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Networked Control Systems: Cloud Control and Secure Control [Pehme köide]

(Distinguished Professor, Systems Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia), (Professor, School of Automation, Beijing Institute of Technology, Beijing, China)
  • Formaat: Paperback / softback, 502 pages, kõrgus x laius: 229x152 mm, kaal: 790 g
  • Ilmumisaeg: 15-Feb-2019
  • Kirjastus: Butterworth-Heinemann Inc
  • ISBN-10: 0128161191
  • ISBN-13: 9780128161197
Teised raamatud teemal:
Networked Control Systems: Cloud Control and Secure ControlSuurem pilt
  • Formaat: Paperback / softback, 502 pages, kõrgus x laius: 229x152 mm, kaal: 790 g
  • Ilmumisaeg: 15-Feb-2019
  • Kirjastus: Butterworth-Heinemann Inc
  • ISBN-10: 0128161191
  • ISBN-13: 9780128161197
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780128161197.html
Märksõnad:

Networked Control Systems: Cloud Control and Secure Control explores new technological developments in networked control systems (NCS), including new techniques, such as event-triggered, secure and cloud control. It provides the fundamentals and underlying issues of networked control systems under normal operating environments and under cyberphysical attack. The book includes a critical examination of the principles of cloud computing, cloud control systems design, the available techniques of secure control design to NCS’s under cyberphysical attack, along with strategies for resilient and secure control of cyberphysical systems. Smart grid infrastructures are also discussed, providing diagnosis methods to analyze and counteract impacts.

Finally, a series of practical case studies are provided to cover a range of NCS’s. This book is an essential resource for professionals and graduate students working in the fields of networked control systems, signal processing and distributed estimation.

  • Provides coverage of cloud-based approaches to control systems and secure control methodologies to protect cyberphysical systems against various types of malicious attacks
  • Provides an overview of control research literature and explores future developments and solutions
  • Includes case studies that offer solutions for issues with modeling, quantization, packet dropout, time delay and communication constraints
About the Authors xv
Acknowledgments xvii
Preface xix
1 An Overview 1(36)
1.1 Introduction
1(1)
1.2 Networked Control Systems: Challenges
1(7)
1.2.1 Basic Classification
4(1)
1.2.2 Main Features
5(3)
1.3 Current Key Ingredients
8(12)
1.3.1 Control of Networks
10(1)
1.3.2 Control Over Networks
11(1)
1.3.3 Delay Characteristics
11(2)
1.3.4 Data Loss
13(3)
1.3.5 Quantization and Coding
16(1)
1.3.6 QoS and Control
16(1)
1.3.7 Multiagent Systems
17(1)
1.3.8 Internet-Based Control
17(3)
1.4 Internet-of-Things
20(3)
1.4.1 Architecture
21(1)
1.4.2 Knowledge and Big Data
21(1)
1.4.3 Robustness
22(1)
1.4.4 Standardizations
22(1)
1.5 Cyberphysical Systems
23(9)
1.5.1 Progress Ahead
24(1)
1.5.2 Basic Features
25(1)
1.5.3 Cyberphysical Attacks
26(1)
1.5.4 Detection Methods
27(1)
1.5.5 Robustness, Resilience and Security
28(1)
1.5.6 Multilayer Systems
29(3)
1.6 Notes
32(1)
References
33(4)
2 Networked Control Systems' Fundamentals 37(54)
2.1 Modeling of NCS
38(15)
2.1.1 Quantization Errors
39(3)
2.1.2 Packet Dropouts
42(6)
2.1.3 Variable Sampling/Transmission Intervals
48(1)
2.1.4 Variable Transmission Delays
49(3)
2.1.5 Communication Constraints
52(1)
2.2 Control Approaches Over Networks
53(19)
2.2.1 Input Delay System Approach
53(5)
2.2.2 Markovian System Approach
58(2)
