Recursive Filtering of Networked Systems with Communication Protocol Scheduling

Recursive Filtering of Networked Systems with Communication Protocol Schedulingexplores protocol-based state estimation for complex networked systems including Kalman filtering for nonlinear systems under Round-Robin (RR) and MEF-TOD protocols, finite-horizon robust state estimation under FlexRay protocol, robust filtering for multi-rate systems under RR and stochastic communication protocols, and state estimation under event-triggering protocol and redundant channel for neural networks. This book provides theoretical frameworks using techniques like backward Riccati equations, Kalman filtering theory, Unscented transform, and ellipsoid estimation theory.FeaturesFocuses on the intersection of recursive filtering techniques and communication protocol schedulingIntroduces communication protocols to allocate limited network resourcesEnhances the reliability and accuracy of information transmission and minimize the occurrence of information conflicts and congestion in the networkOffers practical strategies for real-world challenges in networked systemsExplains designing filtering unit for a class of complex networksThis book is aimed at graduate students and researchers in electrical engineering, power systems, control systems.

Recursive Filtering of Networked Systems with Communication Protocol Schedulingexplores protocol-based state estimation for complex networked systems including Kalman filtering for nonlinear systems under Round-Robin (RR) and MEF-TOD protocols, finite-horizon robust state estimation under FlexRay protocol, robust filtering for multi-rate systems under RR and stochastic communication protocols, and state estimation under event-triggering protocol and redundant channel for neural networks. This book provides theoretical frameworks using techniques like backward Riccati equations, Kalman filtering theory, Unscented transform, and ellipsoid estimation theory.

Recursive Filtering of Networked Systems with Communication Protocol Scheduling

explores protocol-based state estimation for complex networked systems including Kalman filtering for nonlinear systems under Round-Robin (RR) and MEF-TOD protocols, finite-horizon robust state estimation under FlexRay protocol, robust filtering for multi-rate systems under RR and stochastic communication protocols, and state estimation under event-triggering protocol and redundant channel for neural networks. This book provides theoretical frameworks using techniques like backward Riccati equations, Kalman filtering theory, Unscented transform, and ellipsoid estimation theory.

Focuses on the intersection of recursive filtering techniques and communication protocol scheduling

Introduces communication protocols to allocate limited network resources

Enhances the reliability and accuracy of information transmission and minimize the occurrence of information conflicts and congestion in the network

Offers practical strategies for real-world challenges in networked systems

Explains designing filtering unit for a class of complex networks

This book is aimed at graduate students and researchers in electrical engineering, power systems, control systems.