Zidong Wang

This book explores PID control and PI state estimation for complex networked systems facing network-enhanced challenges including fading measurements, time-delays, packet dropouts, and cyber-attacks including PID control problems, PI state estimation and neural networks. It addresses output-feedback control, observer-based control, tracking control, and state estimation across different network conditions, implementing solutions for resource constraints, outlier resistance, and partial measurement scenarios using MATLAB simulations. Key features of the book- 1 Presents systematic research on the PID control problem based on the state space method for networked systems 2 Contains everything needed to capture the essence of design and performance evaluation for PID controllers and PI estimators 3 Covers security aspects of encoded transmissions, encompassing encryption protocols and cyber-physical attack resilience 4 Addresses issues such as network-induced complexities, cybersecurity threats, and adaptive control strategies 5 Emphasizes flexible, reliable, and practical solutions for real-world systems, bridging theoretical rigor with engineering applications This book is aimed at graduate students and researchers in control science and engineering, signal processing, computer science.

Recursive Filtering of Networked Systems with Communication Protocol Scheduling explores protocol-based state estimation for complex networked systems including Kalman filtering for nonlinear systems under RR and MEF-TOD protocols, finite-horizon robust state estimation under FlexRay protocol, robust filtering for multi-rate systems under Round-Robin and stochastic communication protocols, and state estimation under event-triggering protocol and redundant channel for neural networks. This book provides theoretical frameworks using techniques like backward Riccati equations, Kalman filtering theory, Unscented transform, and ellipsoid estimation theory. Features 1 Focuses on the intersection of recursive filtering techniques and communication protocol scheduling 2 Introduces communication protocols to allocate limited network resources 3 Enhances the reliability and accuracy of information transmission and minimize the occurrence of information conflicts and congestion in the network 4 Offers practical strategies for real-world challenges in networked systems 5 Explains designing filtering unit for a class of complex networks This book is aimed at graduate students and researchers in electrical engineering, power systems, control systems.

Model Predictive Control (MPC) has advanced as a robust method for managing complex dynamic systems, surpassing traditional control strategies in performance and constraint handling. This book explores MPC theory and applications, focusing on robust MPC (RMPC) for systems with uncertainties. It examines three system types: networked systems, stochastic switching systems, and nonlinear hybrid systems. It addresses challenges in networked interventions, Markovian jump systems, and nonlinear systems under communication constraints. Integrates model predictive control, network-induced constraints, cyber-security issues, and advanced communication protocols Covers control and state estimation with a focus on dynamic network systems with complex sampling. Considers and models network-induced complexities Employs several analysis techniques to overcome the recent mathematical/computational difficulties for discrete-time systems Deals with practical engineering problems for complex dynamic systems with different kinds of scenario-induced complexities or framework-induced complexities This book is aimed at graduate students and researchers in networks, signal processing, controls, dynamic complex systems.

This book presents advanced Dynamic State Estimation (DSE) methodologies across three power system classes: quasi-steady power systems, synchronous-generator-based multi-machine systems and renewable energy microgrids. The work tackles unconventional measurements including time-delays, multi-rate measurements, event-triggered transmissions, outliers, and sensor saturations including complex factors. The nine-chapter structure progresses from fundamentals through specific applications to future research directions. Explore state estimation in power systems and challenges in large, complex grids with high renewable energy integration. Provides step-by-step derivations of theoretical results and case studies based on widely used power system benchmarks. Addresses two prominent research and technological aspects: soft computing for estimation and power electrical systems. Considers practical issues such as online application and computational efficiency in the estimator design, Reviews analysis techniques such as optimal estimation technique, completing the square method, stochastic analysis technique, and entropy theory This book is aimed at graduate students and researchers in electrical engineering, power systems, control systems, and signal processing.

