Design and Experimental Development of Wireless Iterative Learning Fault Estimation Algorithm With Quantization and Packet Losses

In this paper, a wireless iterative learning fault estimation algorithm (WILFEA) is proposed and validated experimentally with the aim to achieve perfect tracking of a prescribed reference trajectory for systems with packet losses and quantizer measurements that operate repetitively. First, state va...

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Autores principales:	Samba Aime Herve, Yeremou Tamtsia Aurelien, Nneme Nneme Leandre, Idellette Judith Hermine Som, Houwe Alphonse
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Iterative learning algorithm quantiser measurements random packet losses fault estimation Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/207869ae09194fe1b4b41f4f6d1df56e
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id	oai:doaj.org-article:207869ae09194fe1b4b41f4f6d1df56e
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spelling	oai:doaj.org-article:207869ae09194fe1b4b41f4f6d1df56e2021-11-18T00:02:26ZDesign and Experimental Development of Wireless Iterative Learning Fault Estimation Algorithm With Quantization and Packet Losses2169-353610.1109/ACCESS.2021.3123118https://doaj.org/article/207869ae09194fe1b4b41f4f6d1df56e2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9585438/https://doaj.org/toc/2169-3536In this paper, a wireless iterative learning fault estimation algorithm (WILFEA) is proposed and validated experimentally with the aim to achieve perfect tracking of a prescribed reference trajectory for systems with packet losses and quantizer measurements that operate repetitively. First, state variables, Markov chain process of random packet losses, and a logarithmic quantizer are considered to establish an extended-state-space system model. Next, based on this model, sufficient conditions for linear repetitive processes are developed with the Lyapunov-Krasovskii technique and <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> approach is applied to calculate the observer gain and the learning gain. Then, WILFEA based fault estimation is constructed. Compared with the existing methods, the proposed WILFEA improves the fault estimation performance in the current iteration by consider both state error and fault estimation error. Finally, the simulation and experimental results are used for DC-Servomotor system to illustrate the effectiveness of the proposed approach using Matlab/simulink software, LabVIEW Software, ZigBee Xbee and Arduino board.Samba Aime HerveYeremou Tamtsia AurelienNneme Nneme LeandreIdellette Judith Hermine SomHouwe AlphonseIEEEarticleIterative learning algorithmquantiser measurementsrandom packet lossesfault estimationElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 150120-150127 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Iterative learning algorithm quantiser measurements random packet losses fault estimation Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Iterative learning algorithm quantiser measurements random packet losses fault estimation Electrical engineering. Electronics. Nuclear engineering TK1-9971 Samba Aime Herve Yeremou Tamtsia Aurelien Nneme Nneme Leandre Idellette Judith Hermine Som Houwe Alphonse Design and Experimental Development of Wireless Iterative Learning Fault Estimation Algorithm With Quantization and Packet Losses
description	In this paper, a wireless iterative learning fault estimation algorithm (WILFEA) is proposed and validated experimentally with the aim to achieve perfect tracking of a prescribed reference trajectory for systems with packet losses and quantizer measurements that operate repetitively. First, state variables, Markov chain process of random packet losses, and a logarithmic quantizer are considered to establish an extended-state-space system model. Next, based on this model, sufficient conditions for linear repetitive processes are developed with the Lyapunov-Krasovskii technique and <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> approach is applied to calculate the observer gain and the learning gain. Then, WILFEA based fault estimation is constructed. Compared with the existing methods, the proposed WILFEA improves the fault estimation performance in the current iteration by consider both state error and fault estimation error. Finally, the simulation and experimental results are used for DC-Servomotor system to illustrate the effectiveness of the proposed approach using Matlab/simulink software, LabVIEW Software, ZigBee Xbee and Arduino board.
format	article
author	Samba Aime Herve Yeremou Tamtsia Aurelien Nneme Nneme Leandre Idellette Judith Hermine Som Houwe Alphonse
author_facet	Samba Aime Herve Yeremou Tamtsia Aurelien Nneme Nneme Leandre Idellette Judith Hermine Som Houwe Alphonse
author_sort	Samba Aime Herve
title	Design and Experimental Development of Wireless Iterative Learning Fault Estimation Algorithm With Quantization and Packet Losses
title_short	Design and Experimental Development of Wireless Iterative Learning Fault Estimation Algorithm With Quantization and Packet Losses
title_full	Design and Experimental Development of Wireless Iterative Learning Fault Estimation Algorithm With Quantization and Packet Losses
title_fullStr	Design and Experimental Development of Wireless Iterative Learning Fault Estimation Algorithm With Quantization and Packet Losses
title_full_unstemmed	Design and Experimental Development of Wireless Iterative Learning Fault Estimation Algorithm With Quantization and Packet Losses
title_sort	design and experimental development of wireless iterative learning fault estimation algorithm with quantization and packet losses
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/207869ae09194fe1b4b41f4f6d1df56e
work_keys_str_mv	AT sambaaimeherve designandexperimentaldevelopmentofwirelessiterativelearningfaultestimationalgorithmwithquantizationandpacketlosses AT yeremoutamtsiaaurelien designandexperimentaldevelopmentofwirelessiterativelearningfaultestimationalgorithmwithquantizationandpacketlosses AT nnemennemeleandre designandexperimentaldevelopmentofwirelessiterativelearningfaultestimationalgorithmwithquantizationandpacketlosses AT idellettejudithherminesom designandexperimentaldevelopmentofwirelessiterativelearningfaultestimationalgorithmwithquantizationandpacketlosses AT houwealphonse designandexperimentaldevelopmentofwirelessiterativelearningfaultestimationalgorithmwithquantizationandpacketlosses
_version_	1718425212116008960

Design and Experimental Development of Wireless Iterative Learning Fault Estimation Algorithm With Quantization and Packet Losses

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