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Cyber-Physical Systems

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Sinem Coleri Ergen
Sinem Coleri Ergen

Wireless Networked Control Systems (WNCSs) are spatially distributed systems in which sensors, actuators, and controllers connect through a wireless network instead of traditional point-to-point links. WNCSs have a tremendous potential to improve the efficiency of many large-scale distributed systems in industrial automation, building automation, automated highway, air transportation, and smart grid. Transmitting sensor measurements and control commands over wireless links provide many benefits such as the ease of installation and maintenance, low complexity and cost, and large flexibility to accommodate the modification and upgrade of the components in many control applications. Several industrial organizations, such as International Society of Automation (ISA), Highway Addressable Remote Transducer (HART), and Wireless In- dustrial Networking Alliance (WINA), have been actively pushing the application of wireless technologies in the control applications. Building a WNCS is very challenging since control systems often have stringent requirements on timing and reliability, which are difficult to attain by wireless sensor networks due to the adverse properties of the wireless communication and limited battery resources of the nodes. We provide a framework for the joint optimization of controller and communication systems encompassing efficient abstractions of both systems.

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Towards Energy Efficient and Robust Cyber-Physical Systems Sinem Coleri Ergen Wireless Networks Laboratory, Electrical and Electronics Engineering, Koc University
Cyber-Physical Systems  System of collaborating computational elements controlling physical entities
Joint Design of Control and Communication Systems
Wireless Networked Control Systems  Sensors, actuators and controllers connect through a wireless network
Wireless Networked Control Systems  Benefits of wireless  Ease of installation and maintenance  Low complexity and cost  Large flexibility to accommodate modification and upgrade of components  Backed up by several industrial organizations  International Society of Automation (ISA)  Highway Addressable Remote Transducer (HART)  Wireless Industrial Networking Alliance (WINA)
Trade-off for Communication and Control Systems  Wireless communication system  Non-zero packet error probability Unreliability of wireless transmissions  Non-zero delay Packet transmission and shared wireless medium  Sampling and quantization errors Signals transmitted via packets  Limited battery resources  Control system  Stringent requirements on timing and reliability  Smaller packet error probability, delay and sampling period  Better control system performance  More energy consumed in wireless communication
Outline  Optimization of communication system given requirements of control system  Novel design of scheduling algorithms  Joint optimization of control and communication systems  Novel abstractions for control systems
Outline  Optimization of communication system given requirements of control system  Novel design of scheduling algorithms  Joint optimization of control and communication systems  Novel abstractions for control systems
Novel Scheduling Algorithm Design  Packet generation period, transmission delay and reliability requirements:  Network Control Systems  sensor data -> real-time control of mechanical parts  Fixed determinism better than bounded determinism in control systems (Tl ,dl ,rl )
Novel Scheduling Algorithm Design  Adaptivity requirement  Nodes should be scheduled as uniformly as possible EDF Uniform
Novel Scheduling Algorithm Design  Adaptivity requirement  Nodes should be scheduled as uniformly as possible 1 EDF Uniform
Novel Scheduling Algorithm Design  Adaptivity requirement  Nodes should be scheduled as uniformly as possible 2 EDF Uniform
Novel Scheduling Algorithm Design  Adaptivity requirement  Nodes should be scheduled as uniformly as possible 3 EDF Uniform
Medium Access Control Layer: System Model (Tl ,dl ,rl ) T1 £ T2 £ ... £ TL  given for each link l   Choose subframe length as for uniform allocation  Assume is an integer: Allocate every subframes  Uniform distribution minimize max subframe active time Ti /T1 = si T1 si º EDF Uniform max active time=0.9ms max active time=0.6ms ✓
Example Optimization Problem Formulation Maximum active time of subframes Periodic packet generation Delay requirement Energy requirement Maximum allowed power by UWB regulations Transmission time Transmission rate of UWB for no concurrent transmission case
Outline  Optimization of communication system given requirements of control system  Novel design of scheduling algorithms  Joint optimization of control and communication systems  Novel abstractions for control systems
Abstractions of Control System  Maximum Allowable Transfer Interval (MATI): maximum allowed time interval between subsequent state vector reports from the sensor nodes to the controller  Maximum Allowable Delay (MAD): maximum allowed packet delay for the transmission from the sensor node to the controller MAD MATI Hard real-time guarantee not possible for wireless -> Packet error probability >0 at any point in time
Abstractions of Control System  Stochastic MATI: keep time interval between subsequent state vector reports above MATI with a predefined probability to guarantee the stability of control systems  Many control applications and standards already use it  Industrial automation  IEEE 802.15.4e  Air transportation systems  Cooperative vehicular safety  Never been used in the joint optimization of control and communication systems
Example Optimization Problem Formulation Total energy consumption Schedulability constraint Stochastic MATI constraint MAD constraint Maximum transmit power constraint
Publications  Y. Sadi, S. C. Ergen and P. Park, "Minimum Energy Data Transmission for Wireless Networked Control Systems", IEEE Transactions on Wireless Communications, vol. 13, no. 4, pp. 2163-2175, April 2014. [pdf | link]  Y. Sadi and S. C. Ergen, “Optimal Power Control, Rate Adaptation and Scheduling for UWB-Based Intra-Vehicular Wireless Sensor Networks”, IEEE Transactions on Vehicular Technology, vol. 62, no. 1, pp. 219-234, January 2013. [pdf | link]  Y. Sadi and S. C. Ergen, "Energy and Delay Constrained Maximum Adaptive Schedule for Wireless Networked Control Systems", submitted.
Projects at WNL  Intra-Vehicular Wireless Sensor Networks  Supported by Marie Curie Reintegration Grant  Energy Efficient Robust Communication Network Design for Wireless Networked Control Systems  Supported by TUBITAK (The Scientific and Technological Research Council of Turkey)  Energy Efficient Machine-to-Machine Communications  Supported by Turk Telekom  Cross-layer Epidemic Protocols for Inter-vehicular Communication Networks  Supported by Turk Telekom
Thank You! Sinem Coleri Ergen: sergen@ku.edu.tr Personal webpage: http://home.ku.edu.tr/~sergen Wireless Networks Laboratory: http://wnl.ku.edu.tr

