Robust Learning Control for Tank Gun Control Servo Systems Under Alignment Condition

This paper proposes an adaptive learning control scheme to solve high-precision velocity tracking problem for tank gun control servo systems. Lyapunov approach is used to design the learning controller, with alignment condition used to cope with initial problem of iterative learning control. Robust...
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Autor*in:	Guangming Zhu [verfasserIn] Xiushan Wu [verfasserIn] Qiuzhen Yan [verfasserIn] Jianping Cai [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Tank gun control servo systems iterative learning control adaptive control

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 7(2019), Seite 145524-145531
Übergeordnetes Werk:	volume:7 ; year:2019 ; pages:145524-145531

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2019.2938814

Katalog-ID:	DOAJ014522896

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allfields	10.1109/ACCESS.2019.2938814 doi (DE-627)DOAJ014522896 (DE-599)DOAJe5bd1bb471c141fb9fdfe7ed760baaec DE-627 ger DE-627 rakwb eng TK1-9971 Guangming Zhu verfasserin aut Robust Learning Control for Tank Gun Control Servo Systems Under Alignment Condition 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper proposes an adaptive learning control scheme to solve high-precision velocity tracking problem for tank gun control servo systems. Lyapunov approach is used to design the learning controller, with alignment condition used to cope with initial problem of iterative learning control. Robust control technique and adaptive learning control technique are synthesized to handle nonlinear uncertainties and external disturbances. The unknown parameters are estimated according to the full saturation difference learning strategy. As the iteration number increases, the system state can accurately track the reference signal over the whole time interval, and all signal are guaranteed to be bounded. Tank gun control servo systems iterative learning control adaptive control Electrical engineering. Electronics. Nuclear engineering Xiushan Wu verfasserin aut Qiuzhen Yan verfasserin aut Jianping Cai verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 145524-145531 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:145524-145531 https://doi.org/10.1109/ACCESS.2019.2938814 kostenfrei https://doaj.org/article/e5bd1bb471c141fb9fdfe7ed760baaec kostenfrei https://ieeexplore.ieee.org/document/8822428/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 145524-145531
spelling	10.1109/ACCESS.2019.2938814 doi (DE-627)DOAJ014522896 (DE-599)DOAJe5bd1bb471c141fb9fdfe7ed760baaec DE-627 ger DE-627 rakwb eng TK1-9971 Guangming Zhu verfasserin aut Robust Learning Control for Tank Gun Control Servo Systems Under Alignment Condition 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper proposes an adaptive learning control scheme to solve high-precision velocity tracking problem for tank gun control servo systems. Lyapunov approach is used to design the learning controller, with alignment condition used to cope with initial problem of iterative learning control. Robust control technique and adaptive learning control technique are synthesized to handle nonlinear uncertainties and external disturbances. The unknown parameters are estimated according to the full saturation difference learning strategy. As the iteration number increases, the system state can accurately track the reference signal over the whole time interval, and all signal are guaranteed to be bounded. Tank gun control servo systems iterative learning control adaptive control Electrical engineering. Electronics. Nuclear engineering Xiushan Wu verfasserin aut Qiuzhen Yan verfasserin aut Jianping Cai verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 145524-145531 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:145524-145531 https://doi.org/10.1109/ACCESS.2019.2938814 kostenfrei https://doaj.org/article/e5bd1bb471c141fb9fdfe7ed760baaec kostenfrei https://ieeexplore.ieee.org/document/8822428/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 145524-145531
allfields_unstemmed	10.1109/ACCESS.2019.2938814 doi (DE-627)DOAJ014522896 (DE-599)DOAJe5bd1bb471c141fb9fdfe7ed760baaec DE-627 ger DE-627 rakwb eng TK1-9971 Guangming Zhu verfasserin aut Robust Learning Control for Tank Gun Control Servo Systems Under Alignment Condition 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper proposes an adaptive learning control scheme to solve high-precision velocity tracking problem for tank gun control servo systems. Lyapunov approach is used to design the learning controller, with alignment condition used to cope with initial problem of iterative learning control. Robust control technique and adaptive learning control technique are synthesized to handle nonlinear uncertainties and external disturbances. The unknown parameters are estimated according to the full saturation difference learning strategy. As the iteration number increases, the system state can accurately track the reference signal over the whole time interval, and all signal are guaranteed to be bounded. Tank gun control servo systems iterative learning control adaptive control Electrical engineering. Electronics. Nuclear engineering Xiushan Wu verfasserin aut Qiuzhen Yan verfasserin aut Jianping Cai verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 145524-145531 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:145524-145531 https://doi.org/10.1109/ACCESS.2019.2938814 kostenfrei https://doaj.org/article/e5bd1bb471c141fb9fdfe7ed760baaec kostenfrei https://ieeexplore.ieee.org/document/8822428/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 145524-145531
allfieldsGer	10.1109/ACCESS.2019.2938814 doi (DE-627)DOAJ014522896 (DE-599)DOAJe5bd1bb471c141fb9fdfe7ed760baaec DE-627 ger DE-627 rakwb eng TK1-9971 Guangming Zhu verfasserin aut Robust Learning Control for Tank Gun Control Servo Systems Under Alignment Condition 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper proposes an adaptive learning control scheme to solve high-precision velocity tracking problem for tank gun control servo systems. Lyapunov approach is used to design the learning controller, with alignment condition used to cope with initial problem of iterative learning control. Robust control technique and adaptive learning control technique are synthesized to handle nonlinear uncertainties and external disturbances. The unknown parameters are estimated according to the full saturation difference learning strategy. As the iteration number increases, the system state can accurately track the reference signal over the whole time interval, and all signal are guaranteed to be bounded. Tank gun control servo systems iterative learning control adaptive control Electrical engineering. Electronics. Nuclear engineering Xiushan Wu verfasserin aut Qiuzhen Yan verfasserin aut Jianping Cai verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 145524-145531 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:145524-145531 https://doi.org/10.1109/ACCESS.2019.2938814 kostenfrei https://doaj.org/article/e5bd1bb471c141fb9fdfe7ed760baaec kostenfrei https://ieeexplore.ieee.org/document/8822428/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 145524-145531
