Event-Driven State Estimation for Stochastic Networked Systems
Will be published approx. on 1. December 2025
Book
Paperback/Softback
244 pages
978-0-443-45014-3 (ISBN)
Description
Event-Driven State Estimation for Stochastic Networked Systems offers a comprehensive and clear explanation of recent developments in event-based state estimation for stochastic systems within limited communication networks, bringing together existing and emerging concepts. It provides a series of the latest results in, including but not limited to, recursive state estimation, fusion estimation, and state and fault estimation. The book provides practitioner readers with practical tools for the analysis and design of stochastic systems under limited communication networks, capturing recent advances in theory, technological aspects and real-world applications of advanced event-based state estimation methodologies. Realistic research problems are addressed in each chapter, with numerical and simulation results provided to reflect engineering practice, while demonstrating the main focus of the developed estimation approaches. The book is an advanced-level resource presented in an accessible manner, appealing to senior students as a core reference and to researchers and practitioners alike
More details
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
Professional and scholarly
College/higher education
Dimensions
Height: 229 mm
Width: 152 mm
Weight
450 gr
ISBN-13
978-0-443-45014-3 (9780443450143)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Cong Huang | Peng Mei | Hamid Reza Karimi
Event-Driven State Estimation for Stochastic Networked Systems
E-Book
10/2025
Elsevier
€158.99
Available for download
Persons
Dr Cong Huang received his Ph.D. degree in control science and engineering from Donghua University, China. From 2019 to 2020, he was a joint PhD student at the Politecnico di Milano, Italy. He is currently an Associate Professor with the School of Transportation, Nantong University, China. He has published around 30 papers in refereed international journals. His research interests include stochastic control and filtering, vehicle platoon control, and estimation for vehicle-borne lithium-ion batteries Dr Peng Mei currently holds a joint postdoctoral position at the Politecnico di Milano and the University of Genoa. He earned his PhD in New Energy Vehicle Engineering from Beihang University in January 2024. From 2019 to 2021, he served as a Visiting Scholar in the Department of Mechanical Engineering at Politecnico di Milano in Milan, Italy. He has published around 20 papers in refereed international journals. His research focuses on various aspects of vehicle control strategies, reinforcement learning, and battery modelling
Dr. Karimi received the B.Sc. (First Hons.) degree in power systems from the Sharif University of Technology, Tehran, Iran, in 1998, and the M.Sc. and Ph.D. (First Hons.) degrees in control systems engineering from the University of Tehran, Tehran, in 2001 and 2005, respectively. His research interests are in the areas of control systems/theory, mechatronics, networked control systems, intelligent control systems, signal processing, vibration control, ground vehicles, structural control, wind turbine control and cutting processes. He is an Editorial Board Member for some international journals and several Technical Committee. Prof. Karimi has been presented a number of national and international awards, including Alexander-von-Humboldt Research Fellowship Award (in Germany), JSPS Research Award (in Japan), DAAD Research Award (in Germany), August-Wilhelm-Scheer Award (in Germany) and been invited as visiting professor at a number of universities in Germany, France, Italy, Poland, Spain, China, Korea, Japan, India.
Dr. Karimi received the B.Sc. (First Hons.) degree in power systems from the Sharif University of Technology, Tehran, Iran, in 1998, and the M.Sc. and Ph.D. (First Hons.) degrees in control systems engineering from the University of Tehran, Tehran, in 2001 and 2005, respectively. His research interests are in the areas of control systems/theory, mechatronics, networked control systems, intelligent control systems, signal processing, vibration control, ground vehicles, structural control, wind turbine control and cutting processes. He is an Editorial Board Member for some international journals and several Technical Committee. Prof. Karimi has been presented a number of national and international awards, including Alexander-von-Humboldt Research Fellowship Award (in Germany), JSPS Research Award (in Japan), DAAD Research Award (in Germany), August-Wilhelm-Scheer Award (in Germany) and been invited as visiting professor at a number of universities in Germany, France, Italy, Poland, Spain, China, Korea, Japan, India.
Content
1. Introduction
2. State-saturated resilient filtering for nonlinear complex networks under event-triggering protocols
3. A Dynamically event-triggered approach to recursive filtering with censored measurements and parameter uncertainties
4. Distributed state-of-charge estimation for lithium-ion batteries with random sensor failure under dynamic event-triggering protocol
5. Event-based fusion estimation for multi-rate systems subject to sensor degradations
6. Event-triggering robust fusion estimation for a class of multi-rate systems subject to censored observations
7. Dynamic event-triggering joint state and unknown input estimation for nonlinear systems with random sensor failure
8. State and fault estimation for nonlinear systems subject to censored measurements: a dynamic event-triggered case
9. Event-triggering state and fault estimation for a class of nonlinear systems subject to sensor saturations
2. State-saturated resilient filtering for nonlinear complex networks under event-triggering protocols
3. A Dynamically event-triggered approach to recursive filtering with censored measurements and parameter uncertainties
4. Distributed state-of-charge estimation for lithium-ion batteries with random sensor failure under dynamic event-triggering protocol
5. Event-based fusion estimation for multi-rate systems subject to sensor degradations
6. Event-triggering robust fusion estimation for a class of multi-rate systems subject to censored observations
7. Dynamic event-triggering joint state and unknown input estimation for nonlinear systems with random sensor failure
8. State and fault estimation for nonlinear systems subject to censored measurements: a dynamic event-triggered case
9. Event-triggering state and fault estimation for a class of nonlinear systems subject to sensor saturations