Wireless Networked Control Systems
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Transcript Wireless Networked Control Systems
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
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: (Tl ,dl ,rl )
Network Control Systems
sensor data -> real-time control of mechanical parts
Fixed determinism better than bounded determinism in control systems
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
Medium Access Control Layer: System Model
(Tl ,dl ,rl ) given for each link l
T1 T2 ... TL
Choose subframe length as T1 for uniform allocation
Assume Ti /T1 si is an integer: Allocate every si subframes
Uniform distribution
minimize max subframe active time
max active time=0.9ms
EDF
Uniform
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
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: [email protected]
Personal webpage: http://home.ku.edu.tr/~sergen
Wireless Networks Laboratory: http://wnl.ku.edu.tr