This book introduces four novel Dynamic Event-Triggered Mechanisms (DETMs) for complex networked systems that optimize resource utilization while preserving system performance. These include hybrid dynamic variables-dependent ETMs, hybrid adjusting variables-dependent ETMs, bounded dynamic variable/time-varying threshold-dependent ETMs and terminal constraint set-dependent mixed time/event-triggered mechanisms. It explores applications across fault diagnosis in networked systems, finite-time state estimation for complex dynamical networks, and MPC implementation. Presents systematic study on dynamic event-triggered mechanisms Reviews comprehensive research results on dynamic event-triggered fault diagnosis, state estimation and MPC Explores how these theories can be applied to the practical engineering problem of load frequency control in power systems Discusses complex factors including cyber-attacks, multiple timescales, jumping system parameters, hard constraints, polytopic uncertainties, nonlinearities, and limited network/computing resources Includes numerous simulations and examples to validate the theoretical results including single-link rigid robot model systems, motor systems and power systems This book is aimed at graduate students and researchers in control systems, computer sciences, and signal processing.

This book presents novel state estimation methods for several classes of networked multi-rate systems including state estimation methods for networked multi-rate systems with various complex networked-induced phenomena and communication protocols. The systems investigated include stochastic nonlinear systems, time-delay systems, linear repetitive processes, and artificial neural networks. The techniques used are mainly the Lyapunov stability theory, the optimal estimation theory, the lifting technique, and certain convex optimization method.FeaturesGives a systematic investigation of the state estimation of multi-rate systemsDiscusses results on state estimation problems under network-induced complexitiesStudies different kinds of multi-rate systems including multi-rate nonlinear systems, multi-rate neural networks, and multi-rate linear repetitive processesExplores network-enhanced complexities and communication protocolsIncludes case studies showing the applicability of developed estimation algorithms including practical examples like DC servo systems and continuous stirred tank reactor systemsAnalysis and Synthesis for Networked Multi-Rate Systems is aimed at graduate students and researchers in signal processing, control systems, and electrical engineering.

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.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.

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:- Covers recent advances of recursive filtering for 2-D shift-varying systems subjected to communication constraints from the engineering perspective. Includes the recursive filter design, resilience operation and performance analysis for the considered 2-D shift-varying systems. Captures the essence of the design for 2-D recursive filters. Develops a series of latest results about the robust Kalman filtering and protocol-based filtering. Analyzes recursive filter design and filtering performance for the considered systems.This book aims at graduate students and researchers in mechanical engineering, industrial engineering, communications networks, applied mathematics, robotics and control systems.

The objective of this book is to present the up-to-date research developments and novel methodologies on state estimation and fault diagnosis (FD) techniques for a class of complex systems subject to closed-loop control, nonlinearities, and stochastic phenomena. It covers state estimation design methodologies and FD unit design methodologies including framework of optimal filter and FD unit design, robust filter and FD unit design, stability, and performance analysis for the considered systems subject to various kinds of complex factors.Features: Reviews latest research results on the state estimation and fault diagnosis issues. Presents comprehensive framework constituted for systems under imperfect measurements. Includes quantitative performance analyses to solve problems in practical situations. Provides simulation examples extracted from practical engineering scenarios. Discusses proper and novel techniques such as the Carleman approximation and completing the square method is employed to solve the mathematical problems.This book aims at Graduate students, Professionals and Researchers in Control Science and Application, Stochastic Process, Fault Diagnosis, and Instrumentation and Measurement.

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 H8 state estimation, partial-nodes-based state estimation and recursive filtering for nonlinear time-varying complex networks with randomly varying topologies, and random coupling strengths. Offers a comprehensive treatment of the topics related to Networked Nonlinear Stochastic Time-Varying Systems with rigorous math foundation and derivation Unifies existing and emerging concepts concerning control/filtering/estimation and distributed filtering 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 H8 filtering, non-fragile distributed estimation, recursive filtering, set-membership filtering Demonstrates illustrative examples in each chapter to verify the correctness of the proposed resultsThis 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.

