Minimal Control Placement of Networked Reaction-Diffusion Systems Based on Turing Model

IF 2.2 2区 数学 Q2 AUTOMATION & CONTROL SYSTEMS SIAM Journal on Control and Optimization Pub Date : 2024-06-24 DOI:10.1137/23m1616856
Yuexin Cao, Yibei Li, Lirong Zheng, Xiaoming Hu
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Abstract

SIAM Journal on Control and Optimization, Volume 62, Issue 3, Page 1809-1831, June 2024.
Abstract. 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.
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基于图灵模型的网络反应扩散系统的最小控制布局
SIAM 控制与优化期刊》第 62 卷第 3 期第 1809-1831 页,2024 年 6 月。 摘要图灵反应-扩散模型由一组常微分方程控制,其相互作用由环形图定义。图灵模型考虑了两种形态发生反应并在空间域扩散的情况,被广泛认为是解释发育中胚胎模式形成的最基本模型之一。了解产生如此广泛模式的各种反应动力学背后的机制非常重要。作为实现这一目标的第一步,我们在本文中研究了图灵模型的可控性,即细胞连接成方形网格的情况,其中可对边界细胞施加控制。我们首先研究了仅扩散系统的最小控制位置问题。根据几何多重性对扩散矩阵的特征值进行分类,并研究相应特征空间的特性。设计了对称控制集,根据网络拓扑的对称性对控制候选集进行分类。然后提供了放置最小控制以保证扩散系统可控性的必要条件和充分条件。此外,我们还证明了必要条件可以通过对称控制集的自然扩展扩展到图灵模型。在某些情况下,我们证明这也足以保证图灵模型的可控性。
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来源期刊
CiteScore
4.00
自引率
4.50%
发文量
143
审稿时长
12 months
期刊介绍: SIAM Journal on Control and Optimization (SICON) publishes original research articles on the mathematics and applications of control theory and certain parts of optimization theory. Papers considered for publication must be significant at both the mathematical level and the level of applications or potential applications. Papers containing mostly routine mathematics or those with no discernible connection to control and systems theory or optimization will not be considered for publication. From time to time, the journal will also publish authoritative surveys of important subject areas in control theory and optimization whose level of maturity permits a clear and unified exposition. The broad areas mentioned above are intended to encompass a wide range of mathematical techniques and scientific, engineering, economic, and industrial applications. These include stochastic and deterministic methods in control, estimation, and identification of systems; modeling and realization of complex control systems; the numerical analysis and related computational methodology of control processes and allied issues; and the development of mathematical theories and techniques that give new insights into old problems or provide the basis for further progress in control theory and optimization. Within the field of optimization, the journal focuses on the parts that are relevant to dynamic and control systems. Contributions to numerical methodology are also welcome in accordance with these aims, especially as related to large-scale problems and decomposition as well as to fundamental questions of convergence and approximation.
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