In this book, the stability analysis and estimator design problems are discussed for delayed discrete-time memristive neural networks. In each chapter, the analysis problems are firstly considered, where the stability, synchronization and other performances (e.g., robustness, disturbances attenuation level) are investigated within a unified theoretical framework. In this stage, some novel notions are put forward to reflect the engineering practice. Then, the estimator design issues are discussed where sufficient conditions are derived to ensure the existence of the desired estimators with guaranteed performances. Finally, the theories and techniques developed in previous parts are applied to deal with some issues in several emerging research areas. The book <ul> <li>Unifies existing and emerging concepts concerning delayed discrete memristive neural networks with an emphasis on a variety of network-induced phenomena</li> <li>Captures recent advances of theories, techniques, and applications of delayed discrete memristive neural networks from a network-oriented perspective</li> <li>Provides a series of latest results in two popular yet interrelated areas, stability analysis and state estimation of neural networks</li> <li>Exploits a unified framework for analysis and synthesis by designing new tools and techniques in combination with conventional theories of systems science, control engineering and signal processing</li> <li>Gives simulation examples in each chapter to reflect the engineering practice</li> </ul>

Stability Analysis and State Estimation of Memristive Neural Networks

Engineering & Transportation

Wang, Zidong

Ma, Lifeng

Liu, Hongjian

Engineering

CRC-Press

Recursive Filtering for 2-D Shift-Varying Systems with Communication Constraints

Computers & Technology

Wang Fan

Liang, Jinling

Computer Science

This book presents up-to-date research developments and novel methodologies regarding recursive filtering for 2-D shift-varying systems with various communication constraints. It investigates recursive filter/estimator design and performance analysis by a combination of intensive stochastic analysis, recursive Riccati-like equations, variance-constrained approach, and mathematical induction. Each chapter considers dynamics of the system, subtle design of filter gains, and effects of the communication constraints on filtering performance. Effectiveness of the derived theories and applicability of the developed filtering strategies are illustrated via simulation examples and practical insight.Features: -<ul> <li>Covers recent advances of recursive filtering for 2-D shift-varying systems subjected to communication constraints from the engineering perspective.</li> <li>Includes the recursive filter design, resilience operation and performance analysis for the considered 2-D shift-varying systems.</li> <li>Captures the essence of the design for 2-D recursive filters.</li> <li>Develops a series of latest results about the robust Kalman filtering and protocol-based filtering.</li> <li>Analyzes recursive filter design and filtering performance for the considered systems.</li> </ul>This book aims at graduate students and researchers in mechanical engineering, industrial engineering, communications networks, applied mathematics, robotics and control systems.

Networked Nonlinear Stochastic Time-Varying Systems

Science & Math

Dong, Hongli

Hou, Nan

Mathematics

Networked Non-linear Stochastic Time-Varying Systems: Analysis and Synthesis copes with the filter design, fault estimation and reliable control problems for different classes of nonlinear stochastic time-varying systems with network-enhanced complexities. Divided into three parts, the book discusses the finite-horizon filtering, fault estimation and reliable control, and randomly occurring nonlinearities/uncertainties followed by designing of distributed state and fault estimators, and distributed filters. The third part includes problems of variance-constrained H&#8734; state estimation, partial-nodes-based state estimation and recursive filtering for nonlinear time-varying complex networks with randomly varying topologies, and random coupling strengths.<ul> <li>Offers a comprehensive treatment of the topics related to Networked Nonlinear Stochastic Time-Varying Systems with rigorous math foundation and derivation </li> <li>Unifies existing and emerging concepts concerning control/filtering/estimation and distributed filtering </li> <li>Provides a series of latest results by drawing on the conventional theories of systems science, control engineering and signal processing Deal with practical engineering problems such as event triggered H&#8734; filtering, non-fragile distributed estimation, recursive filtering, set-membership filtering </li> <li>Demonstrates illustrative examples in each chapter to verify the correctness of the proposed results</li> </ul>This book is aimed at engineers, mathematicians, scientists, and upper-level students in the fields of control engineering, signal processing, networked control systems, robotics, data analysis, and automation.

Control and State Estimation for Dynamical Network Systems with Complex Samplings

Shen, Bo

Li, Qi

State Estimation and Fault Diagnosis under Imperfect Measurements

Liu, Yang

Zhou, Donghua

This book discusses the Sliding Mode Control (SMC) problems of networked control systems (NCSs) under various communication protocols including static/dynamic/periodic event-triggered mechanism, and stochastic communication, Round-Robin, weighted try-once-discard, multiple-packet transmission, and the redundant channel transmission protocol.&#12288; The super-twisting algorithm and the extended-state-observer-based SMC scheme are described in this book for suppressing chattering. Besides, the SMC designs for two-dimensional (1-D) and two-dimensional (2-D) NCSs are illustrated as well. Features: <ul> <li>Captures recent advances of theories, techniques, and applications of networked sliding mode control from an engineering-oriented perspective.</li> <li>Includes new design ideas and optimization techniques of networked sliding mode control theory.</li> <li>Provides advanced tools to apply networked sliding mode control techniques in the practical applications.</li> <li>Discusses some new tools to the engineering applications while dealing with the model uncertainties and external disturbances.</li> </ul> This book aims at Researchers and professionals in Control Systems, Computer Networks, Internet of Things, and Communication Systems.

Protocol-Based Sliding Mode Control: 1D and 2D System Cases

Song, Jun

Niu, Yugang

This book unifies existing and emerging concepts concerning state estimation, fault detection, fault isolation and fault estimation on industrial systems with an emphasis on a variety of network-induced phenomena, fault diagnosis and remaining useful life for industrial equipment. It covers state estimation/monitor, fault diagnosis and remaining useful life prediction by drawing on the conventional theories of systems science, signal processing and machine learning. Features: <ul> <li>Unifies existing and emerging concepts concerning robust filtering and fault diagnosis with an emphasis on a variety of network-induced complexities.</li> <li>Explains theories, techniques, and applications of state estimation as well as fault diagnosis from an engineering-oriented perspective.</li> <li>Provides a series of latest results in robust/stochastic filtering, multidate sample, and time-varying system.</li> <li>Captures diagnosis (fault detection, fault isolation and fault estimation) for time-varying multi-rate systems.</li> <li>Includes simulation examples in each chapter to reflect the engineering practice.</li> </ul> This book aims at graduate students, professionals and researchers in control science and application, system analysis, artificial intelligence, and fault diagnosis.

Filter-Based Fault Diagnosis and Remaining Useful Life Prediction

ZHANG YONG

Yuan, Ye

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Books by Wang, Zidong