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.

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