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Название: Analysis and Synthesis for Networked Multi-Rate Systems
Автор: Yuxuan Shen, Zidong Wang, Hongli Dong
Издательство: CRC Press
Год: 2024
Страниц: 260
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

In this book, we present the novel state estimation methods for several classes of networked multi-rate systems. The content of this book can be divided into two parts. In the first part, we show the state estimation methods for networked multi-rate systems with various complex network-induced phenomena. The state estimation methods for networked multi-rate systems under the communication protocols are presented in the second part. The systems we investigated include stochastic non-linear systems, time-delay systems, linear repetitive processes, and Artificial Neural Networks (ANNs). The complex networkinduced phenomena considered are time-delays, integral measurements, sensor resolutions, and dynamical bias. The communication protocols included are the Round-Robin protocol, the weighted Try-Once-Discard protocol, the p-persistent carrier sense multiple access protocol, and the dynamic event-triggered protocol. The techniques used are mainly the Lyapunov stability theory, the optimal estimation theory, the lifting technique, and certain convex optimization methods. This book provides valuable reference materials for researchers who wish to explore the state estimation for multi-rate systems.

With the rapid development of wireless communication technology and digital technology, networked systems have been widely applied in practical applications such as process monitoring, power grids, industrial control systems, and traffic systems. In networked systems, the signals generated by system components, including the sensors, underlying plant, and controllers, are first sampled and then transmitted through communication networks. Compared to traditional systems, networked systems provide the advantages of low cost, easy maintenance, and high reliability. Nevertheless, the introduction of the communication network largely increases the complexity of networked systems and hence brings major challenges to the state estimation of networked systems. Consequently, the problem of state estimation for networked systems has been attracting ever-increasing research
interest.

Due to its large scale, it is often the case that the networked system contains numerous spatially distributed system components (including multiple sensors). As mentioned before, continuous signals from system components are first sampled into discrete signals with fixed sampling periods before being transmitted. Traditionally, to simplify the design of the state estimation algorithms, it is assumed that a unified sampling period is chosen for different signals. Unfortunately, such an assumption is not realistic in real practice. Since different system components own different physical characteristics, it is quite difficult (if not impossible) to unify the sampling periods for different components. Furthermore, setting different sampling periods for different system components (i.e., multi-rate sampling) according to the importance of their signals is preferable in engineering practice. As such, the state estimation problems for networked multi-rate systems (MRSs), which reflect the real situation in practical engineering, have stirred the attentions from researchers.

Features:

Gives a systematic investigation of the state estimation of multi-rate systems
Discusses results on state estimation problems under network-induced complexities
Studies different kinds of multi-rate systems including multi-rate nonlinear systems, multi-rate neural networks, and multi-rate linear repetitive processes
Explores network-enhanced complexities and communication protocols
Includes case studies showing the applicability of developed estimation algorithms including practical examples like DC servo systems and continuous stirred tank reactor systems

Analysis and Synthesis for Networked Multi-Rate Systems is aimed at graduate students and researchers in signal processing, control systems, and electrical engineering.

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