Event-driven State Estimation for Stochastic Networked Systems

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

• Summarizes the latest research concepts, conclusions and applications of event-based state estimation methodologies for stochastic systems under limited communication networks
• Addresses the analysis and design of various types of stochastic systems under event-triggered mechanisms
• Utilizing state estimation strategies, challenges such as recursive state estimation, fusion estimation, and state and fault estimation for different stochastic systems are explored
• Utilizing state estimation strategies, the book challenges such as recursive state estimation, fusion estimation, and state and fault estimation for different stochastic systems are explored

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.