2.2.3 Switched System Approach
60(5)
2.2.4 Stochastic System Approach
65(2)
2.2.5 Impulsive System Approach
67(2)
2.2.6 Predictive Control Approach
69(3)
2.3 Advanced Issues in NCS
72(6)
2.3.1 Decentralized and Distributed NCS
72(1)
2.3.2 Event-Triggered Schemes
73(1)
2.3.3 Cloud Control System
74(3)
2.3.4 Co-Design in NCS
77(1)
2.4 Notes
78(1)
References
78(13)
3 Cloud Computing 91(36)
3.1 Introduction
91(1)
3.2 Overview of Cloud Computing
92(2)
3.2.1 Definitions
92(1)
3.2.2 Related Technologies
93(1)
3.3 Cloud Computing Architecture
94(4)
3.3.1 A Layered Model of Cloud Computing
94(1)
3.3.2 Business Model
95(1)
3.3.3 Types of Clouds
96(2)
3.4 Integrating CPS With the Cloud
98(1)
3.5 Cloud Computing Characteristics
98(9)
3.5.1 State-of-the-Art
100(1)
3.5.2 Cloud Computing Technologies
100(1)
3.5.3 Architectural Design of Data Centers
100(2)
3.5.4 Distributed File System Over Clouds
102(1)
3.5.5 Distributed Application Framework Over Clouds
103(1)
3.5.6 Commercial Products
103(1)
3.5.7 Microsoft Windows Azure Platform
104(3)
3.6 Addressed Challenges
107(5)
3.6.1 Automated Service Provisioning
107(1)
3.6.2 Virtual Machine Migration
108(1)
3.6.3 Server Consolidation
108(1)
3.6.4 Energy Management
109(1)
3.6.5 Traffic Management and Analysis
109(1)
3.6.6 Data Security
110(1)
3.6.7 Software Frameworks
110(1)
3.6.8 Storage Technologies and Data Management
111(1)
3.6.9 Novel Cloud Architectures
111(1)
3.7 Progress of Cloud Computing
112(5)
3.7.1 The Major Providers
114(1)
3.7.2 Control in the Cloud
114(1)
3.7.3 PLC as a Service
115(1)
3.7.4 Historian as a Service
116(1)
3.7.5 HMI as a Service
116(1)
3.7.6 Control as a Service
117(1)
3.8 Cloud-Based Manufacturing
117(3)
3.8.1 Cloud-Based Services
118(1)
3.8.2 Conceptual Framework
119(1)
3.9 Notes
120(2)
References
122(5)
4 Control From the Cloud 127(40)
4.1 Introduction
127(1)
4.2 Towards Controlling From the Cloud
128(15)
4.2.1 Overview
128(3)
4.2.2 Wireless Control Systems
131(1)
4.2.3 ,Basic Classification
132(1)
4.2.4 Remote Control Systems
133(2)
4.2.5 Some Prevailing Challenges
135(1)
4.2.6 Reflections on Industrial Automation
136(3)
4.2.7 Quality-of-Service (QoS)
139(1)
4.2.8 Preliminary Control Models
140(3)
4.3 Cloud Control Systems
143(19)
4.3.1 Introduction
144(1)
4.3.2 Model Based Networked Control Systems
145(3)
4.3.3 Data Driven Networked Control Systems Design
148(1)
4.3.4 Networked Multiagent Systems
149(2)
4.3.5 Control of Complex Systems
151(2)
4.3.6 Cloud Control System Concepts
153(2)
4.3.7 A Rudiment of Cloud Control Systems
155(4)
4.3.8 Cooperative Cloud Control
159(3)
4.4 Notes
162(1)
References
162(5)
5 Secure Control Design Techniques 167(92)
5.1 Introduction
167(8)
5.1.1 Security Goals
168(1)
5.1.2 Workflow Within CPS
169(1)
5.1.3 Summary of Attacks
170(2)
5.1.4 Robust Networked Control Systems
172(1)
5.1.5 Resilient Networked Systems Under Attacks
173(2)
5.2 Time-Delay Switch Attack
175(17)
5.2.1 Introduction
176(1)
5.2.2 Model Setup
176(4)
5.2.3 Control Methodology
180(5)
5.2.4 Procedure for Controller Design
185(1)
5.2.5 Simulation Example 5.1
186(1)
5.2.6 Simulation Example 5.2
187(1)
5.2.7 Simulation Example 5.3
188(2)
5.2.8 Simulation Example 5.4
190(2)
5.3 Security Control Under Constraints
192(19)
5.3.1 Problem Formulation
193(2)
5.3.2 A Binary Framework
195(7)
5.3.3 An Mary Framework
202(2)
5.3.4 Terminal State With a Continuous Distribution
204(4)
5.3.5 Simulation Example 5.5
208(3)
5.4 Lyapunov-Based Methods Under Denial-of-Service
211(15)
5.4.1 Networked Distributed System
211(1)
5.4.2 DoS Attacks' Frequency and Duration
212(1)
5.4.3 A Small-Gain Approach for Networked Systems
