, respectively. Via the three conditions: actuators operating normally, actuators losing 50% of effectiveness instantaneously, and actuators losing 50% of effectiveness gradually, the results show that the tracking error of each joint of the system is less than 0.2 rad, and the tracking time is limited to the specified time (0.8 s), which proves the effectiveness of the proposed control scheme. Neural adaptive approximation (dpeaa)DE-He213 Modified-prescribed performance (dpeaa)DE-He213 Fault-tolerant control (dpeaa)DE-He213 Fixed-time second-order filter (dpeaa)DE-He213 Compensation mechanism (dpeaa)DE-He213 The (dpeaa)DE-He213 -link flexible-joint robot (dpeaa)DE-He213 Zhang, Junxing aut Li, Shaobo aut Zhou, Peng aut Lv, Dongchao aut Enthalten in Nonlinear dynamics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 111(2023), 17 vom: 26. Juli, Seite 16187-16214 (DE-627)315297034 (DE-600)2012600-1 1573-269X nnns volume:111 year:2023 number:17 day:26 month:07 pages:16187-16214 https://dx.doi.org/10.1007/s11071-023-08714-1 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_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_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 AR 111 2023 17 26 07 16187-16214 |
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10.1007/s11071-023-08714-1 doi (DE-627)SPR05273949X (SPR)s11071-023-08714-1-e DE-627 ger DE-627 rakwb eng Li, Tandong verfasserin aut Neural-based adaptive fixed-time prescribed performance control for the flexible-joint robot with actuator failures 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In this paper, a fixed-time prescribed performance fault-tolerant control scheme is presented for the n-link flexible joint robot with actuator failures. Firstly, a modified prescribed performance control method is proposed to enhance the robustness of the system against input perturbations and to ensure that the tracking error converges in a predetermined time, and the constrained system is transferred into an unconstrained system. Secondly, an adaptive-based passive fault-tolerant controller is constructed to counteract the actuator failures in the system. Then, the uncertainty problem in the flexible-joint robot system is solved by incorporating the radial basis function neural networks and adaptive techniques into the fixed-time backstepping framework. After that, the “complexity explosion” issue is well handled by creating the fixed-time second-order filter, in which the filtering errors are eliminated by the devised compensation mechanism. The stability analysis proves that the closed-loop system is fixed-time stable, and the tracking error is limited to the predefined range. Finally, simulations have been performed on a two-link FJR and a three-link flexible joint robot, respectively. Via the three conditions: actuators operating normally, actuators losing 50% of effectiveness instantaneously, and actuators losing 50% of effectiveness gradually, the results show that the tracking error of each joint of the system is less than 0.2 rad, and the tracking time is limited to the specified time (0.8 s), which proves the effectiveness of the proposed control scheme. Neural adaptive approximation (dpeaa)DE-He213 Modified-prescribed performance (dpeaa)DE-He213 Fault-tolerant control (dpeaa)DE-He213 Fixed-time second-order filter (dpeaa)DE-He213 Compensation mechanism (dpeaa)DE-He213 The (dpeaa)DE-He213 -link flexible-joint robot (dpeaa)DE-He213 Zhang, Junxing aut Li, Shaobo aut Zhou, Peng aut Lv, Dongchao aut Enthalten in Nonlinear dynamics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 111(2023), 17 vom: 26. Juli, Seite 16187-16214 (DE-627)315297034 (DE-600)2012600-1 1573-269X nnns volume:111 year:2023 number:17 day:26 month:07 pages:16187-16214 https://dx.doi.org/10.1007/s11071-023-08714-1 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_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_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 AR 111 2023 17 26 07 16187-16214 |
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Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract In this paper, a fixed-time prescribed performance fault-tolerant control scheme is presented for the n-link flexible joint robot with actuator failures. Firstly, a modified prescribed performance control method is proposed to enhance the robustness of the system against input perturbations and to ensure that the tracking error converges in a predetermined time, and the constrained system is transferred into an unconstrained system. Secondly, an adaptive-based passive fault-tolerant controller is constructed to counteract the actuator failures in the system. Then, the uncertainty problem in the flexible-joint robot system is solved by incorporating the radial basis function neural networks and adaptive techniques into the fixed-time backstepping framework. After that, the “complexity explosion” issue is well handled by creating the fixed-time second-order filter, in which the filtering errors are eliminated by the devised compensation mechanism. The stability analysis proves that the closed-loop system is fixed-time stable, and the tracking error is limited to the predefined range. Finally, simulations have been performed on a two-link FJR and a three-link flexible joint robot, respectively. Via the three conditions: actuators operating normally, actuators losing 50% of effectiveness instantaneously, and actuators losing 50% of effectiveness gradually, the results show that the tracking error of each joint of the system is less than 0.2 rad, and the tracking time is limited to the specified time (0.8 s), which proves the effectiveness of the proposed control scheme.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Neural adaptive approximation</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Modified-prescribed performance</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Fault-tolerant control</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Fixed-time second-order filter</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Compensation mechanism</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">The</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">-link flexible-joint robot</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhang, Junxing</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, Shaobo</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhou, Peng</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lv, Dongchao</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Nonlinear dynamics</subfield><subfield code="d">Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990</subfield><subfield code="g">111(2023), 17 vom: 26. 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Li, Tandong |
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Li, Tandong misc Neural adaptive approximation misc Modified-prescribed performance misc Fault-tolerant control misc Fixed-time second-order filter misc Compensation mechanism misc The misc -link flexible-joint robot Neural-based adaptive fixed-time prescribed performance control for the flexible-joint robot with actuator failures |
