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
1. Chapter One: Introduction - p. 1 2. Part One: Event-based state estimation for stochastic systems under networked environment - p. P1 3. Chapter Two: State-saturated resilient filtering for nonlinear complex networks under event-triggering protocol - p. 15 4. Chapter Three: A dynamically event-triggered approach to recursive filtering with censored measurements and parameter uncertainties - p. 41 5. Chapter Four: Distributed state-of-charge estimation for lithium-ion batteries with random sensor failure under dynamic event-triggering protocol - p. 61 6. Part Two: Event-based fusion estimation for multi-rate systems under networked environment - p. P2 7. Chapter Five: Event-based fusion estimation for multirate systems subject to sensor degradations - p. 89 8. Chapter Six: Event-triggering robust fusion estimation for a class of multirate systems subject to censored observations - p. 109 9. Part Three: Event-based state and fault estimation for nonlinear systems under networked environment - p. P3 10. Chapter Seven: Dynamic event-triggering joint state and unknown input estimation for nonlinear systems with random sensor failure - p. 141 11. Chapter Eight: State and fault estimation for nonlinear systems subject to censored measurements: a dynamic event-triggered case - p. 165 12. Chapter Nine: Event-triggering state and fault estimation for a class of nonlinear systems subject to sensor saturations - p. 191 13. References - p. 211 14. Index - p. 229
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
1. Chapter One: Introduction - p. 1 2. Part One: Event-based state estimation for stochastic systems under networked environment - p. P1 3. Chapter Two: State-saturated resilient filtering for nonlinear complex networks under event-triggering protocol - p. 15 4. Chapter Three: A dynamically event-triggered approach to recursive filtering with censored measurements and parameter uncertainties - p. 41 5. Chapter Four: Distributed state-of-charge estimation for lithium-ion batteries with random sensor failure under dynamic event-triggering protocol - p. 61 6. Part Two: Event-based fusion estimation for multi-rate systems under networked environment - p. P2 7. Chapter Five: Event-based fusion estimation for multirate systems subject to sensor degradations - p. 89 8. Chapter Six: Event-triggering robust fusion estimation for a class of multirate systems subject to censored observations - p. 109 9. Part Three: Event-based state and fault estimation for nonlinear systems under networked environment - p. P3 10. Chapter Seven: Dynamic event-triggering joint state and unknown input estimation for nonlinear systems with random sensor failure - p. 141 11. Chapter Eight: State and fault estimation for nonlinear systems subject to censored measurements: a dynamic event-triggered case - p. 165 12. Chapter Nine: Event-triggering state and fault estimation for a class of nonlinear systems subject to sensor saturations - p. 191 13. References - p. 211 14. Index - p. 229
