AI赋能基于模型的系统工程研究现状与展望

doi:10.12305/j.issn.1001-506X.2025.12.21

系统工程与电子技术 ›› 2025, Vol. 47 ›› Issue (12): 3966-3980.doi: 10.12305/j.issn.1001-506X.2025.12.21

• “基于模型的系统架构设计与验证技术”专栏 • 上一篇

AI赋能基于模型的系统工程研究现状与展望

宋则隆, 陈瑾, 周诠, 谭一凡, 赵嘉熙, 郑晓晨

南方科技大学自动化与智能制造学院，广东深圳 518055

收稿日期:2025-01-08 修回日期:2025-03-28 出版日期:2025-07-08 发布日期:2025-07-08
通讯作者: 郑晓晨
作者简介:宋则隆（1999—），男，博士研究生，主要研究方向为基于模型的系统工程、AI4MBSE、认知数字孪生
陈　瑾（2003—），女，主要研究方向为基于模型的系统工程、智能制造
周　诠（2004—），男，主要研究方向为基于模型的系统工程、智能制造
谭一凡（2001—），男，硕士研究生，主要研究方向为基于大模型的需求分析、基于模型的系统工程、数字孪生及认知数字孪生
赵嘉熙（2001—），男，硕士研究生，主要研究方向为基于模型的系统工程、工业数字孪生
基金资助:
深圳市自然科学基金（JCYJ20240813100906009）；广东省自然科学基金（2025A1515011490）；广东省全驱系统控制理论与技术重点实验室项目（2024B1212010002）资助课题

Current state and prospects of research on AI for model-based systems engineering

Zelong SONG, Jin CHEN, Quan ZHOU, Yifan TAN, Jiaxi ZHAO, Xiaochen ZHENG

School of Automation and Intelligent Manufacturing，Southern University of Science and Technology，Shenzhen 518055，China

Received:2025-01-08 Revised:2025-03-28 Online:2025-07-08 Published:2025-07-08
Contact: Xiaochen ZHENG

摘要/Abstract

摘要：

随着科学技术的高速发展，现代产品和系统的复杂度大幅增加，导致设计信息量呈爆炸式增长，为复杂系统下的基于模型的系统工程（model-based systems engineering, MBSE）带来了巨大挑战。人工智能（artificial intelligence, AI）为这一问题提供了可行的解决方案。然而，AI赋能MBSE（AI for MBSE, AI4MBSE）概念自提出以来尚未经过相关综述研究。为了探讨AI4MBSE的研究现状并提出展望，总结了MBSE和AI的发展概况，介绍AI4MBSE的概念，利用相关数据库检索近6年与AI4MBSE相关的文献，分析并汇总AI4MBSE的研究现状与关键技术，最后提出AI4MBSE的研究空白、研究展望和未来研究趋势。本文对AI4MBSE的发展有一定推动作用，对提升MBSE自动化、数字化与智能化水平具有重要意义。

关键词: 基于模型的系统工程, 人工智能, AI赋能MBSE

Abstract:

With the rapid advancement of science and technology, the complexity of modern products and systems increases significantly, resulting in an exponential growth of design information, and posing significant challenges for model-based systems engineering （MBSE） in complex systems. Artificial intelligence （AI） offers a viable solution to these challenges. However, the concept of AI for MBSE （AI4MBSE） is not reviewed since its inception. To explore the current state of research on AI4MBSE and to provide prospects, the development overview of MBSE and AI is summarized, and the concept of AI4MBSE is introduced. Then, the current state and key technologies of research on AI4MBSE are analyzed and summarized by searching for literature related to AI4MBSE from relevant databases over the past six years. Finally, the research gaps, research prospects and future research trends of AI4MBSE are presented. This paper has certain contributes to the development of AI4MBSE and is of significant importance for enhancing the automation, digitization, and intelligence levels of MBSE.

Key words: model-based systems engineering （MBSE）, artificial intelligence （AI）, AI for MBSE （AI4MBSE）

中图分类号:

N 945

宋则隆, 陈瑾, 周诠, 谭一凡, 赵嘉熙, 郑晓晨. AI赋能基于模型的系统工程研究现状与展望[J]. 系统工程与电子技术, 2025, 47(12): 3966-3980.

Zelong SONG, Jin CHEN, Quan ZHOU, Yifan TAN, Jiaxi ZHAO, Xiaochen ZHENG. Current state and prospects of research on AI for model-based systems engineering[J]. Systems Engineering and Electronics, 2025, 47(12): 3966-3980.

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AI相关检索词	MBSE相关检索词
人工智能和AI	基于模型的系统工程和MBSE
机器学习	系统建模语言和SysML
深度学习	—
知识图谱	—
NLP	—
LLM	—

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AI赋能基于模型的系统工程研究现状与展望

Current state and prospects of research on AI for model-based systems engineering

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