213(4)
5.4.4 Stabilization of Distributed Systems Under DoS
217(3)
5.4.5 A Hybrid Transmission Strategy
220(1)
5.4.6 Zeno-Free Event-Triggered Control in the Absence of DoS
220(2)
5.4.7 Hybrid Transmission Strategy Under DoS
222(2)
5.4.8 Simulation Example 5.6
224(1)
5.4.9 Simulation Example 5.7
225(1)
5.5 Stabilizing Secure Control
226(25)
5.5.1 Process Dynamics and Ideal Control Action
228(1)
5.5.2 DoS and Actual Control Action
229(1)
5.5.3 Control Objectives
230(1)
5.5.4 Stabilizing Control Update Policies
231(4)
5.5.5 Time-Constrained DoS
235(1)
5.5.6 ISS Under Denial-of-Service
236(11)
5.5.7 Simulation Example 5.8
247(1)
5.5.8 Simulation Example 5.9
247(1)
5.5.9 Simulation Example 5.10
248(1)
5.5.10 Simulation Example 5.11
249(2)
5.6 Notes
251(2)
References
253(6)
6 Case Studies 259(56)
6.1 Hybrid Cloud-Based SCADA Approach
259(8)
6.1.1 Cloud-Based SCADA Concept
260(3)
6.1.2 Architecture Adaptation
263(3)
6.1.3 Risk Evaluation
266(1)
6.2 Smart Grid Under Time Delay Switch Attacks
267(21)
6.2.1 System Model
267(3)
6.2.2 Time-Delay Attack
270(2)
6.2.3 TDS Attack as Denial-of-Service (DoS) Attack
272(2)
6.2.4 A Crypto-Free TDS Recovery Protocol
274(1)
6.2.5 Decision Making Unit (DMU)
275(1)
6.2.6 Delay Estimator Unit (DEU)
276(2)
6.2.7 Stability of the LFC Under TDS Attack
278(1)
6.2.8 Simulation Example 6.1
279(9)
6.3 Multisensor Track Fusion-Based Model Prediction
288(21)
6.3.1 State Representation of Observation Model
291(1)
6.3.2 Electromechanical Oscillation Model Formulation
292(1)
6.3.3 Initial Correlation Information
293(3)
6.3.4 Computation of Crosscovariance
296(3)
6.3.5 Moving Horizon Estimate
299(1)
6.3.6 Track Fusion Center
300(1)
6.3.7 Evaluation of Residuals
301(1)
6.3.8 N$imulation Studies
302(7)
6.4 Notes
309(2)
References
311(4)
7 Smart Grid Infrastructures 315(36)
7.1 Cyberphysical Security
315(14)
7.1.1 Introduction
315(1)
7.1.2 Pricing and Generation
316(1)
7.1.3 Cyberphysical Approach to Smart Grid Security
317(2)
7.1.4 System Model
319(1)
7.1.5 Cybersecurity Requirements
320(1)
7.1.6 Attack Model
321(4)
7.1.7 Countermeasures
325(4)
7.2 System Theoretic Approaches
329(11)
7.2.1 System Model
329(1)
7.2.2 Security Requirements
330(1)
7.2.3 Attack Model
331(1)
7.2.4 Countermeasures
331(1)
7.2.5 Needs for Cyberphysical Security
332(2)
7.2.6 Typical Cases
334(1)
7.2.7 Defense Against Replay Attacks
334(3)
7.2.8 Cybersecurity Investment
337(3)
7.3 Wide-Area Monitoring, Protection and Control
340(5)
7.3.1 Introduction
341(1)
7.3.2 Wide-Area Monitoring, Protection and Control
341(2)
7.3.3 Cyberattack Taxonomy
343(1)
7.3.4 Cyberattack Classification
344(1)
7.3.5 Coordinated Attacks on WAMPAC
345(1)
7.4 Notes
345(2)
References
347(4)
8 Secure Resilient Control Strategies 351(38)
8.1 Basis for Resilient Cyberphysical System
351(2)
8.1.1 Networked Control System Models
352(1)
8.2 Resilient Design Approach
353(14)
8.2.1 Introduction
354(1)
8.2.2 Background
355(1)
8.2.3 Problem Statement
356(1)
8.2.4 System Model
357(1)
8.2.5 Attack Monitor
357(3)
8.2.6 Switching the Controller
360(4)
8.2.7 Simulation Example 8.1
364(3)
8.3 Remote State Estimation Under DoS Attacks
367(17)
8.3.1 Introduction
368(2)
8.3.2 Problem Setup
370(1)
8.3.3 Process and Sensor Model
370(1)
8.3.4 Multichannel Communication and Attack Model
371(1)
8.3.5 Remote State Estimation
372(1)
8.3.6 Problem of Interest
372(1)
8.3.7 Stochastic Game Framework
373(3)
8.3.8 Markov Chain Model
376(1)
8.3.9 Extension to Power-Level Selection
377(1)
8.3.10 Equilibrium Analysis
377(1)
8.3.11 Learning Methodology
378(3)
8.3.12 Simulations Example 8.2
381(3)
8.4 Notes
