Modeling and filtering for a stochastic uncertain system in a complex scenario

This paper presents a new approach to filter signals for discrete-time physical problems with stochastic uncertain in the presence of random data transmission delays, out-of-order packets and correlated noise. To deal with the packet disorder, the system model synthesizing the transmission delays an...
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Autor*in:	Li Liu [verfasserIn] Yao Tao [verfasserIn] Zhou Chunjie [verfasserIn] Liu Fei [verfasserIn] Hou Dianli [verfasserIn] Yang Hongyong [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	finite horizon filtering transmission delays out-of-order packets variational principle fractal calculus

Übergeordnetes Werk:	In: Thermal Science - VINCA Institute of Nuclear Sciences, 2006, 25(2021), 2 Part B, Seite 1411-1424
Übergeordnetes Werk:	volume:25 ; year:2021 ; number:2 Part B ; pages:1411-1424

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.2298/TSCI191201041L

Katalog-ID:	DOAJ047718226

Internformat


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520			\|a This paper presents a new approach to filter signals for discrete-time physical problems with stochastic uncertain in the presence of random data transmission delays, out-of-order packets and correlated noise. To deal with the packet disorder, the system model synthesizing the transmission delays and out-of-order packets from the plant to the filter is established by utilizing signal reconstruction schemes based on the zero-order-holder and logic zero-order-holder. A robust finite horizon Kalman filter is proposed by augmenting the state-space model and minimizing the error covariance. To further improve the filtering performance, a linear estimation-based delay compensation strategy is proposed by employing the reorganized time-stamped measurements. Moreover, for solving the missing measurement problem whilst reducing the computational costs, an artificial delay compensation approach is established using an one-step prediction approach. Simulation results show the effectiveness of the proposed method.
650		4	\|a finite horizon filtering
650		4	\|a transmission delays
650		4	\|a out-of-order packets
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650		4	\|a fractal calculus
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author_variant	l l ll y t yt z c zc l f lf h d hd y h yh
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allfields	10.2298/TSCI191201041L doi (DE-627)DOAJ047718226 (DE-599)DOAJ524b8a2fb7dd4c3894e1f6a26b9793d1 DE-627 ger DE-627 rakwb eng TJ1-1570 Li Liu verfasserin aut Modeling and filtering for a stochastic uncertain system in a complex scenario 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper presents a new approach to filter signals for discrete-time physical problems with stochastic uncertain in the presence of random data transmission delays, out-of-order packets and correlated noise. To deal with the packet disorder, the system model synthesizing the transmission delays and out-of-order packets from the plant to the filter is established by utilizing signal reconstruction schemes based on the zero-order-holder and logic zero-order-holder. A robust finite horizon Kalman filter is proposed by augmenting the state-space model and minimizing the error covariance. To further improve the filtering performance, a linear estimation-based delay compensation strategy is proposed by employing the reorganized time-stamped measurements. Moreover, for solving the missing measurement problem whilst reducing the computational costs, an artificial delay compensation approach is established using an one-step prediction approach. Simulation results show the effectiveness of the proposed method. finite horizon filtering transmission delays out-of-order packets variational principle fractal calculus Mechanical engineering and machinery Yao Tao verfasserin aut Zhou Chunjie verfasserin aut Liu Fei verfasserin aut Hou Dianli verfasserin aut Yang Hongyong verfasserin aut In Thermal Science VINCA Institute of Nuclear Sciences, 2006 25(2021), 2 Part B, Seite 1411-1424 (DE-627)514240016 (DE-600)2241319-4 23347163 nnns volume:25 year:2021 number:2 Part B pages:1411-1424 https://doi.org/10.2298/TSCI191201041L kostenfrei https://doaj.org/article/524b8a2fb7dd4c3894e1f6a26b9793d1 kostenfrei http://www.doiserbia.nb.rs/img/doi/0354-9836/2021/0354-98362100041L.pdf kostenfrei https://doaj.org/toc/0354-9836 Journal toc kostenfrei https://doaj.org/toc/2334-7163 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 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_2027 GBV_ILN_2031 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2190 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 25 2021 2 Part B 1411-1424
