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Proceedings of the 17th International Conference on Modelling, Identification and Control (ICMIC2025)

Volume II

  • Conference proceedings
  • May 2026

Overview

Editors:
  1. Tingli Su

    1. Beijing Technology and Business University, Beijing, China

  2. Ning Sheng

    1. Qingdao University of Science and Technology, Qingdao, China

  3. Qiang Chen

    1. Zhejiang University of Technology, Hangzhou, China

  4. Weicun Zhang

    1. University of Science and Technology Beijing, Beijing, China

  • Presents the proceedings of the 17th International Conference on Modelling, Identification and Control (ICMIC2025)
  • Covers a range of emerging topics in modelling, identification, and control, integrated with AI
  • Applicable across virtually all engineering domains, it will appeal to a broad and diverse readership

Part of the book series: Lecture Notes in Electrical Engineering (LNEE, volume 1496)

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About this book

This book includes original, peer-reviewed research papers from the 17th International Conference on Modelling, Identification and Control (ICMIC2025), held in Qingdao, Shandong, China on June 13-15, 2025. The topics covered include but are not limited to: System Identification, Linear/Nonlinear Control Systems, Data-driven Modelling and Control, Process Modelling and Process Control, Fault Diagnosis and Reliable Control, Intelligent Systems, and Machine Learning and Artificial Intelligence.

The papers showcased here share the latest findings on methodologies, algorithms and applications in modelling, identification, and control, integrated with Artificial Intelligence (AI), making the book an asset for researchers, engineers, and university students alike.

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Editors and Affiliations

  • Beijing Technology and Business University, Beijing, China

    Tingli Su

  • Qingdao University of Science and Technology, Qingdao, China

    Ning Sheng

  • Zhejiang University of Technology, Hangzhou, China

    Qiang Chen

  • University of Science and Technology Beijing, Beijing, China

    Weicun Zhang

About the editors

Tingli Su received her B.E. degree in Mechatronic Engineering and the Ph.D. degree in Control Science and Engineering from Beijing Institute of Technology. During 2009 and 2012, she has been a visiting student in University of Bristol with her work on Networked Control Systems. She is now an associate professor in Beijing Technology and Business University. Her research interests lie in the multi-sensor fusion, data analytics, and series-data based state estimation. She has published over 20 journal papers as the first author or corresponding author, holds 2 authorized invention patents, and has contributed to 3 academic monographs.

Ning Sheng obtained her Ph.D. in Control Science and Engineering from Northeastern University. Currently, she is an associate professor and the vice dean of the School of Automation and Electronic Engineering at Qingdao University of Science and Technology. Her research interests lie in intelligent control of nonlinear systems, fault-tolerant control, and fault diagnosis, etc. She has published over 30 journal papers as the first or corresponding author and holds 5 authorized invention patents.

Qiang Chen (Member, IEEE) received the B.S. degree in measurement and control technology and instrumentation from Hebei Agricultural University, Baoding, China, in 2006, and the Ph.D. degree in control science and engineering from Beijing Institute of Technology, Beijing, China, in 2012. Since 2012, he has been with the College of Information Engineering, Zhejiang University of Technology, Hangzhou, China, where he is currently a Professor. He has published over 100 peer-reviewed papers in journals and conference proceedings, and has been authorized more than 60 invention patents, 13 of which were transferred. His research interests include adaptive control and iterative learning control with application to motion control systems.

Weicun Zhang is an associate professor of the School of Automation and Electrical Engineering, University of Science and Technology Beijing. He earned his Ph. D degree from Tsinghua University in the field of control theory. His research interest includes: self-tuning adaptive control, multiple model adaptive control/estimation of both linear and nonlinear systems. As representative research work, he established a Virtual Equivalent System (VES) theory for unified analysis of adaptive control systems, which is independent of specific control strategy and parameter estimation algorithm. Recently, he published a paper on the Riemann Hypothesis.

Accessibility Information

PDF accessibility summary

This PDF has been created in accordance with the PDF/UA-1 standard to enhance accessibility, including screen reader support, described non-text content (images, graphs), bookmarks for easy navigation, keyboard-friendly links and forms and searchable, selectable text. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. Please note that a more accessible version of this eBook is available as ePub.

EPUB accessibility summary

This ebook is designed with accessibility in mind, aiming to meet the ePub Accessibility 1.0 AA and WCAG 2.2 Level AA standards. It features a navigable table of contents, structured headings, and alternative text for images, ensuring smooth, intuitive navigation and comprehension. The text is reflowable and resizable, with sufficient contrast. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com.

Bibliographic Information

  • Book Title: Proceedings of the 17th International Conference on Modelling, Identification and Control (ICMIC2025)

  • Book Subtitle: Volume II

  • Editors: Tingli Su, Ning Sheng, Qiang Chen, Weicun Zhang

  • Series Title: Lecture Notes in Electrical Engineering

  • Publisher: Springer Singapore

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0), Springer Nature Proceedings excluding Computer Science

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026

  • Hardcover ISBN: 978-981-95-3315-2Due: 20 May 2026

  • Softcover ISBN: 978-981-95-3318-3Due: 20 May 2027

  • eBook ISBN: 978-981-95-3316-9Due: 02 May 2026

  • Series ISSN: 1876-1100

  • Series E-ISSN: 1876-1119

  • Edition Number: 1

  • Number of Pages: XII, 642

  • Number of Illustrations: 37 b/w illustrations, 256 illustrations in colour

Keywords

  • Modelling and control
  • intelligent systems
  • networks
  • fault tolerant
  • smart grids
  • linear systems
  • nonlinear systems
  • vibration analysis
  • renewable energy systems
  • data-driven science, modeling and theory building

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