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Neural-based adaptive fixed-time prescribed performance control for the flexible-joint robot with actuator failures Neural adaptive approximation (dpeaa)DE-He213 Modified-prescribed performance (dpeaa)DE-He213 Fault-tolerant control (dpeaa)DE-He213 Fixed-time second-order filter (dpeaa)DE-He213 Compensation mechanism (dpeaa)DE-He213 The (dpeaa)DE-He213 -link flexible-joint robot (dpeaa)DE-He213 |
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misc Neural adaptive approximation misc Modified-prescribed performance misc Fault-tolerant control misc Fixed-time second-order filter misc Compensation mechanism misc The misc -link flexible-joint robot |
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misc Neural adaptive approximation misc Modified-prescribed performance misc Fault-tolerant control misc Fixed-time second-order filter misc Compensation mechanism misc The misc -link flexible-joint robot |
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misc Neural adaptive approximation misc Modified-prescribed performance misc Fault-tolerant control misc Fixed-time second-order filter misc Compensation mechanism misc The misc -link flexible-joint robot |
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Li, Tandong Zhang, Junxing Li, Shaobo Zhou, Peng Lv, Dongchao |
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neural-based adaptive fixed-time prescribed performance control for the flexible-joint robot with actuator failures |
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Neural-based adaptive fixed-time prescribed performance control for the flexible-joint robot with actuator failures |
| abstract |
Abstract In this paper, a fixed-time prescribed performance fault-tolerant control scheme is presented for the n-link flexible joint robot with actuator failures. Firstly, a modified prescribed performance control method is proposed to enhance the robustness of the system against input perturbations and to ensure that the tracking error converges in a predetermined time, and the constrained system is transferred into an unconstrained system. Secondly, an adaptive-based passive fault-tolerant controller is constructed to counteract the actuator failures in the system. Then, the uncertainty problem in the flexible-joint robot system is solved by incorporating the radial basis function neural networks and adaptive techniques into the fixed-time backstepping framework. After that, the “complexity explosion” issue is well handled by creating the fixed-time second-order filter, in which the filtering errors are eliminated by the devised compensation mechanism. The stability analysis proves that the closed-loop system is fixed-time stable, and the tracking error is limited to the predefined range. Finally, simulations have been performed on a two-link FJR and a three-link flexible joint robot, respectively. Via the three conditions: actuators operating normally, actuators losing 50% of effectiveness instantaneously, and actuators losing 50% of effectiveness gradually, the results show that the tracking error of each joint of the system is less than 0.2 rad, and the tracking time is limited to the specified time (0.8 s), which proves the effectiveness of the proposed control scheme. © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstractGer |
Abstract In this paper, a fixed-time prescribed performance fault-tolerant control scheme is presented for the n-link flexible joint robot with actuator failures. Firstly, a modified prescribed performance control method is proposed to enhance the robustness of the system against input perturbations and to ensure that the tracking error converges in a predetermined time, and the constrained system is transferred into an unconstrained system. Secondly, an adaptive-based passive fault-tolerant controller is constructed to counteract the actuator failures in the system. Then, the uncertainty problem in the flexible-joint robot system is solved by incorporating the radial basis function neural networks and adaptive techniques into the fixed-time backstepping framework. After that, the “complexity explosion” issue is well handled by creating the fixed-time second-order filter, in which the filtering errors are eliminated by the devised compensation mechanism. The stability analysis proves that the closed-loop system is fixed-time stable, and the tracking error is limited to the predefined range. Finally, simulations have been performed on a two-link FJR and a three-link flexible joint robot, respectively. Via the three conditions: actuators operating normally, actuators losing 50% of effectiveness instantaneously, and actuators losing 50% of effectiveness gradually, the results show that the tracking error of each joint of the system is less than 0.2 rad, and the tracking time is limited to the specified time (0.8 s), which proves the effectiveness of the proposed control scheme. © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Abstract In this paper, a fixed-time prescribed performance fault-tolerant control scheme is presented for the n-link flexible joint robot with actuator failures. Firstly, a modified prescribed performance control method is proposed to enhance the robustness of the system against input perturbations and to ensure that the tracking error converges in a predetermined time, and the constrained system is transferred into an unconstrained system. Secondly, an adaptive-based passive fault-tolerant controller is constructed to counteract the actuator failures in the system. Then, the uncertainty problem in the flexible-joint robot system is solved by incorporating the radial basis function neural networks and adaptive techniques into the fixed-time backstepping framework. After that, the “complexity explosion” issue is well handled by creating the fixed-time second-order filter, in which the filtering errors are eliminated by the devised compensation mechanism. The stability analysis proves that the closed-loop system is fixed-time stable, and the tracking error is limited to the predefined range. Finally, simulations have been performed on a two-link FJR and a three-link flexible joint robot, respectively. Via the three conditions: actuators operating normally, actuators losing 50% of effectiveness instantaneously, and actuators losing 50% of effectiveness gradually, the results show that the tracking error of each joint of the system is less than 0.2 rad, and the tracking time is limited to the specified time (0.8 s), which proves the effectiveness of the proposed control scheme. © The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| title_short |
Neural-based adaptive fixed-time prescribed performance control for the flexible-joint robot with actuator failures |
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https://dx.doi.org/10.1007/s11071-023-08714-1 |
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Zhang, Junxing Li, Shaobo Zhou, Peng Lv, Dongchao |
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Zhang, Junxing Li, Shaobo Zhou, Peng Lv, Dongchao |
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10.1007/s11071-023-08714-1 |
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2024-07-03T14:26:50.268Z |
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| score |
7.4001513 |