Compensation of Data Loss Using ARMAX Model in State Estimation for Control and Communication Systems Applications

Compensation of data loss in the state estimation plays an indispensable role in efficient and stable control and communication systems. However, accurate compensation of data loss in the state estimation is extremely challenging issue. To cater this challenging issue, two techniques such as the ope...

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Autores principales:	Syed Abuzar Bacha, Gulzar Ahmad, Ghulam Hafeez, Fahad R. Albogamy, Sadia Murawwat
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	autoregressive moving average with exogenous input model Kalman filter linear prediction theory loss of observation open-loop estimation closed-loop estimation Technology T
Acceso en línea:	https://doaj.org/article/6e5d43ebe6324f5aa8060b76a7e6dada
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spelling	oai:doaj.org-article:6e5d43ebe6324f5aa8060b76a7e6dada2021-11-25T17:26:51ZCompensation of Data Loss Using ARMAX Model in State Estimation for Control and Communication Systems Applications10.3390/en142275731996-1073https://doaj.org/article/6e5d43ebe6324f5aa8060b76a7e6dada2021-11-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/22/7573https://doaj.org/toc/1996-1073Compensation of data loss in the state estimation plays an indispensable role in efficient and stable control and communication systems. However, accurate compensation of data loss in the state estimation is extremely challenging issue. To cater this challenging issue, two techniques such as the open-loop Kalman filter and the compensating closed-loop Kalman filter have emerged. The closed-loop technique compensates for the missing data using the autoregressive model. However, the autoregressive model used only past measurements for data loss compensation. Considering only one parameter, i.e., the past measurements, is insufficient and leads to inaccurate state estimation. Thus, in this work, autoregressive moving average with exogenous inputs model considers three parameters, i.e., the past measurements, the input signal, and the sensor noise, simultaneously to compensate data loss in state estimation. To endorse the effectiveness and applicability of the proposed model, a standard mass-spring-damper is employed in the case study. Simulation results show that the proposed model outperforms the existing autoregressive models in terms of performance parameters.Syed Abuzar BachaGulzar AhmadGhulam HafeezFahad R. AlbogamySadia MurawwatMDPI AGarticleautoregressive moving average with exogenous input modelKalman filterlinear prediction theoryloss of observationopen-loop estimationclosed-loop estimationTechnologyTENEnergies, Vol 14, Iss 7573, p 7573 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	autoregressive moving average with exogenous input model Kalman filter linear prediction theory loss of observation open-loop estimation closed-loop estimation Technology T
spellingShingle	autoregressive moving average with exogenous input model Kalman filter linear prediction theory loss of observation open-loop estimation closed-loop estimation Technology T Syed Abuzar Bacha Gulzar Ahmad Ghulam Hafeez Fahad R. Albogamy Sadia Murawwat Compensation of Data Loss Using ARMAX Model in State Estimation for Control and Communication Systems Applications
description	Compensation of data loss in the state estimation plays an indispensable role in efficient and stable control and communication systems. However, accurate compensation of data loss in the state estimation is extremely challenging issue. To cater this challenging issue, two techniques such as the open-loop Kalman filter and the compensating closed-loop Kalman filter have emerged. The closed-loop technique compensates for the missing data using the autoregressive model. However, the autoregressive model used only past measurements for data loss compensation. Considering only one parameter, i.e., the past measurements, is insufficient and leads to inaccurate state estimation. Thus, in this work, autoregressive moving average with exogenous inputs model considers three parameters, i.e., the past measurements, the input signal, and the sensor noise, simultaneously to compensate data loss in state estimation. To endorse the effectiveness and applicability of the proposed model, a standard mass-spring-damper is employed in the case study. Simulation results show that the proposed model outperforms the existing autoregressive models in terms of performance parameters.
format	article
author	Syed Abuzar Bacha Gulzar Ahmad Ghulam Hafeez Fahad R. Albogamy Sadia Murawwat
author_facet	Syed Abuzar Bacha Gulzar Ahmad Ghulam Hafeez Fahad R. Albogamy Sadia Murawwat
author_sort	Syed Abuzar Bacha
title	Compensation of Data Loss Using ARMAX Model in State Estimation for Control and Communication Systems Applications
title_short	Compensation of Data Loss Using ARMAX Model in State Estimation for Control and Communication Systems Applications
title_full	Compensation of Data Loss Using ARMAX Model in State Estimation for Control and Communication Systems Applications
title_fullStr	Compensation of Data Loss Using ARMAX Model in State Estimation for Control and Communication Systems Applications
title_full_unstemmed	Compensation of Data Loss Using ARMAX Model in State Estimation for Control and Communication Systems Applications
title_sort	compensation of data loss using armax model in state estimation for control and communication systems applications
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/6e5d43ebe6324f5aa8060b76a7e6dada
work_keys_str_mv	AT syedabuzarbacha compensationofdatalossusingarmaxmodelinstateestimationforcontrolandcommunicationsystemsapplications AT gulzarahmad compensationofdatalossusingarmaxmodelinstateestimationforcontrolandcommunicationsystemsapplications AT ghulamhafeez compensationofdatalossusingarmaxmodelinstateestimationforcontrolandcommunicationsystemsapplications AT fahadralbogamy compensationofdatalossusingarmaxmodelinstateestimationforcontrolandcommunicationsystemsapplications AT sadiamurawwat compensationofdatalossusingarmaxmodelinstateestimationforcontrolandcommunicationsystemsapplications
_version_	1718412355497361408

Compensation of Data Loss Using ARMAX Model in State Estimation for Control and Communication Systems Applications

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