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wang l data rate constrained state estimation complex networked systems 2025

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Textbook in PDF format This book presents research developments and novel methodologies on data-rate-constrained control and state estimation for complex networked systems with different kinds of encoding-decoding mechanisms. It describes framework of state estimator and controller design, stability and performance analysis for data-rate constrained complex systems with various kinds of encoding-decoding schemes and so forth. Simulations given in this book are constructed by applying MatLAB software package. With ever-rapid developments in sensing, computing, communication and integration technologies, the modern industrial systems possess high scalability and integrated architecture. In particular, compared with traditional industrial control systems where information interactions are implemented by a wire-based point-to-point way, modern networked control systems upgrade in such a data exchange manner to the shared-network-based one (e.g. field bus, IP/Ethernet, Bluetooth), which greatly enhances the reliability, efficiency and flexibility of the systems. On the other hand, the introduction of the communication network in industrial systems also brings in some issues, a representative one of which is the data rate-constraint. In practical applications, most of the systems suffer from limited date rate of communication network due either to physical constraint or to cost consideration, which gives rise to various undesirable network-induced phenomena. The data encoding-decoding scheme is one of the efficient approaches to deal with the scarcity issue of the communication resource and thus might avoid the performance deteriorations of data communication. The existing control/state estimation methods are designed without consideration of the date rate issue and this necessitates re-designing or developing new methodologies to accommodate the imbedding of different encoding-decoding mechanisms. The objective of this book is to present the state-of-the-art research developments and novel methodologies on data-rate-constrained control and state estimation for complex networked systems with different kinds of encoding-decoding mechanisms. The contents of this book can be divided into two parts, where the first part (Chapters 2–5) addresses the data-constrained control/state estimation problems under uniform-quantization-based encoding-decoding scheme for complicated systems (e.g. neural networks, complex networks and multi-agent systems) and the second part (Chapters 6–9) introduces both the multiple description encoding mechanism and the event-based encoding protocol into the networked systems to cope with the data constraint issue. The work provides a framework of state estimator and controller design, stability and performance analysis for data-rate constrained complex systems with various kinds of encoding-decoding schemes, including the static/dynamic uniform-quantization-based scheme, the multiple description coding scheme, the sign-based coding scheme, etc. Some related techniques and theories are applied, which include the recursive Riccati-like equations, hybrid system theory, matrix theory, and mathematical optimization methods, to fulfill the specific analysis and synthesis issues. Features: Gives a systematic investigation of the control and state estimation for complex networked systems subject to the data rate constraint. Develops control/filtering algorithms in a unified framework. Includes comparisons for different coding-decoding techniques proposed. Discusses theoretical value and practical application for the resource-constrained communication environment. Provides performance analysis as well as the parameterizations of filters and FD units. This book is aimed at researchers and graduate students in electrical engineering, signal processing, control systems and complex networks. Contents: Introduction Gain-Scheduled State Estimation for Discrete-Time Complex Networks Under Bit-Rate Constraints Partial-Neurons-Based State Estimation For Artificial Neural Networks Under Constrained Bit Rate: The Finite-Time Case Synchronization Control for a Class of Discrete-Time Dynamical Networks With Packet Dropouts: A Coding-Decoding-Based Approach Observer-Based Consensus Control for Discrete-Time Multi- Agent Systems with Coding-Decoding Communication Protocol Recursive Filtering with Measurement Fading: A Multiple Description Coding Scheme Stabilization of Linear Discrete-Time Systems Over Resource-Constrained Networks Under Dynamical Multiple Description Coding Scheme An Event-Triggered Encoding Approach to Control of Linear Systems under Bit Rate Conditions Event-Based State Estimation under Constrained Bit Rate: An Encoding-Decoding Approach Conclusions and Future Topics

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wang l data rate constrained state estimation complex networked systems 2025

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