Cyber-physical systems : decision making mechanisms and applications /

As systems continue to evolve they rely less on human decision-making and more on computational intelligence. This trend in conjunction to the available technologies for providing advanced sensing, measurement, process control, and communication lead towards the new field of Cyber-Physical System (C...

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Bibliographic Details
Call Number:Libro Electrónico
Other Authors: Siozios, Kostas (Editor), Soudris, Dimitrios, 1964- (Editor), Kosmatopoulos, Elias (Editor)
Format: Electronic eBook
Language:Inglés
Published: Gistrup, Denmark : River Publishers, 2017.
Series:River Publishers series in circuits and systems.
Subjects:
Cooperating objects (Computer systems) > Decision making.
Objets coopérants (Systèmes informatiques) > Prise de décision.
Online Access:Texto completo
Table of Contents:
  • Machine generated contents note: 1. Overview of Emerging Systems-Related Concepts, Approaches and Technologies Unifying and Advancing S & T Achievements of the Past Decades (e.g. CPS, IoT, I2oT, SoS/E, 5G and Cross-Cutting Decision Making) / Alkis Konstantellos
  • 1.1. Introduction
  • 1.1.1. Key Survey, Review, Reference Publications and Textbooks
  • 1.1.2. Motivating Example: Air Traffic Management and Collision Avoidance Systems
  • 1.1.3. Success and Failure of Contemporary Systems
  • 1.2. System, Model(s), Many Systems and Their Characterisation
  • 1.2.1. What Is a General System?
  • 1.2.1.1. One system
  • 1.2.1.2. Many systems in an environment
  • 1.2.2. System Characterisations
  • Elementary Abstractions
  • 1.2.2.1. Characterisation through fundamental attributes
  • 1.2.2.2. Characterisation according to the nature of a system
  • 1.2.2.3. intuitive characterisation-profiling scheme for systems
  • 1.3. Specific Systems Classification in Established R & D-S & T Databases
  • 1.3.1. Condensed Outline-Definitions of the New Topics and Initiatives
  • 1.3.2. Sciences, Technologies, Industry and Related Communities
  • 1.4. Evolutionary Paths towards (CPS, IoT, SoS/E) and (Ind 4, Soc 5.0)
  • 1.4.1. S & T Paths Jointly Leading to CPS
  • 1.4.2. S & T Paths Jointly Leading to IoT
  • 1.4.3. S & T Paths Jointly Leading to SoS/SoSE and Independently to Industry 4.0
  • 1.5. CPS in More Detail: Definitions, Challenges, Debates and Synergies
  • 1.5.1. Introductory Examples
  • 1.5.2. Success of the Term CPS and Its "Externalities"
  • 1.5.3. CPS
  • Definitions
  • 1.5.4. What Is Not a CPS?
  • 1.5.5. Same System Can Be Viewed under Different Perspectives and Modelled through Different Methods
  • 1.5.6. Boundaries between Cyber and Physical Parts of a CPS System
  • 1.5.7. Cascading & Nesting of Multiple Cyber, Physical and Complete CPS
  • 1.5.8. Simple Classification-Profiling Tool for CPS
  • 1.5.9. CPS vs. IoT
  • 1.5.10. CPS vs.
