John Wiley & Sons Cyber-Physical Distributed Systems Cover CYBER-PHYSICAL DISTRIBUTED SYSTEMS Gather detailed knowledge and insights into cyber-physical syste.. Product #: 978-1-119-68267-7 Regular price: $116.82 $116.82 Auf Lager

Cyber-Physical Distributed Systems

Modeling, Reliability Analysis and Applications

Mo, Huadong / Sansavini, Giovanni / Xie, Min


1. Auflage September 2021
224 Seiten, Hardcover
Wiley & Sons Ltd

ISBN: 978-1-119-68267-7
John Wiley & Sons

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Gather detailed knowledge and insights into cyber-physical systems behaviors from a cutting-edge reference written by leading voices in the field

In Cyber-Physical Distributed Systems: Modeling, Reliability Analysis and Applications, distinguished researchers and authors Drs. Huadong Mo, Giovanni Sansavini, and Min Xie deliver a detailed exploration of the modeling and reliability analysis of cyber physical systems through applications in infrastructure and energy and power systems. The book focuses on the integrated modeling of systems that bring together physical and cyber elements and analyzing their stochastic behaviors and reliability with a view to controlling and managing them.

The book offers a comprehensive treatment on the aging process and corresponding online maintenance, networked degradation, and cyber-attacks occurring in cyber-physical systems. The authors include many illustrative examples and case studies based on real-world systems and offer readers a rich set of references for further research and study.

Cyber-Physical Distributed Systems covers recent advances in combinatorial models and algorithms for cyber-physical systems modeling and analysis. The book also includes:
* A general introduction to traditional physical/cyber systems, and the challenges, research trends, and opportunities for real cyber-physical systems applications that general readers will find interesting and useful
* Discussions of general modeling, assessment, verification, and optimization of industrial cyber-physical systems
* Explorations of stability analysis and enhancement of cyber-physical systems, including the integration of physical systems and open communication networks
* A detailed treatment of a system-of-systems framework for the reliability analysis and optimal maintenance of distributed systems with aging components

Perfect for undergraduate and graduate students in computer science, electrical engineering, cyber security, industrial and system engineering departments, Cyber-Physical Distributed Systems will also earn a place on the bookshelves of students taking courses related to reliability, risk and control engineering from a system perspective. Reliability, safety and industrial control professionals will also benefit greatly from this book.