allfieldsSound	10.1109/ACCESS.2019.2938814 doi (DE-627)DOAJ014522896 (DE-599)DOAJe5bd1bb471c141fb9fdfe7ed760baaec DE-627 ger DE-627 rakwb eng TK1-9971 Guangming Zhu verfasserin aut Robust Learning Control for Tank Gun Control Servo Systems Under Alignment Condition 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper proposes an adaptive learning control scheme to solve high-precision velocity tracking problem for tank gun control servo systems. Lyapunov approach is used to design the learning controller, with alignment condition used to cope with initial problem of iterative learning control. Robust control technique and adaptive learning control technique are synthesized to handle nonlinear uncertainties and external disturbances. The unknown parameters are estimated according to the full saturation difference learning strategy. As the iteration number increases, the system state can accurately track the reference signal over the whole time interval, and all signal are guaranteed to be bounded. Tank gun control servo systems iterative learning control adaptive control Electrical engineering. Electronics. Nuclear engineering Xiushan Wu verfasserin aut Qiuzhen Yan verfasserin aut Jianping Cai verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 145524-145531 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:145524-145531 https://doi.org/10.1109/ACCESS.2019.2938814 kostenfrei https://doaj.org/article/e5bd1bb471c141fb9fdfe7ed760baaec kostenfrei https://ieeexplore.ieee.org/document/8822428/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 145524-145531
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source	In IEEE Access 7(2019), Seite 145524-145531 volume:7 year:2019 pages:145524-145531
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institution	findex.gbv.de
topic_facet	Tank gun control servo systems iterative learning control adaptive control Electrical engineering. Electronics. Nuclear engineering
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authorswithroles_txt_mv	Guangming Zhu @@aut@@ Xiushan Wu @@aut@@ Qiuzhen Yan @@aut@@ Jianping Cai @@aut@@
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callnumber-first	T - Technology
author	Guangming Zhu
spellingShingle	Guangming Zhu misc TK1-9971 misc Tank gun control servo systems misc iterative learning control misc adaptive control misc Electrical engineering. Electronics. Nuclear engineering Robust Learning Control for Tank Gun Control Servo Systems Under Alignment Condition
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topic_title	TK1-9971 Robust Learning Control for Tank Gun Control Servo Systems Under Alignment Condition Tank gun control servo systems iterative learning control adaptive control
topic	misc TK1-9971 misc Tank gun control servo systems misc iterative learning control misc adaptive control misc Electrical engineering. Electronics. Nuclear engineering
topic_unstemmed	misc TK1-9971 misc Tank gun control servo systems misc iterative learning control misc adaptive control misc Electrical engineering. Electronics. Nuclear engineering
topic_browse	misc TK1-9971 misc Tank gun control servo systems misc iterative learning control misc adaptive control misc Electrical engineering. Electronics. Nuclear engineering
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title	Robust Learning Control for Tank Gun Control Servo Systems Under Alignment Condition
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title_full	Robust Learning Control for Tank Gun Control Servo Systems Under Alignment Condition
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title_sort	robust learning control for tank gun control servo systems under alignment condition
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title_auth	Robust Learning Control for Tank Gun Control Servo Systems Under Alignment Condition
abstract	This paper proposes an adaptive learning control scheme to solve high-precision velocity tracking problem for tank gun control servo systems. Lyapunov approach is used to design the learning controller, with alignment condition used to cope with initial problem of iterative learning control. Robust control technique and adaptive learning control technique are synthesized to handle nonlinear uncertainties and external disturbances. The unknown parameters are estimated according to the full saturation difference learning strategy. As the iteration number increases, the system state can accurately track the reference signal over the whole time interval, and all signal are guaranteed to be bounded.
abstractGer	This paper proposes an adaptive learning control scheme to solve high-precision velocity tracking problem for tank gun control servo systems. Lyapunov approach is used to design the learning controller, with alignment condition used to cope with initial problem of iterative learning control. Robust control technique and adaptive learning control technique are synthesized to handle nonlinear uncertainties and external disturbances. The unknown parameters are estimated according to the full saturation difference learning strategy. As the iteration number increases, the system state can accurately track the reference signal over the whole time interval, and all signal are guaranteed to be bounded.
abstract_unstemmed	This paper proposes an adaptive learning control scheme to solve high-precision velocity tracking problem for tank gun control servo systems. Lyapunov approach is used to design the learning controller, with alignment condition used to cope with initial problem of iterative learning control. Robust control technique and adaptive learning control technique are synthesized to handle nonlinear uncertainties and external disturbances. The unknown parameters are estimated according to the full saturation difference learning strategy. As the iteration number increases, the system state can accurately track the reference signal over the whole time interval, and all signal are guaranteed to be bounded.
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title_short	Robust Learning Control for Tank Gun Control Servo Systems Under Alignment Condition
url	https://doi.org/10.1109/ACCESS.2019.2938814 https://doaj.org/article/e5bd1bb471c141fb9fdfe7ed760baaec https://ieeexplore.ieee.org/document/8822428/ https://doaj.org/toc/2169-3536
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up_date	2024-07-03T23:25:27.752Z
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