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Real-Time �Wireless Control Networks�for Cyber-Physical Systems
ChenyangLuCyber-PhysicalSystemsLaboratoryDepartmentofComputerScienceandEngineering
sensordata
Sensor
Actuator
controlcommand
Wireless Control Networks
2
Ø Real-time
Ø Reliability
Ø Control performance
Controller
Wireless for Process AutomationØ World-wide adoption of wireless in process industries
3
1.5+billionhoursopera6ngexperience
100,000sofsmartwirelessfielddevices
10,000sofwirelessfieldnetworks Courtesy:EmersonProcessManagement
Offshore Onshore
KillerAppofSensorNetworks!
WirelessHART
Industrialwirelessstandardforprocessmonitoringandcontrol
4
Ø Industrial-grade reliabilityq Multi-channel TDMA MAC
q One transmission per channel
q Redundant routes
q Over IEEE 802.15.4 PHY
Ø Centralized network managerq collects topology informationq generates routes and
transmission scheduleq changes when devices/links break
Our Endeavor
1. Real-time scheduling theory for wireless
2. Wireless-control co-design
3. Case study: wireless structural control
5
Real-Time Scheduling for WirelessGoalsØ Real-time transmission scheduling à meet end-to-end deadlinesØ Fast schedulability analysis à online admission control and adaptation
ApproachØ Leverage real-time scheduling theory for processorsØ Incorporate unique wireless characteristics
ResultsØ Fixed priority scheduling
q Delay analysis [RTAS 2011, TC, RTSS 2015]q Priority assignment [ECRTS 2011]
Ø Dynamic priority schedulingq Conflict-aware Least Laxity First [RTSS 2010]q Delay analysis for Earliest Deadline First [IWQoS 2014]
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Real-Time Flows
Ø Flow:sensoràcontrolleràactuatorovermul6-hops
Ø AsetofflowsF={F1,F2,…,FN}orderedbypriori6esØ EachflowFiischaracterizedby
q Asource(sensor),ades6na6on(actuator)q Aroutethroughthecontrollerq AperiodPiq AdeadlineDi(≤Pi)q TotalnumberoftransmissionsCialongtheroute
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highest lowest priority
Scheduling Problem
Ø Fixed priority schedulingq Every flow has a fixed priority
q Order transmissions based on the priorities of their flows.
Ø Flows are schedulable if delayi ≤ Di for every flow Fi
Ø Goal: efficient delay analysis
q Gives an upper bound of the end-to-end delay for each flow
q Used for online admission control and adaptation
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end-to-end delay of Fi
deadline of Fi
End-to-End Delay Analysis
Ø A lower priority flow is delayed due toq channel contention: all channels in a slot are assigned
to higher priority flowsq transmission conflict involving a same node
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2 1
1 and 5 are conflicting 4 and 5 are conflicting
4 5 3
3 and 4 are conflict-free
Ø Analyzeeachtypeofdelayseparately
Ø Combinebothdelaysàend-to-enddelaybound
InsightsØ Flows vs. Tasks
q Similar: channel contention
q Different: transmission conflict
Ø Channel contention à multiprocessor schedulingq A channel à a processor
q Flow Fi à a task with period Pi, deadline Di, execution time Ci
q Leverage existing response time analysis for multiprocessors
Ø Account for delays due to transmission conflicts
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)*$%+*,
Delay due to Conflict
Ø Low-priority flow Fl and high-priority flow Fh, conflict à delay Fl
Ø Q(I,h): #transmissions of Fh sharing nodes with Fl q In the worst case, Fh can
delay Fl by Q(l,h) slots q Q(l,h) = 5 à Fh can delay Fl
by 5 slots
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Fl delayed by 2 slots
Fl delayed by 2 slots
Fl delayed by 1 slot
WirelessHART Tested
Ø Implementation on a testbed of 69 TelosB motes.Ø WirelessHART stack on TinyOS/mote.
Ø Network manager (scheduler + routing).
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M.Sha,D.Guna6laka,C.WuandC.Lu,Implementa6onandExperimenta6onofIndustrialWirelessSensor-ActuatorNetworkProtocols,EuropeanConferenceonWirelessSensorNetworks(EWSN),February2015.
OutlineØ WirelessHART: real-time wireless in industryØ Real-time scheduling theory for wireless
Ø Wireless-control co-designØ Case study: wireless structural control
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Wireless-Control Co-Design
ChallengeØ Wireless resource is scarce and dynamic
Ø Cannot afford separating wireless and control designs
Cyber-Physical Systems ApproachØ Holistic co-design of wireless and control
ExamplesØ Rate selection for wireless control [RTAS 2012, TECS]
Ø Wireless structural control [ICCPS 2013]
Ø Wireless process control [ICCPS 2015]
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Goal:opAmizecontrolperformanceoverwireless
Rate Selection for Wireless Control
Ø Optimize the sampling rates of control loops sharing a WirelessHART network.