spelling	10.2298/TSCI191201041L doi (DE-627)DOAJ047718226 (DE-599)DOAJ524b8a2fb7dd4c3894e1f6a26b9793d1 DE-627 ger DE-627 rakwb eng TJ1-1570 Li Liu verfasserin aut Modeling and filtering for a stochastic uncertain system in a complex scenario 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper presents a new approach to filter signals for discrete-time physical problems with stochastic uncertain in the presence of random data transmission delays, out-of-order packets and correlated noise. To deal with the packet disorder, the system model synthesizing the transmission delays and out-of-order packets from the plant to the filter is established by utilizing signal reconstruction schemes based on the zero-order-holder and logic zero-order-holder. A robust finite horizon Kalman filter is proposed by augmenting the state-space model and minimizing the error covariance. To further improve the filtering performance, a linear estimation-based delay compensation strategy is proposed by employing the reorganized time-stamped measurements. Moreover, for solving the missing measurement problem whilst reducing the computational costs, an artificial delay compensation approach is established using an one-step prediction approach. Simulation results show the effectiveness of the proposed method. finite horizon filtering transmission delays out-of-order packets variational principle fractal calculus Mechanical engineering and machinery Yao Tao verfasserin aut Zhou Chunjie verfasserin aut Liu Fei verfasserin aut Hou Dianli verfasserin aut Yang Hongyong verfasserin aut In Thermal Science VINCA Institute of Nuclear Sciences, 2006 25(2021), 2 Part B, Seite 1411-1424 (DE-627)514240016 (DE-600)2241319-4 23347163 nnns volume:25 year:2021 number:2 Part B pages:1411-1424 https://doi.org/10.2298/TSCI191201041L kostenfrei https://doaj.org/article/524b8a2fb7dd4c3894e1f6a26b9793d1 kostenfrei http://www.doiserbia.nb.rs/img/doi/0354-9836/2021/0354-98362100041L.pdf kostenfrei https://doaj.org/toc/0354-9836 Journal toc kostenfrei https://doaj.org/toc/2334-7163 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 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_2027 GBV_ILN_2031 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2190 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 25 2021 2 Part B 1411-1424
allfields_unstemmed	10.2298/TSCI191201041L doi (DE-627)DOAJ047718226 (DE-599)DOAJ524b8a2fb7dd4c3894e1f6a26b9793d1 DE-627 ger DE-627 rakwb eng TJ1-1570 Li Liu verfasserin aut Modeling and filtering for a stochastic uncertain system in a complex scenario 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper presents a new approach to filter signals for discrete-time physical problems with stochastic uncertain in the presence of random data transmission delays, out-of-order packets and correlated noise. To deal with the packet disorder, the system model synthesizing the transmission delays and out-of-order packets from the plant to the filter is established by utilizing signal reconstruction schemes based on the zero-order-holder and logic zero-order-holder. A robust finite horizon Kalman filter is proposed by augmenting the state-space model and minimizing the error covariance. To further improve the filtering performance, a linear estimation-based delay compensation strategy is proposed by employing the reorganized time-stamped measurements. Moreover, for solving the missing measurement problem whilst reducing the computational costs, an artificial delay compensation approach is established using an one-step prediction approach. Simulation results show the effectiveness of the proposed method. finite horizon filtering transmission delays out-of-order packets variational principle fractal calculus Mechanical engineering and machinery Yao Tao verfasserin aut Zhou Chunjie verfasserin aut Liu Fei verfasserin aut Hou Dianli verfasserin aut Yang Hongyong verfasserin aut In Thermal Science VINCA Institute of Nuclear Sciences, 2006 25(2021), 2 Part B, Seite 1411-1424 (DE-627)514240016 (DE-600)2241319-4 23347163 nnns volume:25 year:2021 number:2 Part B pages:1411-1424 https://doi.org/10.2298/TSCI191201041L kostenfrei https://doaj.org/article/524b8a2fb7dd4c3894e1f6a26b9793d1 kostenfrei http://www.doiserbia.nb.rs/img/doi/0354-9836/2021/0354-98362100041L.pdf kostenfrei https://doaj.org/toc/0354-9836 Journal toc kostenfrei https://doaj.org/toc/2334-7163 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 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_2027 GBV_ILN_2031 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2190 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 25 2021 2 Part B 1411-1424
