Multi-Source Fusion Filtering for Time-Varying Descriptor Systems

Erscheinungsjahr 2027
ISBN: 978-981-9273-83-6
Verlag: Springer Nature Singapore

Buch, Englisch, 350 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Intelligent Control and Learning Systems

This book is concerned with the multi-source fusion filtering problems under networked transmission environments and their potential applications for time-varying descriptor systems. The prominent features of this book can be highlighted as follows. (1) A unified framework is given for addressing the multi-source fusion filtering problems for time-varying descriptor systems under communication scheduling strategies. (2) The application potentials of multi-source fusion filtering under networked time-varying descriptor systems are outlined. It covers several new concepts, models, and methods with significant practical value. As an integrated work of multiple research achievements, this book provides valuable reference materials for senior undergraduate, graduate, and engineering technicians who are dedicated to multi-source fusion filtering research, pay attention to the latest developments in system analysis and design under communication scheduling strategies and explore the application of relevant theories in practical engineering systems.

Zielgruppe

Research

Autoren/Hrsg.

Hu, Jun

Li, Jiaxing

Zhang, Hongxu

Fachgebiete

• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Regelungstechnik
• Mathematik | Informatik Mathematik Stochastik
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Kybernetik, Systemtheorie, Komplexe Systeme

Inhaltsverzeichnis

Preface.- Acknowledgements.- Introduction.- Optimized Distributed Fusion Filtering with Fading Measurements and Stochastic Nonlinearity.- Multi-sensor Information Fusion Estimation with Missing Measurements.- Distributed Optimal Fusion Filtering with Random Transmission Delays and Packet Dropout Compensations.- Multi-Sensor Information Fusion Filtering with Packet Disorders.- Sequential Covariance Intersection Fusion Filtering under Round-Robin Protocol.- Sequential Covariance Intersection Fusion Filtering with Deception Attacks under Random Access Protocol.- Sequential Covariance Intersection Fusion Filtering under Maximum-Error-First Protocol.- Fusion Filtering with Random Observation Delays under Weighted Try-Once-Discard Protocol.- Dynamic Event-Triggered Fusion Filtering with Random State Delay.- Fusion Filtering with Markovian Random Delays via Dynamic Event-Triggered Feedback.- Cubature Kalman Fusion Filtering Against Deception Attacks.- Conclusions and Future Work.

Über Autor(innen)

Prof. Jun Hu received the B.Sc. degree in Information and Computing Science and M.Sc. degree in Applied Mathematics from Harbin University of Science and Technology, Harbin, China, in 2006 and 2009, respectively, and the Ph.D. degree in Control Science and Engineering from Harbin Institute of Technology, Harbin, China, in 2013. From September 2010 to September 2012, he was a Visiting Ph.D. student in the Department of Information Systems and Computing, Brunel University London, London, U.K. From May 2014 to April 2016, he was an Alexander von Humboldt research fellow at the University of Kaiserslautern, Kaiserslautern, Germany. From January 2018 to January 2021, he was a research fellow at University of South Wales, Pontypridd, U.K. He is with the Department of Mathematics and School of Automation, Harbin University of Science and Technology, Harbin, China. His research interests include nonlinear control, filtering and fault estimation, time-varying systems and complex networks. He has published more than 90 papers in refereed international journals. Prof. Hu serves as a reviewer for Mathematical Reviews, as an editor for Neurocomputing, Neural Processing Letters, Systems Science & Control Engineering, and as a guest editor for International Journal of General Systems and Information Fusion.

Dr. Jiaxing Li received the B.Sc. degree in Mathematics and Applied Mathematics from Harbin University of Commerce, Harbin, China, in 2017, the M.Sc. degree in Mathematics from Harbin University of Science and Technology, Harbin, China, in 2020. She received the Ph.D. degree in Mathematics from Harbin University of Science and Technology as well as University of Jaen, in 2025. From March 2023 to March 2024, she was a Visiting Ph.D. student in the Department of Computer Science, Brunel University London, Uxbridge, U.K. She is with the Department of Mathematics, Harbin University of Science and Technology, Harbin, China. Her current research interests include optimal distributed filtering for time-varying state-saturated systems and cubature Kalman filtering. She serves as a reviewer for journals such as IEEE/CAA Journal of Automatica Sinica, IEEE Transactions on Industrial Informatics, Applied Mathematics and Computation, and Neurocomputing.

Assoc. Prof. Hongxu Zhang received the B.Sc. degree in Information and Computation Science, the M.Sc. degree in Mathematics and the Ph.D. degree in Measuring and Testing Technologies and Instruments from Harbin University of Science and Technology, Harbin, China, in 2014, 2017 and 2021, respectively. From December 2019 to December 2020, he was a Visiting Ph.D. student at University of South Wales, Pontypridd, U.K. He is with the Department of Mathematics, Harbin University of Science and Technology, Harbin, China. His research interests include sliding mode control and optimal control. He is an active reviewer for many international journals such as Communications in Nonlinear Science and Numerical Simulation, Neurocomputing, and Neural Processing Letters.