Ø Rate selection must balance control and network delay.q Lowsamplingrateàpoorcontrolperformanceq Highsamplingrateàlongdelayàpoorcontrolperformance
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Ø Control cost of control loop i under rate fi [Seto RTSS’96] q Approximated as with sensitivity coefficients
Control Performance Index
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Ø Digital implementation of control loop iq Periodic sampling at rate fiq Performance deviates from continuous counterpart
€
α i e−β i fi
Ø Overall control cost of n loops:
€
α i e−β i fi
i=1
n
∑€
α i, βi
delayi ≤1/ fi
The Rate Selection Problem
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€
f = { f1, f2,, fn}
€
fimin ≤ f i ≤ f i
max
minimize control cost
€
α i e−β i fi
i=1
n
∑
subject to
Ø Constrained non-linear optimization
Ø Determine sampling rates
Delay bound
Polynomial Time Delay Bounds
Ø In terms of decision variables (rates), the delay bounds are
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q Non-linear q Non-convex q Non-differentiable
Lagrangedualofo
bjec6ve
Rateofcont
rolloop6
Wireless-Control Co-Design
Relax delay bound to simplify optimizationØ Derive a convex and smooth, but less precise delay bound.
➠ Rate selection becomes a convex optimization problem.
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Controlcost
Evaluation
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q Greedy heuristic is fast but incurs high control cost.q Subgradient method is neither efficient nor effective.q Simulated annealing incurs lowest control cost, but is slow.
q Convex approximation balances control cost and execution time.
5 10 15 20 25 300
5
10
15
20
25
30
Con
trol
Cos
t
Number of Control Loops
Greedy Heuristic Subgradient Convex Approximation Simulated Annealing
5 10 15 20 25 3010−2
100
102
104
106
Exe
cutio
n Ti
me
(sec
onds
)
Number of Control Loops
Greedy Heuristic Subgradient Convex Approximation Simulated Annealing
Wireless Structural ControlØ Structural control systems protect civil infrastructure.Ø Wired control systems are costly and fragile. Ø Wireless structural control achieves flexibility and low cost.
11/16/15 21
HeritagetowercrumblesdowninearthquakeofFinaleEmilia,Italy,2012.
HanshinExpresswayBridgeaderKobeearthquake,Japan,1995.
Contributions
Ø Wireless Cyber-Physical Simulator (WCPS)q Capture dynamics of both physical plants and wireless networksq Enable holistic, high-fidelity simulation of wireless control systemsq Integrate TOSSIM and Simulink/MATLABq Open source: http://wcps.cse.wustl.edu
Ø Realistic case studies on wireless structural controlq Wireless traces from real-world environmentsq Structural models of a building and a large bridgeq Excited by real earthquake signal traces
Ø Cyber-physical co-designq End-to-end scheduling + control designq Improve control performance under wireless delay and loss
11/16/15 22
B.Li,Z.Sun,K.Mechitov,G.Hackmann,C.Lu,S.Dyke,G.AghaandB.Spencer,Realis6cCaseStudiesofWirelessStructuralControl,ACM/IEEEInterna6onalConferenceonCyber-PhysicalSystems(ICCPS'13),April2013.
Bill Emerson Memorial Bridge
Ø Main span: 1,150 ft. Ø Carries up to 14,000 cars
a day over Mississippi. Ø In the New Madrid
Seismic ZoneØ Replaced joints of the
bridge by actuatorsq 24 hydraulic actuators
Ø Vibration mode:q 0.1618 Hz for 1st modeq 0.2666 Hz for 2nd modeq 0.3723 Hz for 3rd mode
11/16/15 23
(a)
(b)
Jindo Bridge: Wireless Traces
Ø Largest wireless bride deployment [Jang 2010] q 113 Imote2 units; Peak acceleration sensitivity of 5mg – 30mg
Ø RSSI/noise traces from 58-node deck-network for this study
11/16/15 24
Conclusion
Ø Real-time wireless is a reality todayq Industrial standards: WirelessHART, ISA100q Field deployments world wide
Ø Real-time scheduling theory for wirelessq Leverage real-time processor schedulingq Incorporate unique wireless properties
Ø Cyber-physical co-design of wireless control systemsq Rate selection for wireless control systemsq Scheduling-control co-design for wireless structural control
Ø WCPS: Wireless Cyber-Physical Simulatorq Enable holistic simulations of wireless control systemsq Realistic case studies of wireless structural control
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Future DirectionsØ Scaling up wireless control networks
q From 100 nodes à 10,000 nodes
q Dealing with dynamics locally
q Hierarchical or decentralized architecture
Ø Science and engineering of wireless controlq Case studies à unified theory, architecture and methodology
q Bridge the gap between theory and systems
q Textbook on cyber-physical co-design
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For More Information
Ø C. Lu, A. Saifullah, B. Li, M. Sha, H. Gonzalez, D. Gunatilaka, C. Wu, L. Nie and Y. Chen, Real-Time Wireless Sensor-Actuator Networks for Industrial Cyber-Physical Systems, Special Issue on Industrial Cyber-Physical Systems, Proceedings of the IEEE, accepted.
Ø Real-Time Industrial Wireless Sensor-Actuator Networks: http://cps.cse.wustl.edu/index.php/Real-Time_Wireless_Control_Networks
Ø Wireless Structural Health Monitoring and Control: http://bridge.cse.wustl.edu
Ø Wireless Cyber-Physical Simulator: http://wcps.cse.wustl.edu
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