allfieldsGer	10.2298/TSCI191201041L doi (DE-627)DOAJ047718226 (DE-599)DOAJ524b8a2fb7dd4c3894e1f6a26b9793d1 DE-627 ger DE-627 rakwb eng TJ1-1570 Li Liu verfasserin aut Modeling and filtering for a stochastic uncertain system in a complex scenario 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper presents a new approach to filter signals for discrete-time physical problems with stochastic uncertain in the presence of random data transmission delays, out-of-order packets and correlated noise. To deal with the packet disorder, the system model synthesizing the transmission delays and out-of-order packets from the plant to the filter is established by utilizing signal reconstruction schemes based on the zero-order-holder and logic zero-order-holder. A robust finite horizon Kalman filter is proposed by augmenting the state-space model and minimizing the error covariance. To further improve the filtering performance, a linear estimation-based delay compensation strategy is proposed by employing the reorganized time-stamped measurements. Moreover, for solving the missing measurement problem whilst reducing the computational costs, an artificial delay compensation approach is established using an one-step prediction approach. Simulation results show the effectiveness of the proposed method. finite horizon filtering transmission delays out-of-order packets variational principle fractal calculus Mechanical engineering and machinery Yao Tao verfasserin aut Zhou Chunjie verfasserin aut Liu Fei verfasserin aut Hou Dianli verfasserin aut Yang Hongyong verfasserin aut In Thermal Science VINCA Institute of Nuclear Sciences, 2006 25(2021), 2 Part B, Seite 1411-1424 (DE-627)514240016 (DE-600)2241319-4 23347163 nnns volume:25 year:2021 number:2 Part B pages:1411-1424 https://doi.org/10.2298/TSCI191201041L kostenfrei https://doaj.org/article/524b8a2fb7dd4c3894e1f6a26b9793d1 kostenfrei http://www.doiserbia.nb.rs/img/doi/0354-9836/2021/0354-98362100041L.pdf kostenfrei https://doaj.org/toc/0354-9836 Journal toc kostenfrei https://doaj.org/toc/2334-7163 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 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_2027 GBV_ILN_2031 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2190 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 25 2021 2 Part B 1411-1424
allfieldsSound	10.2298/TSCI191201041L doi (DE-627)DOAJ047718226 (DE-599)DOAJ524b8a2fb7dd4c3894e1f6a26b9793d1 DE-627 ger DE-627 rakwb eng TJ1-1570 Li Liu verfasserin aut Modeling and filtering for a stochastic uncertain system in a complex scenario 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper presents a new approach to filter signals for discrete-time physical problems with stochastic uncertain in the presence of random data transmission delays, out-of-order packets and correlated noise. To deal with the packet disorder, the system model synthesizing the transmission delays and out-of-order packets from the plant to the filter is established by utilizing signal reconstruction schemes based on the zero-order-holder and logic zero-order-holder. A robust finite horizon Kalman filter is proposed by augmenting the state-space model and minimizing the error covariance. To further improve the filtering performance, a linear estimation-based delay compensation strategy is proposed by employing the reorganized time-stamped measurements. Moreover, for solving the missing measurement problem whilst reducing the computational costs, an artificial delay compensation approach is established using an one-step prediction approach. Simulation results show the effectiveness of the proposed method. finite horizon filtering transmission delays out-of-order packets variational principle fractal calculus Mechanical engineering and machinery Yao Tao verfasserin aut Zhou Chunjie verfasserin aut Liu Fei verfasserin aut Hou Dianli verfasserin aut Yang Hongyong verfasserin aut In Thermal Science VINCA Institute of Nuclear Sciences, 2006 25(2021), 2 Part B, Seite 1411-1424 (DE-627)514240016 (DE-600)2241319-4 23347163 nnns volume:25 year:2021 number:2 Part B pages:1411-1424 https://doi.org/10.2298/TSCI191201041L kostenfrei https://doaj.org/article/524b8a2fb7dd4c3894e1f6a26b9793d1 kostenfrei http://www.doiserbia.nb.rs/img/doi/0354-9836/2021/0354-98362100041L.pdf kostenfrei https://doaj.org/toc/0354-9836 Journal toc kostenfrei https://doaj.org/toc/2334-7163 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 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_2027 GBV_ILN_2031 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2190 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 25 2021 2 Part B 1411-1424
language	English
source	In Thermal Science 25(2021), 2 Part B, Seite 1411-1424 volume:25 year:2021 number:2 Part B pages:1411-1424
sourceStr	In Thermal Science 25(2021), 2 Part B, Seite 1411-1424 volume:25 year:2021 number:2 Part B pages:1411-1424
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	finite horizon filtering transmission delays out-of-order packets variational principle fractal calculus Mechanical engineering and machinery
isfreeaccess_bool	true
container_title	Thermal Science
authorswithroles_txt_mv	Li Liu @@aut@@ Yao Tao @@aut@@ Zhou Chunjie @@aut@@ Liu Fei @@aut@@ Hou Dianli @@aut@@ Yang Hongyong @@aut@@
publishDateDaySort_date	2021-01-01T00:00:00Z
hierarchy_top_id	514240016
id	DOAJ047718226
language_de	englisch
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callnumber-first	T - Technology
author	Li Liu
spellingShingle	Li Liu misc TJ1-1570 misc finite horizon filtering misc transmission delays misc out-of-order packets misc variational principle misc fractal calculus misc Mechanical engineering and machinery Modeling and filtering for a stochastic uncertain system in a complex scenario
