Cong Huang, Hamid Reza Karimi, Peng Mei

Event-Driven State Estimation for Stochastic Networked Systems

• Broschiertes Buch

Produktbeschreibung

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

Produktdetails

• Verlag: Elsevier Science Publishing Co Inc
• Seitenzahl: 250
• Erscheinungstermin: 1. Dezember 2025
• Englisch
• Abmessung: 229mm x 152mm
• Gewicht: 450g
• ISBN-13: 9780443450143
• ISBN-10: 0443450145
• Artikelnr.: 74312758

Autorenporträt

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

Inhaltsangabe

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