  • ICT (Information and Communication Technologies)
  • 1.5.11. Examples of CPS Challenges and Some R & D Directions
  • 1.6. IoT in More Detail and the 5G Mobile Technologies
  • 1.6.1. IoT Applications and Benefits
  • Internet of Everything
  • 1.6.2. On the IoT Definition
  • 1.6.3. Industry Views on IoT and the Industrial IoT (I2oT) by the 12 Consortium
  • 1.6.4. 5th Generation Mobile Technologies (Expected around 2020)
  • 1.7. System of Systems (SoS) and SoS Engineering (SoSE)
  • More Details
  • 1.7.1. System of Systems Examples
  • 1.7.2. Dahmann and Baldwin Types of SoS
  • 1.7.3. Large Scale Systems, Complexity and (Old and New) Cybernetics
  • 1.8. Decision Making: Definitions, Examples, Methods, Interactions with System Design
  • 1.8.1. Scientific, Engineering Aspects
  • Machine and Human Decision Making (DM)
  • 1.8.2. Definitions and Basic Considerations
  • 1.8.3. Motivating DM Example: Football Goal Line Technology
  • 1.8.4. Industrial Examples
  • 1.8.4.1. Same decision making challenges in different industries
  • 1.8.4.2. Elementary process automation DM
  • Decidability cases
  • 1.8.4.3. Decision making and processes in large scale Collision Avoidance systems (CA)
  • 1.8.4.4. Consensus based methods, majority and supermajority voting
  • 1.8.4.5. Human in the loop (HitL)
  • 1.8.5. Sequential Process, CPS and Decision Making
  • 1.8.5.1. General
  • 1.8.5.2. Sequential process examples
  • 1.9. Requirements Engineering and Technology Maturity Levels
  • 1.9.1. Requirements Engineering
  • 1.9.2. Is TRL Sufficient for CPS and SoS/E?
  • 1.10. System of the Future (SoF)
  • Food for Thought
  • 1.10.1. Dreams and Visions of the Systems R & D Communities
  • 1.10.2. System of the Future (SoF)
  • 1.10.3. Further Examples of Systems Topics for Future R & D Activities
  • 1.11. Concluding Remarks
  • 1.12. Summary
  • Acknowledgment
  • References
  • 2. On Designing Decision-Making Mechanisms for Cyber-Physical Systems / Elias Kosmatopoulos
  • 2.1. Introduction
  • 2.2. Related Work for Designing CPS Platforms
  • 2.3. Conclusions
  • References
  • 3. Design Space Exploration Methodology Based on Decision Trees for Cyber-Physical Systems / Dimitrios Soudris
  • 3.1. Methodology
  • 3.1.1. Design Options
  • 3.1.2. Constraints
  • 3.1.3. Interdependencies
  • 3.1.4. Methodology Flow
  • 3.2. Demonstration of the Methodology
  • 3.2.1. DSE on Concurrent Data Structures
  • 3.2.2. DSE on Multiway Streaming Aggregation
  • 3.3. Conclusion
  • References
  • 4. PReDiCt: A Scenario-based Methodology for Realizing Decision-Making Mechanisms Targeting Cyber-Physical Systems / Dimitrios Soudris
  • 4.1. PReDiCt Framework
  • 4.1.1. Step 1: Requirements
  • 4.1.2. Step 2: System Design
  • 4.1.3. Step 3: System Modeling
  • 4.1.4. Step 4: Run-Time Situation (RTS) Definition
  • 4.1.5. Step 5: Scenario Clustering
  • 4.1.6. Step 6: Decision Making
  • 4.1.7. Step 7: System Verification
  • 4.2. Employed Use Case
  • 4.2.1. Applying the Proposed Framework
  • 4.3. Experimental Results
  • 4.3.1. Hardware Implementation of Decision Making
  • 4.4. Conclusion
  • References
  • 5. Studying Fault Tolerance Aspects / Kostas Siozios
  • 5.1. Introduction
  • 5.2. Definition of Faults and Fault-Tolerance
  • 5.3. Overview of Wear-out Mechanisms
  • 5.4. Classication of Faults
  • 5.5. Countermeasures for a Fault-Tolerant System
