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Cyber-physical distributed systems : modeling, reliability analysis and applications /

Bibliographic Details
Main Authors: Mo, Huadong (Author), Sansavini, Giovanni (Author), Xie, Min (Author)
Corporate Author: EBSCOhost
Format: eBook
Language:English
Published: Hoboken, NJ : John Wiley & Sons, Inc., 2021.
Subjects:
Internet of things > Simulation methods.
Cooperating objects (Computer systems) > Simulation methods.
Electronic data processing > Distributed processing > Simulation methods.
Internet des objets > Méthodes de simulation.
Objets coopérants (Systèmes informatiques) > Méthodes de simulation.
Traitement réparti > Méthodes de simulation.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Cover
  • Title Page
  • Copyright Page
  • Contents
  • Preface
  • Acronyms and Abbreviations
  • Chapter 1 Introduction
  • 1.1 Challenges of Traditional Physical and Cyber Systems
  • 1.2 Research Trends of CPSs
  • 1.2.1 Stability of CPSs
  • 1.2.2 Reliability of CPSs
  • 1.3 Opportunities for CPS Applications
  • 1.3.1 Managing Reliability and Feasibility of CPSs
  • 1.3.2 Ensuring Cybersecurity of CPSs
  • Chapter 2 Fundamentals of CPSs
  • 2.1 Models for Exploring CPSs
  • 2.1.1 Control-Block-Diagram for CPSs
  • 2.1.1.1 Control Signal in CPSs
  • 2.1.1.2 Degraded Actuator and Sensor
  • 2.1.1.3 Time-Varying Model of CPSs
  • 2.1.2 Implementation in TrueTime Simulator
  • 2.1.2.1 Introduction of TrueTime Simulator
  • 2.1.2.2 Architectures of CPSs in TrueTime
  • 2.2 Evaluation and Verification of CPSs
  • 2.2.1 CPS Performance Evaluation
  • 2.2.1.1 CPS Performance Index
  • 2.2.1.2 Reliability Evaluation of CPSs
  • 2.2.2 CPS Model Verification
  • 2.3 CPS Performance Improvement
  • 2.3.1 PSO-Based Reliability Enhancement
  • 2.3.2 Optimal PID-AGC
  • Chapter 3 Stability Enhancement of CPSs
  • 3.1 Integration of Physical and Cyber Models
  • 3.1.1 Basics of WAPS
  • 3.1.1.1 Physical Layer
  • 3.1.1.2 Cyber Layer
  • 3.1.1.3 WAPS Realized in TrueTime
  • 3.1.2 An Illustrative WAPS
  • 3.1.2.1 Illustrative Physical Layer
  • 3.1.2.2 Illustrative Cyber Layer
  • 3.1.2.3 Illustrative Integrated System
  • 3.2 Settings of Stability Analysis
  • 3.2.1 Settings for Delay Predictions
  • 3.2.2 Settings for Illustrative WAPS
  • 3.2.3 Cases for Illustrative WAPS
  • 3.3 HMM-Based Stability Improvement
  • 3.3.1 On-line Smith Predictor
  • 3.3.1.1 Initialization of DHMM
  • 3.3.1.2 Parameter Estimation of DHMM
  • 3.3.1.3 Delay Prediction via DHMM
  • 3.3.1.4 Smith Predictor Structure
  • 3.3.2 Delay Predictions
  • 3.3.2.1 Settings of DHMM
  • 3.3.2.2 Prediction Comparison.
