Gradient-Based Iterative Parameter Estimation Algorithms for Dynamical Systems from Observation Data

It is well-known that mathematical models are the basis for system analysis and controller design. This paper considers the parameter identification problems of stochastic systems by the controlled autoregressive model. A gradient-based iterative algorithm is derived from observation data by using t...

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Main Authors:	Feng Ding, Jian Pan, Ahmed Alsaedi, Tasawar Hayat
Format:	Article
Language:	English
Published:	MDPI AG 2019-05-01
Series:	Mathematics
Subjects:	parameter estimation iterative algorithm gradient search multi-innovation identification stochastic system
Online Access:	https://www.mdpi.com/2227-7390/7/5/428

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record_format	Article
spelling	doaj-420efabc997c4e09b9bd9c7bd3048ba72020-11-25T01:31:22ZengMDPI AGMathematics2227-73902019-05-017542810.3390/math7050428math7050428Gradient-Based Iterative Parameter Estimation Algorithms for Dynamical Systems from Observation DataFeng Ding0Jian Pan1Ahmed Alsaedi2Tasawar Hayat3School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, ChinaSchool of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, ChinaDepartment of Mathematics, King Abdulaziz University, Jeddah 21589, Saudi ArabiaDepartment of Mathematics, King Abdulaziz University, Jeddah 21589, Saudi ArabiaIt is well-known that mathematical models are the basis for system analysis and controller design. This paper considers the parameter identification problems of stochastic systems by the controlled autoregressive model. A gradient-based iterative algorithm is derived from observation data by using the gradient search. By using the multi-innovation identification theory, we propose a multi-innovation gradient-based iterative algorithm to improve the performance of the algorithm. Finally, a numerical simulation example is given to demonstrate the effectiveness of the proposed algorithms.https://www.mdpi.com/2227-7390/7/5/428parameter estimationiterative algorithmgradient searchmulti-innovation identificationstochastic system
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Feng Ding Jian Pan Ahmed Alsaedi Tasawar Hayat
spellingShingle	Feng Ding Jian Pan Ahmed Alsaedi Tasawar Hayat Gradient-Based Iterative Parameter Estimation Algorithms for Dynamical Systems from Observation Data Mathematics parameter estimation iterative algorithm gradient search multi-innovation identification stochastic system
author_facet	Feng Ding Jian Pan Ahmed Alsaedi Tasawar Hayat
author_sort	Feng Ding
title	Gradient-Based Iterative Parameter Estimation Algorithms for Dynamical Systems from Observation Data
title_short	Gradient-Based Iterative Parameter Estimation Algorithms for Dynamical Systems from Observation Data
title_full	Gradient-Based Iterative Parameter Estimation Algorithms for Dynamical Systems from Observation Data
title_fullStr	Gradient-Based Iterative Parameter Estimation Algorithms for Dynamical Systems from Observation Data
title_full_unstemmed	Gradient-Based Iterative Parameter Estimation Algorithms for Dynamical Systems from Observation Data
title_sort	gradient-based iterative parameter estimation algorithms for dynamical systems from observation data
publisher	MDPI AG
series	Mathematics
issn	2227-7390
publishDate	2019-05-01
description	It is well-known that mathematical models are the basis for system analysis and controller design. This paper considers the parameter identification problems of stochastic systems by the controlled autoregressive model. A gradient-based iterative algorithm is derived from observation data by using the gradient search. By using the multi-innovation identification theory, we propose a multi-innovation gradient-based iterative algorithm to improve the performance of the algorithm. Finally, a numerical simulation example is given to demonstrate the effectiveness of the proposed algorithms.
topic	parameter estimation iterative algorithm gradient search multi-innovation identification stochastic system
url	https://www.mdpi.com/2227-7390/7/5/428
work_keys_str_mv	AT fengding gradientbasediterativeparameterestimationalgorithmsfordynamicalsystemsfromobservationdata AT jianpan gradientbasediterativeparameterestimationalgorithmsfordynamicalsystemsfromobservationdata AT ahmedalsaedi gradientbasediterativeparameterestimationalgorithmsfordynamicalsystemsfromobservationdata AT tasawarhayat gradientbasediterativeparameterestimationalgorithmsfordynamicalsystemsfromobservationdata
_version_	1725087103251906560

Gradient-Based Iterative Parameter Estimation Algorithms for Dynamical Systems from Observation Data

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