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 Unifies existing and emerging concepts concerning delayed discrete memristive neural networks with an emphasis on a variety of network-induced phenomena Captures recent advances of theories, techniques, and applications of delayed discrete memristive neural networks from a network-oriented perspective Provides a series of latest results in two popular yet interrelated areas, stability analysis and state estimation of neural networks 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 Gives simulation examples in each chapter to reflect the engineering practice

This book presents novel state estimation methods for several classes of networked multi-rate systems including state estimation methods for networked multi-rate systems with various complex networked-induced phenomena and communication protocols. The systems investigated include stochastic nonlinear systems, time-delay systems, linear repetitive processes, and artificial neural networks. The techniques used are mainly the Lyapunov stability theory, the optimal estimation theory, the lifting technique, and certain convex optimization method.FeaturesGives a systematic investigation of the state estimation of multi-rate systemsDiscusses results on state estimation problems under network-induced complexitiesStudies different kinds of multi-rate systems including multi-rate nonlinear systems, multi-rate neural networks, and multi-rate linear repetitive processesExplores network-enhanced complexities and communication protocolsIncludes case studies showing the applicability of developed estimation algorithms including practical examples like DC servo systems and continuous stirred tank reactor systemsAnalysis and Synthesis for Networked Multi-Rate Systems is aimed at graduate students and researchers in signal processing, control systems, and electrical engineering.

Communication-Protocol-Based Filtering and Control of Networked Systems is a self-contained treatment of the state of the art in communication-protocol-based filtering and control;recent advances in networked systems; andthe potential for application in sensor networks. This book provides new concepts, new models and new methodologies with practical significance in control engineering and signal processing. The book first establishes signal-transmission models subject to different communication protocols and then develops new filter design techniques based on those models and preset requirements for filtering performance. The authors then extend this work to finite-horizon H-infinity control, ultimately bounded control and finite-horizon consensus control. The focus throughout is on three typical communications protocols: the round-robin, random-access and try-once-and-discard protocols, and the systems studied are drawn from a variety of classes, among them nonlinear systems, time-delayed and time-varying systems, multi-agent systems and complex networks. Readers are shown the latest techniques—recursive linear matrix inequalities, backward recursive difference equations, stochastic analysis and mapping methods. The unified framework for communication-protocol-based filtering and control for different networked systems established in the book will be of interest to academic researchers and practicing engineers working with communications and other signal-processing systems. Senior undergraduate and graduate students looking to increase their knowledge of current methods in control and signal processing of networked systems will also find this book valuable.

This book establishes a unified framework for dealing with typical engineering complications arising in modern, complex, large-scale networks such as parameter uncertainties, missing measurement and cyber-attack. Distributed Filtering, Control and Synchronization is a timely reflection on methods designed to handle a series of control and signal-processing issues in modern industrial engineering practice in areas like power grids and environmental monitoring. It exploits the latest techniques to handle the emerging mathematical and computational challenges arising from, among other things, the dynamic topologies of distributed systems and in the context of sensor networks and multi-agent systems. These techniques include recursive linear matrix inequalities, local-performance and stochastic analyses and techniques based on matrix theory. Readers interested in the theory and application of control and signal processing will find much to interest them in the new models and methods presented in this book. Academic researchers can find ideas for developing their own research, graduate and advanced undergraduate students will be made aware of the state of the art, and practicing engineers will find methods for addressing practical difficulties besetting modern networked systems

The objective of this book is to present the up-to-date research developments and novel methodologies on state estimation and fault diagnosis (FD) techniques for a class of complex systems subject to closed-loop control, nonlinearities, and stochastic phenomena. It covers state estimation design methodologies and FD unit design methodologies including framework of optimal filter and FD unit design, robust filter and FD unit design, stability, and performance analysis for the considered systems subject to various kinds of complex factors.Features: Reviews latest research results on the state estimation and fault diagnosis issues. Presents comprehensive framework constituted for systems under imperfect measurements. Includes quantitative performance analyses to solve problems in practical situations. Provides simulation examples extracted from practical engineering scenarios. Discusses proper and novel techniques such as the Carleman approximation and completing the square method is employed to solve the mathematical problems.This book aims at Graduate students, Professionals and Researchers in Control Science and Application, Stochastic Process, Fault Diagnosis, and Instrumentation and Measurement.

