Identification of a class of singular Boolean control networks

IF 8.1 1区计算机科学 0 COMPUTER SCIENCE, INFORMATION SYSTEMS

Information Sciences Pub Date : 2024-11-08 DOI:10.1016/j.ins.2024.121627

Rong Zhao , Jun-e Feng , Qingchun Meng , Biao Wang

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引用次数: 0

Abstract

System identification, recognized as an inverse control problem, is a significant aspect of modern control theory. This study focuses on addressing the identification problem related to a specific category of singular Boolean networks (SBNs) and singular Boolean control networks (SBCNs). The introduction of two novel concepts, namely the admissibility and solvability matrices, enables the establishment of conditions for determining the existence and uniqueness of solutions for SBNs and SBCNs. Then criteria are deduced to identify the number of dynamic equations. Based on observability, controllability and detectability, several conditions are presented to characterize identification. Among them, two crucial results show: When the solution to an SBN or SBCN is unique, the SBN is identifiable if and only if it is observable, and the SBCN is identifiable if and only if it is O1-observable, which is the most general type of observability. Besides, effective algorithms are devised to implement identification. Furthermore, the study delves into the normalization issue using the admissibility matrix, which provides a possibility to reduce the identified SBN or SBCN to a lower-order BN or BCN.

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一类奇异布尔控制网络的识别

系统辨识被视为逆控制问题，是现代控制理论的一个重要方面。本研究侧重于解决与奇异布尔网络（SBN）和奇异布尔控制网络（SBCN）的特定类别相关的识别问题。通过引入两个新概念，即可接受性矩阵和可解性矩阵，建立了确定 SBN 和 SBCN 解的存在性和唯一性的条件。然后推导出确定动态方程数量的标准。在可观测性、可控性和可探测性的基础上，提出了几个条件来描述识别。其中有两个关键结果：当 SBN 或 SBCN 的解是唯一的时，只有当 SBN 是可观测的时，它才是可识别的；只有当 SBCN 是 O1-observable 时，它才是可识别的，而 O1-observable 是最一般的可观测类型。此外，还设计了有效的算法来实现识别。此外，研究还利用可接纳矩阵深入探讨了归一化问题，这为将已识别的 SBN 或 SBCN 简化为低阶 BN 或 BCN 提供了可能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Information Sciences 工程技术-计算机：信息系统

CiteScore

14.00

自引率

17.30%

发文量

1322

审稿时长

10.4 months

期刊介绍： Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions. Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.