Mixed Unscented Kalman Filter and differential evolution for parameter identification

This paper presents parameters estimation techniques for coupled industrial tanks using the mixed Unscented Kalman Filter (UKF) and Differential Evolution (DE) method. UKF have known to be a typical estimation technique used to estimate the state vectors and parameters of nonlinear dynamical syst...

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Main Authors:	Legowo, Ari, Mohamad, Zahratu H., Park, HoonCheol
Format:	Article
Language:	English
Published:	Trans Tech Publications 2013
Subjects:	TJ212 Control engineering
Online Access:	http://irep.iium.edu.my/27209/ http://irep.iium.edu.my/27209/ http://irep.iium.edu.my/27209/ http://irep.iium.edu.my/27209/1/AMM.256-259.2347_Journal.pdf

id	iium-27209
recordtype	eprints
spelling	iium-272092013-08-02T00:53:19Z http://irep.iium.edu.my/27209/ Mixed Unscented Kalman Filter and differential evolution for parameter identification Legowo, Ari Mohamad, Zahratu H. Park, HoonCheol TJ212 Control engineering This paper presents parameters estimation techniques for coupled industrial tanks using the mixed Unscented Kalman Filter (UKF) and Differential Evolution (DE) method. UKF have known to be a typical estimation technique used to estimate the state vectors and parameters of nonlinear dynamical systems and DE is one of the most powerful stochastic real-parameter optimization algorithms. Meanwhile, liquid tank systems play important role in industrial application such as in food processing, beverage, dairy, filtration, effluent treatment, pharmaceutical industry, water purification system, industrial chemical processing and spray coating. The aim is to model the coupled tank system using mixed UKF and DE method to estimate the parameters of the tank. First, a non-linear mathematical model is developed. Next, its parameters are identified using mixed Unscented Kalman Filter (UKF) and Differential Evolution (DE) based on the experimental data. DE algorithm is integrated into the UKF algorithm to optimize the Kalman gain obtained. The obtained results demonstrate good performances. Trans Tech Publications 2013 Article PeerReviewed application/pdf en http://irep.iium.edu.my/27209/1/AMM.256-259.2347_Journal.pdf Legowo, Ari and Mohamad, Zahratu H. and Park, HoonCheol (2013) Mixed Unscented Kalman Filter and differential evolution for parameter identification. Applied Mechanics and Materials, 256 (1). pp. 2347-2353. ISSN 1660-9336 http://www.scientific.net/AMM.256-259.2347 10.4028/www.scientific.net/AMM.256-259.2347
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	TJ212 Control engineering
spellingShingle	TJ212 Control engineering Legowo, Ari Mohamad, Zahratu H. Park, HoonCheol Mixed Unscented Kalman Filter and differential evolution for parameter identification
description	This paper presents parameters estimation techniques for coupled industrial tanks using the mixed Unscented Kalman Filter (UKF) and Differential Evolution (DE) method. UKF have known to be a typical estimation technique used to estimate the state vectors and parameters of nonlinear dynamical systems and DE is one of the most powerful stochastic real-parameter optimization algorithms. Meanwhile, liquid tank systems play important role in industrial application such as in food processing, beverage, dairy, filtration, effluent treatment, pharmaceutical industry, water purification system, industrial chemical processing and spray coating. The aim is to model the coupled tank system using mixed UKF and DE method to estimate the parameters of the tank. First, a non-linear mathematical model is developed. Next, its parameters are identified using mixed Unscented Kalman Filter (UKF) and Differential Evolution (DE) based on the experimental data. DE algorithm is integrated into the UKF algorithm to optimize the Kalman gain obtained. The obtained results demonstrate good performances.
format	Article
author	Legowo, Ari Mohamad, Zahratu H. Park, HoonCheol
author_facet	Legowo, Ari Mohamad, Zahratu H. Park, HoonCheol
author_sort	Legowo, Ari
title	Mixed Unscented Kalman Filter and differential evolution for parameter identification
title_short	Mixed Unscented Kalman Filter and differential evolution for parameter identification
title_full	Mixed Unscented Kalman Filter and differential evolution for parameter identification
title_fullStr	Mixed Unscented Kalman Filter and differential evolution for parameter identification
title_full_unstemmed	Mixed Unscented Kalman Filter and differential evolution for parameter identification
title_sort	mixed unscented kalman filter and differential evolution for parameter identification
publisher	Trans Tech Publications
publishDate	2013
url	http://irep.iium.edu.my/27209/ http://irep.iium.edu.my/27209/ http://irep.iium.edu.my/27209/ http://irep.iium.edu.my/27209/1/AMM.256-259.2347_Journal.pdf
first_indexed	2023-09-18T20:40:28Z
last_indexed	2023-09-18T20:40:28Z
_version_	1777409330751995904

Mixed Unscented Kalman Filter and differential evolution for parameter identification

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