{"title":"基于图灵模型的网络反应扩散系统的最小控制布局","authors":"Yuexin Cao, Yibei Li, Lirong Zheng, Xiaoming Hu","doi":"10.1137/23m1616856","DOIUrl":null,"url":null,"abstract":"SIAM Journal on Control and Optimization, Volume 62, Issue 3, Page 1809-1831, June 2024. <br/> 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.","PeriodicalId":49531,"journal":{"name":"SIAM Journal on Control and Optimization","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Minimal Control Placement of Networked Reaction-Diffusion Systems Based on Turing Model\",\"authors\":\"Yuexin Cao, Yibei Li, Lirong Zheng, Xiaoming Hu\",\"doi\":\"10.1137/23m1616856\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"SIAM Journal on Control and Optimization, Volume 62, Issue 3, Page 1809-1831, June 2024. <br/> 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.\",\"PeriodicalId\":49531,\"journal\":{\"name\":\"SIAM Journal on Control and Optimization\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SIAM Journal on Control and Optimization\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1137/23m1616856\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIAM Journal on Control and Optimization","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1137/23m1616856","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Minimal Control Placement of Networked Reaction-Diffusion Systems Based on Turing Model
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.
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.