系统辨识: 新的模式、挑战及机遇

王乐一; 赵文虓

doi:10.3724/SP.J.1004.2013.00933

系统辨识: 新的模式、挑战及机遇

doi: 10.3724/SP.J.1004.2013.00933

王乐一^1, ,,
赵文虓²

1.
美国韦恩州立大学电气与计算机工程系底特律密歇根州 48202 美国;
2.
中国科学院数学与系统科学研究院北京 100190 中国

基金项目:

国家自然科学基金(61134013, 61104052, 61273193)资助

详细信息

通讯作者:
王乐一

计量
- 文章访问数: 3182
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- 被引次数: 0
出版历程
- 收稿日期: 2012-07-04
- 修回日期: 2012-11-07
- 刊出日期: 2013-07-20

System Identification: New Paradigms, Challenges, and Opportunities

WANG Le-Yi^{1
, ,},
ZHAO Wen-Xiao²

1.
Department of Electrical and Computer Engineering, Wayne State University, Detroit, Michigan 48202, USA;
2.
Institute of Systems Science, Chinese Academy of Sciences, Beijing 100190, China

Funds:

Supported by National Natural Science Foundation of China (61134013, 61104052, 61273193)

摘要

摘要: 钱学森教授曾对系统给出一个简明的定义: 系统是指依一定秩序相互联系的一组事物. 一般说来, 系统辨识可以认为是利用已知先验信息和输入-输出数据来建立系统数学模型的科学. 经过半个多世纪的发展, 系统辨识已成为一个定义较为明确、发展相当成熟的研究领域, 在思想方法、理论基础、实际应用等诸多方面都有丰富的研究成果. 进入新世纪, 伴随着科学技术的突飞猛进, 新学科、新研究领域不断涌现, 给传统的系统辨识带来了新的挑战与机遇. 因而, 从这个角度说, 系统辨识仍是一个年轻的、朝气蓬勃的学科. 本文将讨论系统辨识在新机遇下一些具有潜力的重要方向, 提出一些值得关注的热点问题, 以此为楔入点, 抛砖引玉, 希望能引发进一步的讨论.
- 系统辨识 /
- 不确定性 /
- 信息 /
- 复杂性 /
- 网络系统 /
- 大数据处理 /
- 辨识与决策的结合
Abstract: The traditional paradigm of system identification employs prior information on system structures and environments and input/output observation data to derive system models. Extensive research and development on its methodologies, theoretical foundation, algorithms, verifications, and applications over the past half century have established a mature field with a rich literature and substantial benchmark applications. However, rapid advancement in science, technology, engineering, and social medias has ushered in a new era of systems science and control in which challenges and opportunities are abundant for system identification. In this sense, system identification remains an exciting, young, viable, and critical field that mandates new paradigms to meet such challenges. This article points out some potentially important aspects of system identification in these new paradigms, suggests some worthy areas of research focus, and most importantly opens the forum for further discussions.
- System identification /
- uncertainty /
- information /
- complexity /
- networked system /
- large data processing /
- integration of identification and decision

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