Design of an Optimized GMV Controller Based on Data-Driven Approach

This paper presents a data-driven scheme that can obtain the optimized Generalized Minimum Variance (GMV) control parameters by applying the Nelder–Mead (NM) method based on Proportional-Integral Derivative (PID) controller for linear system. An adjustable λ is included in the GMV-PID controller. In...

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Autores principales:	Liying Shi, Zhe Guan, Toru Yamamoto
Formato:	article
Lenguaje:	EN
Publicado:	Atlantis Press 2021
Materias:	PID controller GMV Nelder–Mead method data-driven approach Technology T
Acceso en línea:	https://doaj.org/article/8fd8278392ce4c06ba118c126135436f
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spelling	oai:doaj.org-article:8fd8278392ce4c06ba118c126135436f2021-11-19T07:45:36ZDesign of an Optimized GMV Controller Based on Data-Driven Approach10.2991/jrnal.k.210922.0061259613812352-6386https://doaj.org/article/8fd8278392ce4c06ba118c126135436f2021-10-01T00:00:00Zhttps://www.atlantis-press.com/article/125961381/viewhttps://doaj.org/toc/2352-6386This paper presents a data-driven scheme that can obtain the optimized Generalized Minimum Variance (GMV) control parameters by applying the Nelder–Mead (NM) method based on Proportional-Integral Derivative (PID) controller for linear system. An adjustable λ is included in the GMV-PID controller. In the existing GMV-PID controller, the PID parameters are calculated by simply changing λ manually. Therefore, it is hard to get desirable control performance. The NM method is introduced to improve the control performance. The application of NM method can optimize the calculation of λ. However, the objective function in NM method needs the output calculation. In other words, the model information is inevitably to obtain output. To achieve model-free design scheme, the estimation of closed-loop response method is introduced in database-driven approach. Using obtained closed-loop data can predict the output and then substitute it into the objective function without any model information of the process. The effectiveness is verified by experiment.Liying ShiZhe GuanToru YamamotoAtlantis PressarticlePID controllerGMVNelder–Mead methoddata-driven approachTechnologyTENJournal of Robotics, Networking and Artificial Life (JRNAL), Vol 8, Iss 3 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	PID controller GMV Nelder–Mead method data-driven approach Technology T
spellingShingle	PID controller GMV Nelder–Mead method data-driven approach Technology T Liying Shi Zhe Guan Toru Yamamoto Design of an Optimized GMV Controller Based on Data-Driven Approach
description	This paper presents a data-driven scheme that can obtain the optimized Generalized Minimum Variance (GMV) control parameters by applying the Nelder–Mead (NM) method based on Proportional-Integral Derivative (PID) controller for linear system. An adjustable λ is included in the GMV-PID controller. In the existing GMV-PID controller, the PID parameters are calculated by simply changing λ manually. Therefore, it is hard to get desirable control performance. The NM method is introduced to improve the control performance. The application of NM method can optimize the calculation of λ. However, the objective function in NM method needs the output calculation. In other words, the model information is inevitably to obtain output. To achieve model-free design scheme, the estimation of closed-loop response method is introduced in database-driven approach. Using obtained closed-loop data can predict the output and then substitute it into the objective function without any model information of the process. The effectiveness is verified by experiment.
format	article
author	Liying Shi Zhe Guan Toru Yamamoto
author_facet	Liying Shi Zhe Guan Toru Yamamoto
author_sort	Liying Shi
title	Design of an Optimized GMV Controller Based on Data-Driven Approach
title_short	Design of an Optimized GMV Controller Based on Data-Driven Approach
title_full	Design of an Optimized GMV Controller Based on Data-Driven Approach
title_fullStr	Design of an Optimized GMV Controller Based on Data-Driven Approach
title_full_unstemmed	Design of an Optimized GMV Controller Based on Data-Driven Approach
title_sort	design of an optimized gmv controller based on data-driven approach
publisher	Atlantis Press
publishDate	2021
url	https://doaj.org/article/8fd8278392ce4c06ba118c126135436f
work_keys_str_mv	AT liyingshi designofanoptimizedgmvcontrollerbasedondatadrivenapproach AT zheguan designofanoptimizedgmvcontrollerbasedondatadrivenapproach AT toruyamamoto designofanoptimizedgmvcontrollerbasedondatadrivenapproach
_version_	1718420272796663808

Design of an Optimized GMV Controller Based on Data-Driven Approach

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