More Related Content

Cyber-Physical Systems

  • 1. Towards Energy Efficient and Robust Cyber-Physical Systems Sinem Coleri Ergen Wireless Networks Laboratory, Electrical and Electronics Engineering, Koc University
  • 2. Cyber-Physical Systems  System of collaborating computational elements controlling physical entities
  • 3. Joint Design of Control and Communication Systems
  • 4. Wireless Networked Control Systems  Sensors, actuators and controllers connect through a wireless network
  • 5. Wireless Networked Control Systems  Benefits of wireless  Ease of installation and maintenance  Low complexity and cost  Large flexibility to accommodate modification and upgrade of components  Backed up by several industrial organizations  International Society of Automation (ISA)  Highway Addressable Remote Transducer (HART)  Wireless Industrial Networking Alliance (WINA)
  • 6. Trade-off for Communication and Control Systems  Wireless communication system  Non-zero packet error probability Unreliability of wireless transmissions  Non-zero delay Packet transmission and shared wireless medium  Sampling and quantization errors Signals transmitted via packets  Limited battery resources  Control system  Stringent requirements on timing and reliability  Smaller packet error probability, delay and sampling period  Better control system performance  More energy consumed in wireless communication
  • 7. Outline  Optimization of communication system given requirements of control system  Novel design of scheduling algorithms  Joint optimization of control and communication systems  Novel abstractions for control systems
  • 8. Outline  Optimization of communication system given requirements of control system  Novel design of scheduling algorithms  Joint optimization of control and communication systems  Novel abstractions for control systems
  • 9. Novel Scheduling Algorithm Design  Packet generation period, transmission delay and reliability requirements:  Network Control Systems  sensor data -> real-time control of mechanical parts  Fixed determinism better than bounded determinism in control systems (Tl ,dl ,rl )
  • 10. Novel Scheduling Algorithm Design  Adaptivity requirement  Nodes should be scheduled as uniformly as possible EDF Uniform
  • 11. Novel Scheduling Algorithm Design  Adaptivity requirement  Nodes should be scheduled as uniformly as possible 1 EDF Uniform
  • 12. Novel Scheduling Algorithm Design  Adaptivity requirement  Nodes should be scheduled as uniformly as possible 2 EDF Uniform
  • 13. Novel Scheduling Algorithm Design  Adaptivity requirement  Nodes should be scheduled as uniformly as possible 3 EDF Uniform
  • 14. Medium Access Control Layer: System Model (Tl ,dl ,rl ) T1 £ T2 £ ... £ TL  given for each link l   Choose subframe length as for uniform allocation  Assume is an integer: Allocate every subframes  Uniform distribution minimize max subframe active time Ti /T1 = si T1 si º EDF Uniform max active time=0.9ms max active time=0.6ms ✓
  • 15. Example Optimization Problem Formulation Maximum active time of subframes Periodic packet generation Delay requirement Energy requirement Maximum allowed power by UWB regulations Transmission time Transmission rate of UWB for no concurrent transmission case
  • 16. Outline  Optimization of communication system given requirements of control system  Novel design of scheduling algorithms  Joint optimization of control and communication systems  Novel abstractions for control systems
  • 17. Abstractions of Control System  Maximum Allowable Transfer Interval (MATI): maximum allowed time interval between subsequent state vector reports from the sensor nodes to the controller  Maximum Allowable Delay (MAD): maximum allowed packet delay for the transmission from the sensor node to the controller MAD MATI Hard real-time guarantee not possible for wireless -> Packet error probability >0 at any point in time
