A methodology to improve simulation of multibody systems using estimation techniques

This paper presents a methodology for state estimation and accuracy improvement of computer simulations of computer aided engineering (CAE) models based on prediction and correction state estimation techniques and sensing. The aim is to simulate the dynamic behaviour of a real system, which can be s...

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Autores principales:	Carlos Cuesta, Pablo Luque, Daniel A. Mantaras
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2022
Materias:	state estimation cae model multibody Control engineering systems. Automatic machinery (General) TJ212-225 Automation T59.5
Acceso en línea:	https://doaj.org/article/517e0c797aa549f7a1f35665aac23a13
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spelling	oai:doaj.org-article:517e0c797aa549f7a1f35665aac23a132021-12-01T14:40:58ZA methodology to improve simulation of multibody systems using estimation techniques0005-11441848-338010.1080/00051144.2021.1999129https://doaj.org/article/517e0c797aa549f7a1f35665aac23a132022-01-01T00:00:00Zhttp://dx.doi.org/10.1080/00051144.2021.1999129https://doaj.org/toc/0005-1144https://doaj.org/toc/1848-3380This paper presents a methodology for state estimation and accuracy improvement of computer simulations of computer aided engineering (CAE) models based on prediction and correction state estimation techniques and sensing. The aim is to simulate the dynamic behaviour of a real system, which can be sensed, and obtain values of states that are not measurable due to economic or technical limitations. This methodology can be applied to both optimization of design processes and on-line control of complex systems. State estimation techniques are currently used only on mathematical models, where the relationships among system variables are expressed by means of mathematical language, making state observer implementation possible but leading to limitations in system modelling and knowledge. Favoured over mathematical models, multibody CAE models (created by means of computer-aided engineering software) have become the essential tool for complex system development, simulation, analysis, optimization and control, such as multibody systems; one of their main advantages is the ease and flexibility in creating and modifying them, allowing the faithful modelling of complex systems.Carlos CuestaPablo LuqueDaniel A. MantarasTaylor & Francis Grouparticlestate estimationcae modelmultibodyControl engineering systems. Automatic machinery (General)TJ212-225AutomationT59.5ENAutomatika, Vol 63, Iss 1, Pp 16-25 (2022)
institution	DOAJ
collection	DOAJ
language	EN
topic	state estimation cae model multibody Control engineering systems. Automatic machinery (General) TJ212-225 Automation T59.5
spellingShingle	state estimation cae model multibody Control engineering systems. Automatic machinery (General) TJ212-225 Automation T59.5 Carlos Cuesta Pablo Luque Daniel A. Mantaras A methodology to improve simulation of multibody systems using estimation techniques
description	This paper presents a methodology for state estimation and accuracy improvement of computer simulations of computer aided engineering (CAE) models based on prediction and correction state estimation techniques and sensing. The aim is to simulate the dynamic behaviour of a real system, which can be sensed, and obtain values of states that are not measurable due to economic or technical limitations. This methodology can be applied to both optimization of design processes and on-line control of complex systems. State estimation techniques are currently used only on mathematical models, where the relationships among system variables are expressed by means of mathematical language, making state observer implementation possible but leading to limitations in system modelling and knowledge. Favoured over mathematical models, multibody CAE models (created by means of computer-aided engineering software) have become the essential tool for complex system development, simulation, analysis, optimization and control, such as multibody systems; one of their main advantages is the ease and flexibility in creating and modifying them, allowing the faithful modelling of complex systems.
format	article
author	Carlos Cuesta Pablo Luque Daniel A. Mantaras
author_facet	Carlos Cuesta Pablo Luque Daniel A. Mantaras
author_sort	Carlos Cuesta
title	A methodology to improve simulation of multibody systems using estimation techniques
title_short	A methodology to improve simulation of multibody systems using estimation techniques
title_full	A methodology to improve simulation of multibody systems using estimation techniques
title_fullStr	A methodology to improve simulation of multibody systems using estimation techniques
title_full_unstemmed	A methodology to improve simulation of multibody systems using estimation techniques
title_sort	methodology to improve simulation of multibody systems using estimation techniques
publisher	Taylor & Francis Group
publishDate	2022
url	https://doaj.org/article/517e0c797aa549f7a1f35665aac23a13
work_keys_str_mv	AT carloscuesta amethodologytoimprovesimulationofmultibodysystemsusingestimationtechniques AT pabloluque amethodologytoimprovesimulationofmultibodysystemsusingestimationtechniques AT danielamantaras amethodologytoimprovesimulationofmultibodysystemsusingestimationtechniques AT carloscuesta methodologytoimprovesimulationofmultibodysystemsusingestimationtechniques AT pabloluque methodologytoimprovesimulationofmultibodysystemsusingestimationtechniques AT danielamantaras methodologytoimprovesimulationofmultibodysystemsusingestimationtechniques
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A methodology to improve simulation of multibody systems using estimation techniques

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