Preface v

List of Acronyms and Abbreviations ix

Introduction 1

Challenges of Traditional Physical and Cyber Systems 1

Research Trends in Cyber-Physical Systems (CPSs) 3

Stability of CPSs 3

Reliability of CPSs 6

Opportunities for CPS Applications 7

Managing Reliability and Feasibility of CPSs 7

Ensuring Cybersecurity of CPSs 9

Fundamentals of CPSs 13

Models for Exploring CPSs 14

Control-Block-Diagram of CPSs 14

Control Signal in CPSs 14

Degraded Actuator and Sensor 14

Time-Varying Model of CPSs 15

Implementation in TrueTime Simulator 16

Introduction of TrueTime Simulator 16

Architecture of CPSs in TrueTime 17

Evaluation and Verification of CPSs 18

CPS Performance Evaluation 18

CPS Performance Index 18

Reliability Evaluation of CPSs 19

CPS Model Verification 20

CPS Performance Improvement 21

PSO-Based Reliability Enhancement 22

Optimal PID-Automatic Generation Control (AGC) 23

Stability Enhancement of CPSs 29

Integration of Physical and Cyber Models 30

Basics of Wide-Area Power Systems (WAPS) 30

Physical Layer 30

Cyber Layer 31

WAPS Realized in TrueTime 32

An Illustrative WAPS 33

Illustrative Physical Layer 33

Illustrative Cyber Layer 34

Illustrative Integrated System 36

Settings of Stability Analysis 36

Settings of Delay Predictions 37

Settings of Illustrative WAPS 37

Cases for Illustrative WAPS 38

Hidden Markov Model (HMM)-Based Stability Improvement 38

Online Smith Predictor 38

Initialization of Discrete HMM (DHMM) 39

Parameter Estimation of DHMM 41

Delay Prediction via DHMM 43

Smith Predictor Structure 44

Delay Predictions 44

Settings of DHMM 45

Prediction Comparison 46

Performance of Smith Predictor 47

Settings of Smith Predictor 47

Analysis of Case 1 47

Analysis of Case 2 48

Stability Enhancement of Illustrative WAPS 49

Eigenvalue Analysis and Delay Impact 49

Sensitivity Analysis of Network Parameters 49

Optimal AGC 50

Optimal Controller Performance 50

Scenario 1 Analysis 51

Scenario 2 Analysis 51

Scenario 3 Analysis 52

Scenario 4 Analysis 52

Robustness of Optimal AGC 52

Reliability Analysis of CPSs 65

Conceptual Distributed Generation Systems (DGSs) 65

Mathematical Model of Degraded Network 65

Model of Transmission Delay 66

Model of Packet Dropout 67

Scenarios of Degraded Network 68

Modeling and Simulation of DGSs 69

DGS Model 69

Preliminary Model 69

Power Source Model 70

Data Interpolation 71

Reliability Estimation Via Optimal Power Flow (OPF) 71

Data Prediction 71

Monte Carlo Simulation (MCS) of DGSs 73

OPF of DGSs 74

Actual Cost and Reliability Analysis 75

OPF of DGSs Against Unreliable Network 76

Settings of Networked DGSs 76

OPF Under Different Demand Levels 78

OPF Under Entire Period 79

Maintenance of Aging CPSs 87

Data-driven Degradation Model for CPSs 88

Degraded Control System 88

Parameter Estimation via EM Algorithm 89

Load Frequency Control (LFC) Performance Criteria 90

Maintenance Model and Cost Model 91

Performance Based Maintenance (PBM) Model 91

Cost Model 93

Applications to DGSs 94

Output of Aging Generators 94

Impact of Aging on DGSs 94

Settings of Aging DGSs 94

Validations of Generator Performance Indexes 95

Quantitative Aging Impact 96

Applications to Gas Turbine Plant 98

Settings of Networked DGS Sensitivity Analysis of PBM 98

Impact of Degradation on LFC 98

Numerical Sensitivity Analysis 98

Pictorial Sensitivity Analysis 99

Optimal Maintenance Strategy 100

Maintenance Models Comparison 100

Game Theory Based CPS Protection Plan 109

Vulnerability Model for CPSs 110

Multi-state Attack-Defence Game 111

Backgrounds of Game Model for CPSs 111

Mathematical Game Model 112

Attack Consequence and Optimal Defence 113

Damage Cost Model 113

Attack Uncertainty 114

Optimal Defence Plan 115

Applications to DGSs with Uncertain Cyber-Attacks 116

Settings of Game Model 116

Optimal Protection with Constant Resource Allocation 116

Impact Under Constant Case 116

Optimal Constant Resource Allocation Fraction 117

Optimal Protection with Dynamic Resource Allocation 118

Vulnerability Model Under Dynamic Case 119

Optimal Dynamic Resource Allocation Fraction 120

Optimization Results Justification 121

Bayesian Based Cyberteam Deployment 125

Poisson Distribution based Cyber-attacks 125

Impacts of DoS Attack 125

Poisson Arrival Model Verification 126

Average Arrival Attacks 127

Cost of Multi-node Bandit Model 128

Regret Function of Worst Case 128

Upper Bound on Cost 129

Thompson-Hedge Algorithm 130

Hedge Algorithm 130

Details of Thompson-Hedge Algorithm 131

Separation of Target Regret 132

Upper Bound of Lambda_1 133

Upper Bound of Lambda_2 133

Upper Bound of Regret R^TH 134

Applications to Smart Grids 135

Operation Cost of Smart Grid 135

Numerical Analysis of Cost Sequences 137

Performance of Thompson-Hedge Algorithm 137

Comparison Study Against R.EXP3 137

Sensitivity to the Variation 140

Recent Advances in CPS Modeling, Stability and Reliability 145

Modeling Techniques for CPS Components 145

Inverse Gaussian Process 145

Hitting Time to a Curved Boundary 146

Estimator Error 147

Theoretical Stability Analysis 148

Impacts of Uncertainties 148

Small Gain Theorem based Stability Criteria 149

Robust Stability Criteria 150

Game Model for CPSs 151

References 153

Index 177
Huadong Mo, PhD, is Lecturer in the School of Engineering and Information Technology at the University of New South Wales. He received his doctorate from the City University of Hong Kong in the area of cyber-physical system reliability engineering.

Giovanni Sansavini, PhD, is Associate Professor at the Reliability and Risk Engineering Laboratory, Institute of Energy and Process Engineering, ETH Zurich, Switzerland. He received his doctorate in nuclear engineering in 2010 from Politecnico di Milano, Italy, and a doctorate in engineering mechanics from Virginia Tech in Blacksburg in 2010.

Min Xie, PhD, is Chair Professor of Industrial Engineering in the Department of Advanced Design and Systems Engineering, at City University of Hong Kong. He received his doctorate in Quality Technology in 1987 from Linkoping University in Sweden and was elected as a Fellow of the IEEE in 2006.

M. Xie, National University of Singapore