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Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals/ by Ju H. Park, Hao Shen, Xiao-Heng Chang, Tae H. Lee.
Author:	Park, Ju H.
other author:	Shen, Hao.
Description:	XXVII, 226 p. 56 illus., 54 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Control engineering. -
Online resource:	https://doi.org/10.1007/978-3-319-96202-3
ISBN:	9783319962023

Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals
Park, Ju H.

Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals[electronic resource] /by Ju H. Park, Hao Shen, Xiao-Heng Chang, Tae H. Lee. - 1st ed. 2019. - XXVII, 226 p. 56 illus., 54 illus. in color.online resource. - Studies in Systems, Decision and Control,1702198-4182 ;. - Studies in Systems, Decision and Control,27.

Introduction -- Network-based Control with Asynchronous Samplings and Quantizations -- Quantized Static Output Feedback Control For Discrete-Time Systems -- Sampled-Data Control for a Class of Linear Systems with Randomly Occurring Missing Data -- Reliable Event-triggered Retarded Dynamic Output Feedback H∞ Control for Networked Systems -- Reliable H∞ Event-triggered Control for Markov Jump Systems -- Fuzzy Resilient Energy-to-Peak Filter Design for Continuous-time Nonlinear Systems -- Fuzzy Generalized H2 Filtering For Nonlinear Discrete-Time Systems With Measurement Quantization -- Event-triggered Dissipative Filtering for Networked semi-Markov Jump Systems -- Network-based H∞ State Estimation for Neural Networks Using Limited Measurement -- Mixed H∞/passive Synchronization for Complex Dynamical Networks with Sampled-data Control -- Index.

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 and professors, as well as R&D engineers involved in control theory and applications looking to analyze dynamical systems with constraints and to synthesize various types of corresponding controllers and filters for optimal performance of feedback systems.

ISBN: 9783319962023

Standard No.: 10.1007/978-3-319-96202-3doiSubjects--Topical Terms:

1249728
Control engineering.

LC Class. No.: TJ212-225

Dewey Class. No.: 629.8

Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals
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505 0 $a Introduction -- Network-based Control with Asynchronous Samplings and Quantizations -- Quantized Static Output Feedback Control For Discrete-Time Systems -- Sampled-Data Control for a Class of Linear Systems with Randomly Occurring Missing Data -- Reliable Event-triggered Retarded Dynamic Output Feedback H∞ Control for Networked Systems -- Reliable H∞ Event-triggered Control for Markov Jump Systems -- Fuzzy Resilient Energy-to-Peak Filter Design for Continuous-time Nonlinear Systems -- Fuzzy Generalized H2 Filtering For Nonlinear Discrete-Time Systems With Measurement Quantization -- Event-triggered Dissipative Filtering for Networked semi-Markov Jump Systems -- Network-based H∞ State Estimation for Neural Networks Using Limited Measurement -- Mixed H∞/passive Synchronization for Complex Dynamical Networks with Sampled-data Control -- Index.
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