  • 5.5.1. Fault Avoidance
  • 5.5.2. Fault Detection
  • 5.5.3. Containment
  • 5.5.4. Isolation
  • 5.5.5. Recovery
  • 5.6. Improving Fault Masking with Redundancy
  • 5.7. Fault Forecasting
  • 5.8. Conclusion
  • References
  • 6. Framework for Research and Prototyping in Robotics: From Ideas to Software and Hardware Development / Evangelos Papadopoulos
  • 6.1. Introduction
  • 6.2. Framework for Simulation and Prototyping
  • 6.2.1. Modeling, Dynamics, and Simulation
  • 6.2.1.1. Dynamics derivation and simulation methods
  • 6.2.1.2. Modeling the environment
  • 6.2.2. System Development: Hardware and Software
  • 6.2.2.1. Introduction
  • 6.2.2.2. automation pyramid
  • 6.2.2.3. OSI model and Media Access Control (MAC) methods
  • 6.2.2.4. Networked Control System design
  • 6.2.2.5. Switched Ethernet and determinism
  • 6.2.2.6. Quality of Service (QoS)
  • 6.2.2.7. Latency in switched Ethernet
  • 6.2.2.8. Message exchange using Ethernet, IP, and UDP
  • 6.2.2.9. Network layer: The Internet Protocol
  • 6.2.2.10. Transport layer: The User Datagram Protocol
  • 6.2.2.11. Application layer
  • 6.2.2.12. Software design for the MCU node
  • 6.2.2.13. Software design for the ROS computer
  • 6.3. Application Experiments
  • 6.3.1. Treadmill Control
  • 6.3.1.1. System description
  • 6.3.1.2. Software design: MCU side
  • 6.3.1.3. Software design: ROS side
  • 6.3.1.4. Hardware experiment
  • 6.3.2. Single Actuated Hopping Robot (SAHR)
  • 6.3.2.1. Robot description
  • 6.3.2.2. Software design: MCU side
  • 6.3.2.3. Software design: ROS side
  • 6.3.2.4. Simulation experiment
  • 6.3.2.5. Hardware experiment
  • 6.3.2.6. Simulations on interactions with terrains
  • 6.4. Conclusions
  • Acknowledgment
  • References
  • 7. Modeling Control Mechanisms in MATLAB / Kostas Siozios
  • 7.1. Introduction
  • 7.2. MATLAB Control System Toolbox
  • 7.3. Overview of Commands for the Control System Toolbox
  • 7.4. Examples of Designing Control Systems at MATLAB
  • 7.4.1. Example 7.1
  • 7.4.2. Example 7.2
  • 7.4.3. Example 7.3
  • 7.4.4. Example 7.4
  • 7.4.5. Example 7.5
  • 7.4.6. Example 7.6
  • 7.4.7. Example 7.7
  • 7.4.8. Example 7.8
  • 7.4.9. Example 7.9
  • 7.4.10. Example 7.10
  • 7.4.11. Example 7.11
  • 7.4.12. Example 7.12
  • 7.4.13. Example 7.13
  • 7.4.14. Example 7.14
  • 7.4.15. Example 7.15
  • 7.4.16. Example 7.16
  • 7.4.17. Example 7.17
  • 7.4.18. Example 7.18
  • 8. Overview of R & D Projects and Support Actions in Relevant Topics / Alkis Konstantellos
  • 8.1. Road-Mapping Projects on CPS, IoT, SoS, Combined CPS
  • SoS and Related Technologies
  • 8.2. Systems Related Foundations and Novel Concepts
  • 8.3. Cross-Layer Programming
  • 8.4. Systems of Systems and CPS
  • 8.5. Control and Optimization in CPS and SoS
  • 8.6. CPS Modeling, Design, Methods, and Tools
  • 8.7. CPS Security, Safety, Trust, and Testing
  • 8.8. CPS Verification
  • 8.9. CPS Platforms
  • 8.10. CPS and Manufacturing
  • 8.11. Industry 4.0 and CPS
  • 8.12. IoT and Underpinning Challenges
  • 8.13. International Cooperation
  • Examples
  • 8.14. Decision Making (Methods Applied)
  • 8.15. Decision Processes
  • Human in the Loop
  • 8.16. Collision Avoidance (CA) Including ACAS-X
  • 8.17. Concluding Comments
  • Acknowledgment
  • References.

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