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Titlebook: Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals; Ju H. Park,Hao Shen,Tae H. Lee Book 2019 Springer In

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書(shū)目名稱(chēng)Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals
編輯Ju H. Park,Hao Shen,Tae H. Lee
視頻videohttp://file.papertrans.cn/823/822696/822696.mp4
概述Presents recent research trends and practical examples in control and filtering of dynamic systems with constrained signals.Demonstrates various dynamic system models in continuous or discrete-time do
叢書(shū)名稱(chēng)Studies in Systems, Decision and Control
圖書(shū)封面Titlebook: Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals; Ju H. Park,Hao Shen,Tae H. Lee Book 2019 Springer In
描述.This book introduces the principle theories and applications of control and filtering problems to address emerging hot topics in feedback systems. With the development of IT technology at the core of the 4th industrial revolution, dynamic systems are becoming more sophisticated, networked, and advanced to achieve even better performance. However, this evolutionary advance in dynamic systems also leads to unavoidable constraints. In particular, such elements in control systems involve uncertainties, communication/transmission delays, external noise, sensor faults and failures, data packet dropouts, sampling and quantization errors, and switching phenomena, which have serious effects on the system’s stability and performance. This book discusses how to deal with such constraints to guarantee the system’s design objectives, focusing on real-world dynamical systems such as Markovian jump systems, networked control systems, neural networks, and complex networks, which have recently excited considerable attention. It also provides a number of practical examples to show the applicability of the presented methods and techniques...This book is of interest to graduate students, researchers
出版日期Book 2019
關(guān)鍵詞Control; Filtering; Dynamics systems; Dynamic networks; Synchronization; Stability; Stabilization; Quantiza
版次1
doihttps://doi.org/10.1007/978-3-319-96202-3
isbn_softcover978-3-030-07154-7
isbn_ebook978-3-319-96202-3Series ISSN 2198-4182 Series E-ISSN 2198-4190
issn_series 2198-4182
copyrightSpringer International Publishing AG, part of Springer Nature 2019
The information of publication is updating

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Network-Based Control with Asynchronous Samplings and Quantizationsn and receiving channels, asynchronous samplings and different logarithmic quantization effects are considered. The quantizer is assumed to be satisfied by the sector bounded condition and it is handled by the convex combination technique. To deal with sampling effect, we categorize three cases: one
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Quantized Static Output Feedback Control for Discrete-Time Systemsuantization in the communication channels from the sensor to the controller and from the controller to the actuator. In the presence of the input and output dynamic quantization effects, the attention of this chapter is focused on the design of both robust static output feedback stabilization and .
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Reliable Event-Triggered Retarded Dynamic Output Feedback , Control for Networked Systems randomness of actuators failures is modeled by a stochastic variable in a Markov jump model framework. In this paper, a Markov jump event-triggered retarded dynamic output feedback . controller is designed to guarantee the considered closed-loop system is stochastically stable with a prescribed . p
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Fuzzy Resilient Energy-to-Peak Filter Design for Continuous-Time Nonlinear Systemsnonlinear systems, the Takagi-Sugeno (T-S) fuzzy model with norm-bounded uncertainties is employed. By using a two-step approach, two new sufficient design conditions for the resilient filter are presented in terms of solutions to a set of linear matrix inequalities (LMIs), which guarantee the asymp
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