384(1)
References
385(4)
9 Cyberphysical Security Methods 389(68)
9.1 A Generalized Game Theoretic Approach
389(25)
9.1.1 Physical Layer Control Problem
391(1)
9.1.2 Cyberstrategy
392(1)
9.1.3 Perfect-State Feedback Control
393(3)
9.1.4 Cyberlayer Defense System
396(2)
9.1.5 Linear Quadratic Problem
398(2)
9.1.6 Cascading Failures
400(2)
9.1.7 Games-in-Games Structure
402(1)
9.1.8 Simulation Example 9.1
403(3)
9.1.9 Defense Against Denial-of-Service Attack
406(1)
9.1.10 Control System Model
406(1)
9.1.11 Intrusion Detection Systems
407(3)
9.1.12 Crosslayer Control Design
410(2)
9.1.13 Simulation Example 11.2
412(1)
9.1.14 Linear Programming for Computing Saddle-Point Equilibrium
413(1)
9.2 Game-Theoretic Approach
414(18)
9.2.1 Introduction
414(2)
9.2.2 Model of NCS Subject to DoS Attack
416(1)
9.2.3 Optimal Tasking Design
417(1)
9.2.4 Defense and Attack Strategy Design
418(1)
9.2.5 Tasking Control Strategies
419(3)
9.2.6 Defense and Attack Strategies
422(1)
9.2.7 Development of Defense Strategies
423(1)
9.2.8 Development of Attack Strategies
424(2)
9.2.9 Model Description
426(1)
9.2.10 Strategy Design
427(1)
9.2.11 Robustness Study
428(1)
9.2.12 COmparative Study
429(1)
9.2.13 Verification
430(2)
9.3 Convex Optimization Problems
432(17)
9.3.1 Introduction
433(2)
9.3.2 Cybermission Damage Model
435(1)
9.3.3 Known Mission Damage Data
436(4)
9.3.4 Unknown Mission Damage Data
440(2)
9.3.5 iCTF Competition
442(1)
9.3.6 2011 iCTF
442(2)
9.3.7 Actions Available to Every Team
444(1)
9.3.8 Optimization Schemes and iCTF
445(1)
9.3.9 iCTF Results
446(3)
9.4 Notes
449(4)
References
453(4)
A Appendix 457(18)
A.1 Preliminaries and Notations
457(2)
A.2 A Brief of Game Theory
459(6)
A.2.1 A Short Review
459(1)
A.2.2 General Game Model and Equilibrium Concept
460(1)
A.2.3 A Stochastic Game Formulation
461(2)
A.2.4 Minimax Theorem
463(2)
A.3 Gateaux Differential
465(1)
A.4 Linear Matrix Inequalities
466(4)
A.4.1 Basics
466(1)
A.4.2 Some Standard Problems
467(2)
A.4.3 The S-Procedure
469(1)
A.5 Some Lyapunov-Krasovskii Functionals
470(1)
A.6 Some Formulae for Matrix Inverses
470(2)
A.6.1 Inverses of Block Matrices
471(1)
A.6.2 Matrix Inversion Lemma
472(1)
A.7 Partial Differentiation
472(1)
References
473(2)
Index 475
Magdi S. Mahmoud is a distinguished professor at King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia. He has been faculty member at different universities worldwide including Egypt (CU, AUC), Kuwait (KU), UAE (UAEU), UK (UMIST), USA (Pitt, Case Western), Singapore (Nanyang), and Australia (Adelaide). He lectured in Venezuela (Caracas), Germany (Hanover), UK (Kent), USA (UoSA), Canada (Montreal) and China (BIT, Yanshan). He is the principal author of 51 books, inclusive book-chapters, and author/co-author of more than 610 peer-reviewed papers. He is a fellow of the IEE and a senior member of the IEEE, the CEI (UK). He is currently actively engaged in teaching and research in the development of modern methodologies to distributed control and filtering, networked control systems, fault-tolerant systems, cyberphysical systems, and information technology. Yuanqing Xia has worked in the Department of Automatic Control, Beijing Institute of Technology, Beijing, since 2004, first as an associate professor, and, since 2008, as a professor. He is a Yangtze River Scholar and Chair Professor of the Beijing Institute of Technology since 2016. His current research interests are in the fields of networked control systems, robust control, sliding mode control, active disturbance rejection control, biomedical signal processing, and cloud control systems.