Minimal control placement of networked reaction-diffusion systems based on Turing model

In this paper, we consider the problem of placing a minimal number of controls to achieve controllability for a class of networked control systems that are based on the original Turing reaction-diffusion model, which is governed by a set of ordinary differential equations with interactions defined b...

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Main Authors: Cao, Yuexin, Li, Yibei, Zheng, Lirong, Hu, Xiaoming
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2024
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Online Access:https://hdl.handle.net/10356/181832
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1818322024-12-23T05:45:26Z Minimal control placement of networked reaction-diffusion systems based on Turing model Cao, Yuexin Li, Yibei Zheng, Lirong Hu, Xiaoming School of Electrical and Electronic Engineering Engineering Turing model Controllability of networked systems In this paper, we consider the problem of placing a minimal number of controls to achieve controllability for a class of networked control systems that are based on the original Turing reaction-diffusion model, which is governed by a set of ordinary differential equations with interactions defined by a ring graph. Turing model considers two morphogens reacting and diffusing over the spatial domain and has been widely accepted as one of the most fundamental models to explain pattern formation in a developing embryo. It is of great importance to understand the mechanism behind the various reaction kinetics that generate such a wide range of patterns. As a first step towards this goal, in this paper we study controllability of Turing model for the case of cells connected as a square grid in which controls can be applied to the boundary cells. We first investigate the minimal control placement problem for the diffusion only system. The eigenvalues of the diffusion matrix are classified by their geometric multiplicity, and the properties of the corresponding eigenspaces are studied. The symmetric control sets are designed to categorize control candidates by symmetry of the network topology. Then the necessary and sufficient condition is provided for placing the minimal control to guarantee controllability for the diffusion system. Furthermore, we show that the necessary condition can be extended to Turing model by a natural expansion of the symmetric control sets. Under certain circumstances, we prove that it is also sufficient to ensure controllability of Turing model. Nanyang Technological University This paper was partially supported by the China Scholarship Council, and by the Wallenberg Foundation Postdoctoral Fellowship at Nanyang Technological University. 2024-12-23T05:45:25Z 2024-12-23T05:45:25Z 2024 Journal Article Cao, Y., Li, Y., Zheng, L. & Hu, X. (2024). Minimal control placement of networked reaction-diffusion systems based on Turing model. SIAM Journal On Control and Optimization, 62(3), 1809-1831. https://dx.doi.org/10.1137/23M1616856 0363-0129 https://hdl.handle.net/10356/181832 10.1137/23M1616856 2-s2.0-85200923918 3 62 1809 1831 en SIAM Journal on Control and Optimization © 2024 Society for Industrial and Applied Mathematics. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
Turing model
Controllability of networked systems
spellingShingle Engineering
Turing model
Controllability of networked systems
Cao, Yuexin
Li, Yibei
Zheng, Lirong
Hu, Xiaoming
Minimal control placement of networked reaction-diffusion systems based on Turing model
description In this paper, we consider the problem of placing a minimal number of controls to achieve controllability for a class of networked control systems that are based on the original Turing reaction-diffusion model, which is governed by a set of ordinary differential equations with interactions defined by a ring graph. Turing model considers two morphogens reacting and diffusing over the spatial domain and has been widely accepted as one of the most fundamental models to explain pattern formation in a developing embryo. It is of great importance to understand the mechanism behind the various reaction kinetics that generate such a wide range of patterns. As a first step towards this goal, in this paper we study controllability of Turing model for the case of cells connected as a square grid in which controls can be applied to the boundary cells. We first investigate the minimal control placement problem for the diffusion only system. The eigenvalues of the diffusion matrix are classified by their geometric multiplicity, and the properties of the corresponding eigenspaces are studied. The symmetric control sets are designed to categorize control candidates by symmetry of the network topology. Then the necessary and sufficient condition is provided for placing the minimal control to guarantee controllability for the diffusion system. Furthermore, we show that the necessary condition can be extended to Turing model by a natural expansion of the symmetric control sets. Under certain circumstances, we prove that it is also sufficient to ensure controllability of Turing model.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Cao, Yuexin
Li, Yibei
Zheng, Lirong
Hu, Xiaoming
format Article
author Cao, Yuexin
Li, Yibei
Zheng, Lirong
Hu, Xiaoming
author_sort Cao, Yuexin
title Minimal control placement of networked reaction-diffusion systems based on Turing model
title_short Minimal control placement of networked reaction-diffusion systems based on Turing model
title_full Minimal control placement of networked reaction-diffusion systems based on Turing model
title_fullStr Minimal control placement of networked reaction-diffusion systems based on Turing model
title_full_unstemmed Minimal control placement of networked reaction-diffusion systems based on Turing model
title_sort minimal control placement of networked reaction-diffusion systems based on turing model
publishDate 2024
url https://hdl.handle.net/10356/181832
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