  • 18. Abstractions of Control System  Stochastic MATI: keep time interval between subsequent state vector reports above MATI with a predefined probability to guarantee the stability of control systems  Many control applications and standards already use it  Industrial automation  IEEE 802.15.4e  Air transportation systems  Cooperative vehicular safety  Never been used in the joint optimization of control and communication systems
  • 19. Example Optimization Problem Formulation Total energy consumption Schedulability constraint Stochastic MATI constraint MAD constraint Maximum transmit power constraint
  • 20. Publications  Y. Sadi, S. C. Ergen and P. Park, "Minimum Energy Data Transmission for Wireless Networked Control Systems", IEEE Transactions on Wireless Communications, vol. 13, no. 4, pp. 2163-2175, April 2014. [pdf | link]  Y. Sadi and S. C. Ergen, “Optimal Power Control, Rate Adaptation and Scheduling for UWB-Based Intra-Vehicular Wireless Sensor Networks”, IEEE Transactions on Vehicular Technology, vol. 62, no. 1, pp. 219-234, January 2013. [pdf | link]  Y. Sadi and S. C. Ergen, "Energy and Delay Constrained Maximum Adaptive Schedule for Wireless Networked Control Systems", submitted.
  • 21. Projects at WNL  Intra-Vehicular Wireless Sensor Networks  Supported by Marie Curie Reintegration Grant  Energy Efficient Robust Communication Network Design for Wireless Networked Control Systems  Supported by TUBITAK (The Scientific and Technological Research Council of Turkey)  Energy Efficient Machine-to-Machine Communications  Supported by Turk Telekom  Cross-layer Epidemic Protocols for Inter-vehicular Communication Networks  Supported by Turk Telekom
  • 22. Thank You! Sinem Coleri Ergen: sergen@ku.edu.tr Personal webpage: http://home.ku.edu.tr/~sergen Wireless Networks Laboratory: http://wnl.ku.edu.tr

Editor's Notes

  1. Requires expertise for both systems, and still unsolved problem
  2. Scheduling design necessitates understanding requirements of sensor nodes and network
  3. If we had chosen a smaller subframe length than T1, say T1=2, this may have resulted in a more uniform distribution than choosing T1 still satisfying the periodic data generation and delay requirements of the sensors. However, since a transmission cannot be done partially in different time intervals, the shorter unallocated time duration at the end of the subframes may not allow including new nodes, changing the transmission time or allocating additional messages violating the adaptivity requirement. The shorter subframe length may even avoid generating feasible schedules if the length of the time slots is too large to fit in one subframe. Choosing the subframe length larger than T1 on the other hand does not bring any advantage and result in less uniform distribution.
  4. If we had chosen a smaller subframe length than T1, say T1=2, this may have resulted in a more uniform distribution than choosing T1 still satisfying the periodic data generation and delay requirements of the sensors. However, since a transmission cannot be done partially in different time intervals, the shorter unallocated time duration at the end of the subframes may not allow including new nodes, changing the transmission time or allocating additional messages violating the adaptivity requirement. The shorter subframe length may even avoid generating feasible schedules if the length of the time slots is too large to fit in one subframe. Choosing the subframe length larger than T1 on the other hand does not bring any advantage and result in less uniform distribution.