Communication-Protocol-Based Filtering and Control of Networked Systems is a self-contained treatment of the state of the art in communication-protocol-based filtering and control;recent advances in networked systems; andthe potential for application in sensor networks. This book provides new concepts, new models and new methodologies with practical significance in control engineering and signal processing. The book first establishes signal-transmission models subject to different communication protocols and then develops new filter design techniques based on those models and preset requirements for filtering performance. The authors then extend this work to finite-horizon H-infinity control, ultimately bounded control and finite-horizon consensus control. The focus throughout is on three typical communications protocols: the round-robin, random-access and try-once-and-discard protocols, and the systems studied are drawn from a variety of classes, among them nonlinear systems, time-delayed and time-varying systems, multi-agent systems and complex networks. Readers are shown the latest techniques—recursive linear matrix inequalities, backward recursive difference equations, stochastic analysis and mapping methods. The unified framework for communication-protocol-based filtering and control for different networked systems established in the book will be of interest to academic researchers and practicing engineers working with communications and other signal-processing systems. Senior undergraduate and graduate students looking to increase their knowledge of current methods in control and signal processing of networked systems will also find this book valuable.

This book establishes a unified framework for dealing with typical engineering complications arising in modern, complex, large-scale networks such as parameter uncertainties, missing measurement and cyber-attack. Distributed Filtering, Control and Synchronization is a timely reflection on methods designed to handle a series of control and signal-processing issues in modern industrial engineering practice in areas like power grids and environmental monitoring. It exploits the latest techniques to handle the emerging mathematical and computational challenges arising from, among other things, the dynamic topologies of distributed systems and in the context of sensor networks and multi-agent systems. These techniques include recursive linear matrix inequalities, local-performance and stochastic analyses and techniques based on matrix theory. Readers interested in the theory and application of control and signal processing will find much to interest them in the new models and methods presented in this book. Academic researchers can find ideas for developing their own research, graduate and advanced undergraduate students will be made aware of the state of the art, and practicing engineers will find methods for addressing practical difficulties besetting modern networked systems

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 H8 state estimation, partial-nodes-based state estimation and recursive filtering for nonlinear time-varying complex networks with randomly varying topologies, and random coupling strengths. Offers a comprehensive treatment of the topics related to Networked Nonlinear Stochastic Time-Varying Systems with rigorous math foundation and derivation Unifies existing and emerging concepts concerning control/filtering/estimation and distributed filtering 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 H8 filtering, non-fragile distributed estimation, recursive filtering, set-membership filtering Demonstrates illustrative examples in each chapter to verify the correctness of the proposed resultsThis 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.

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:- Covers recent advances of recursive filtering for 2-D shift-varying systems subjected to communication constraints from the engineering perspective. Includes the recursive filter design, resilience operation and performance analysis for the considered 2-D shift-varying systems. Captures the essence of the design for 2-D recursive filters. Develops a series of latest results about the robust Kalman filtering and protocol-based filtering. Analyzes recursive filter design and filtering performance for the considered systems.This book aims at graduate students and researchers in mechanical engineering, industrial engineering, communications networks, applied mathematics, robotics and control systems.

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 Unifies existing and emerging concepts concerning delayed discrete memristive neural networks with an emphasis on a variety of network-induced phenomena Captures recent advances of theories, techniques, and applications of delayed discrete memristive neural networks from a network-oriented perspective Provides a series of latest results in two popular yet interrelated areas, stability analysis and state estimation of neural networks 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 Gives simulation examples in each chapter to reflect the engineering practice