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topic_title	TJ1-1570 Modeling and filtering for a stochastic uncertain system in a complex scenario finite horizon filtering transmission delays out-of-order packets variational principle fractal calculus
topic	misc TJ1-1570 misc finite horizon filtering misc transmission delays misc out-of-order packets misc variational principle misc fractal calculus misc Mechanical engineering and machinery
topic_unstemmed	misc TJ1-1570 misc finite horizon filtering misc transmission delays misc out-of-order packets misc variational principle misc fractal calculus misc Mechanical engineering and machinery
topic_browse	misc TJ1-1570 misc finite horizon filtering misc transmission delays misc out-of-order packets misc variational principle misc fractal calculus misc Mechanical engineering and machinery
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title	Modeling and filtering for a stochastic uncertain system in a complex scenario
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title_full	Modeling and filtering for a stochastic uncertain system in a complex scenario
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journal	Thermal Science
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author_browse	Li Liu Yao Tao Zhou Chunjie Liu Fei Hou Dianli Yang Hongyong
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title_sort	modeling and filtering for a stochastic uncertain system in a complex scenario
callnumber	TJ1-1570
title_auth	Modeling and filtering for a stochastic uncertain system in a complex scenario
abstract	This paper presents a new approach to filter signals for discrete-time physical problems with stochastic uncertain in the presence of random data transmission delays, out-of-order packets and correlated noise. To deal with the packet disorder, the system model synthesizing the transmission delays and out-of-order packets from the plant to the filter is established by utilizing signal reconstruction schemes based on the zero-order-holder and logic zero-order-holder. A robust finite horizon Kalman filter is proposed by augmenting the state-space model and minimizing the error covariance. To further improve the filtering performance, a linear estimation-based delay compensation strategy is proposed by employing the reorganized time-stamped measurements. Moreover, for solving the missing measurement problem whilst reducing the computational costs, an artificial delay compensation approach is established using an one-step prediction approach. Simulation results show the effectiveness of the proposed method.
abstractGer	This paper presents a new approach to filter signals for discrete-time physical problems with stochastic uncertain in the presence of random data transmission delays, out-of-order packets and correlated noise. To deal with the packet disorder, the system model synthesizing the transmission delays and out-of-order packets from the plant to the filter is established by utilizing signal reconstruction schemes based on the zero-order-holder and logic zero-order-holder. A robust finite horizon Kalman filter is proposed by augmenting the state-space model and minimizing the error covariance. To further improve the filtering performance, a linear estimation-based delay compensation strategy is proposed by employing the reorganized time-stamped measurements. Moreover, for solving the missing measurement problem whilst reducing the computational costs, an artificial delay compensation approach is established using an one-step prediction approach. Simulation results show the effectiveness of the proposed method.
abstract_unstemmed	This paper presents a new approach to filter signals for discrete-time physical problems with stochastic uncertain in the presence of random data transmission delays, out-of-order packets and correlated noise. To deal with the packet disorder, the system model synthesizing the transmission delays and out-of-order packets from the plant to the filter is established by utilizing signal reconstruction schemes based on the zero-order-holder and logic zero-order-holder. A robust finite horizon Kalman filter is proposed by augmenting the state-space model and minimizing the error covariance. To further improve the filtering performance, a linear estimation-based delay compensation strategy is proposed by employing the reorganized time-stamped measurements. Moreover, for solving the missing measurement problem whilst reducing the computational costs, an artificial delay compensation approach is established using an one-step prediction approach. Simulation results show the effectiveness of the proposed method.
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container_issue	2 Part B
title_short	Modeling and filtering for a stochastic uncertain system in a complex scenario
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doi_str	10.2298/TSCI191201041L
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up_date	2024-07-03T13:43:36.200Z
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Modeling and filtering for a stochastic uncertain system in a complex scenario

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