  • 3.3.3 Performance of Smith Predictor
  • 3.3.3.1 Settings of Smith Predictor
  • 3.3.3.2 Analysis of Case 1
  • 3.3.3.3 Analysis of Case 2
  • 3.4 Stability Enhancement of Illustrative WAPS
  • 3.4.1 Eigenvalue Analysis and Delay Impact
  • 3.4.2 Sensitivity Analysis of Network Parameters
  • 3.4.3 Optimal AGC
  • 3.4.3.1 Optimal Controller Performance
  • 3.4.3.2 Scenario 1 Analysis
  • 3.4.3.3 Scenario 2 Analysis
  • 3.4.3.4 Scenario 3 Analysis
  • 3.4.3.5 Scenario 4 Analysis
  • 3.4.3.6 Robustness of Optimal AGC
  • Chapter 4 Reliability Analysis of CPSs
  • 4.1 Conceptual DGSs
  • 4.2 Mathematical Model of Degraded Network
  • 4.2.1 Model of Transmission Delay
  • 4.2.2 Model of Packet Dropout
  • 4.2.3 Scenarios of Degraded Network
  • 4.3 Modeling and Simulation of DGSs
  • 4.3.1 DGS Model
  • 4.3.1.1 Preliminary Model
  • 4.3.1.2 Power Source Model
  • 4.3.2 Data Interpolation
  • 4.4 Reliability Estimation Via OPF
  • 4.4.1 Data Prediction
  • 4.4.2 MCS of DGSs
  • 4.4.3 OPF of DGSs
  • 4.4.4 Actual Cost and Reliability Analysis
  • 4.5 OPF of DGSs Against Unreliable Network
  • 4.5.1 Settings of Networked DGSs
  • 4.5.2 OPF Under Different Demand Levels
  • 4.5.3 OPF Under Entire Period
  • Chapter 5 Maintenance of Aging CPSs
  • 5.1 Data-driven Degradation Model for CPSs
  • 5.1.1 Degraded Control System
  • 5.1.2 Parameter Estimation via EM Algorithm
  • 5.1.3 LFC Performance Criteria
  • 5.2 Maintenance Model and Cost Model
  • 5.2.1 PBM Model
  • 5.2.2 Cost Model
  • 5.3 Applications to DGSs
  • 5.3.1 Output of Aging Generators
  • 5.3.2 Impact of Aging on DGSs
  • 5.3.2.1 Settings of Aging DGSs
  • 5.3.2.2 Validations of Generator Performance Indexes
  • 5.3.2.3 Quantitative Aging Impact
  • 5.4 Applications to Gas Turbine Plant
  • 5.4.1 Sensitivity Analysis of PBM
  • 5.4.1.1 Impact of Degradation on LFC
  • 5.4.1.2 Numerical Sensitivity Analysis.
  • 5.4.1.3 Pictorial Sensitivity Analysis
  • 5.4.2 Optimal Maintenance Strategy
  • 5.4.3 Maintenance Models Comparison
  • Chapter 6 Game Theory Based CPS Protection Plan
  • 6.1 Vulnerability Model for CPSs
  • 6.2 Multi-state Attack-Defence Game
  • 6.2.1 Backgrounds of Game Model for CPSs
  • 6.2.2 Mathematical Game Model
  • 6.3 Attack Consequence and Optimal Defence
  • 6.3.1 Damage Cost Model
  • 6.3.2 Attack Uncertainty
  • 6.3.3 Optimal Defence Plan
  • 6.4 Applications to Distributed Generation Systems (DGSs) with Uncertain Cyber-attacks
  • 6.4.1 Settings of Game Model
  • 6.4.2 Optimal Protection with Constant Resource Allocation
  • 6.4.2.1 Impact Under Constant Case
  • 6.4.2.2 Optimal Constant Resource Allocation Fraction
  • 6.4.3 Optimal Protection with Dynamic Resource Allocation
  • 6.4.3.1 Vulnerability Model Under Dynamic Case
  • 6.4.3.2 Optimal Dynamic Resource Allocation Fraction
  • 6.4.3.3 Optimization Results Justification
  • Chapter 7 Bayesian Based Cyberteam Deployment
  • 7.1 Poisson Distribution based Cyber-attacks
  • 7.1.1 Impacts of DoS Attack
  • 7.1.2 Poisson Arrival Model Verification
  • 7.1.3 Average Arrival Attacks
  • 7.2 Cost of MNB Model
  • 7.2.1 Regret Function of Worst Case
  • 7.2.2 Upper Bound on Cost
  • 7.3 Thompson-Hedge Algorithm
  • 7.3.1 Hedge Algorithm
  • 7.3.2 Details of Thompson-Hedge Algorithm
  • 7.3.2.1 Separation of Target Regret
  • 7.3.2.2 Upper Bound of .1
  • 7.3.2.3 Upper Bound of .2
  • 7.3.2.4 Upper Bound of Regret RTH
  • 7.4 Applications to Smart Grids
  • 7.4.1 Operation Cost of Smart Grids
  • 7.4.2 Numerical Analysis of Cost Sequences
  • 7.5 Performance of Thompson-Hedge Algorithm
  • 7.5.1 Comparison Study Against R.EXP3
  • 7.5.2 Sensitivity to the Variation
  • Chapter 8 Recent Advances in CPS Modeling, Stability and Reliability
  • 8.1 Modeling Techniques for CPS Components
  • 8.1.1 Inverse Gaussian Process.
  • 8.1.2 Hitting Time to a Curved Boundary
  • 8.1.3 Estimator Error
  • 8.2 Theoretical Stability Analysis
  • 8.2.1 Impacts of Uncertainties
  • 8.2.2 Small Gain Theorem based Stability Criteria
  • 8.2.3 Robust Stability Criteria
  • 8.3 Game Model for CPSs
  • References
  • Index
  • EULA.