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Introduction toCyber-physical Systems (CPSs)
Ricardo SanfeliceDepartment of Computer EngineeringHybrid Systems LabUniversity of California, Santa Cruz
Broad Scope of Cyber-physical Systems
Cyber-physicalSystems
ComputerNetworks
NonsmoothControlSystems
DigitalControl
Multi-modeControl
DistributedControl
PowerNetworks
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_
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Ricardo Sanfelice - University of California, Santa Cruz
Broad Scope of Cyber-physical Systems
Systems of today feature:
! Heterogeneous components and interfaces(e.g. humans, networks, analog/digital devices).
! Modular hardware for flexibility andreconfigurability.
! Distributed coordination and control.
Ricardo Sanfelice - University of California, Santa Cruz
Broad Scope of Cyber-physical Systems
Systems of today feature:
! Heterogeneous components and interfaces(e.g. humans, networks, analog/digital devices).
! Modular hardware for flexibility andreconfigurability.
! Distributed coordination and control.
xuplant
controller
Ricardo Sanfelice - University of California, Santa Cruz
Broad Scope of Cyber-physical Systems
Systems of today feature:
! Heterogeneous components and interfaces(e.g. humans, networks, analog/digital devices).
! Modular hardware for flexibility andreconfigurability.
! Distributed coordination and control.
xu
logic for decision making multiple control laws
plant
controller
Ricardo Sanfelice - University of California, Santa Cruz
Broad Scope of Cyber-physical Systems
Systems of today feature:
! Heterogeneous components and interfaces(e.g. humans, networks, analog/digital devices).
! Modular hardware for flexibility andreconfigurability.
! Distributed coordination and control.
xu
distributed
logic for decision making multiple control laws
plant
controller
Ricardo Sanfelice - University of California, Santa Cruz
Broad Scope of Cyber-physical Systems
Systems of today feature:
! Heterogeneous components and interfaces(e.g. humans, networks, analog/digital devices).
! Modular hardware for flexibility andreconfigurability.
! Distributed coordination and control.
xu
interfaceinterface
logic for decision making multiple control laws
plant
controller
Ricardo Sanfelice - University of California, Santa Cruz
Broad Scope of Cyber-physical Systems
Systems of today feature:
! Heterogeneous components and interfaces(e.g. humans, networks, analog/digital devices).
! Modular hardware for flexibility andreconfigurability.
! Distributed coordination and control.
xu
D/A
A/D
network
interfaceinterface
environment
logic for decision making multiple control laws
perturbations
human interaction
ZOHplant
controller
Ricardo Sanfelice - University of California, Santa Cruz
Modeling Cyber-Physical Systems
Frameworks for modeling of CPSs includenot an exhaustive list!
! Discrete-time models
! Finite-state machines
! Continuous-time models
! Impulsive differential equations
! Measure-driven differential equations
! Event-driven systems
! Timed automata
! Hybrid automata
!
...
Ricardo Sanfelice - University of California, Santa Cruz
Discrete-time models
Ricardo Sanfelice - University of California, Santa Cruz
Given a fnctian G :lRnx1Rm→Rn
Xlkti ) = G ( X( k ) .nlk ) ) KEN :={ 0,1 ,
given Xlo ) wd ktm ( k ).
' " }
If G is defined
on IRNXIRM 2nd¥"÷€zif!€gk m is defined an1 N
⇒ Existence of solnIn genie
.Add constraints : Hu ) ED
. Nanmiqveress / Nondetoninisne exzple• Extra inputs . G set vowed -
×+EG- ( ×,u)=G(x,u)+Xtxlkti ) 81Pa
Finite-state machines
Ricardo Sanfelice - University of California, Santa Cruz
Consider QEQ where Qissfniteset
q+=8( 9 ,v) 8 : theaterFI @¥@ Q=lAD}
qtLqNotAVHv=O⇒8iqM={ a
niBf••T SCQMafter Teflon
Continuous-time models
Ricardo Sanfelice - University of California, Santa Cruz
xit , x°=fcx,u) xeitrn ,norm
th x : denx → Rn↳ donx C [ 0 ,oD
Cenpleteness of maximal solutions depends on
refutnts of f ( nd input )In general : t#
• Differential inclusion -Fan := Q
.
ctfcxtsrs )for no mput
EE Fcx ,u) F is aa ne
T settled
regulation . ff map
Impulsive differential equations
Ricardo Sanfelice - University of California, Santa Cruz
i. fix ) x¥M×+= gk ) × EM
MCIR"
xtirn
. . -
. - .. -
.
ifcx ) t -4 LTIII ,
00
xltithglxttill tetti )i=
Measure-driven differential equations
Ricardo Sanfelice - University of California, Santa Cruz
Event-driven systems
Ricardo Sanfelice - University of California, Santa Cruz
CPS Applications
Feedback Control for Smart Grids
! Hetereogeneous networked power sources,buses, users, and loads
! Conversion required between differentwaveforms
! Dynamic demands and supplies
! Multiple time scales(e.g., fast and slow switching)
Classical approaches:
! Steady-state and averaged models
! Linear control design
! Bening conditions
~
...
...
~
~
DC bus
AC busPhotovoltaicarray
DC
DC
DC
DC
DC
DC
AC
AC
AC
AC
Diesel generator
Turbine
Fuel cells
Storage
AC loads
DC loads
Communication ( )
and Control ( ) bus
Electric power grid
Ricardo Sanfelice - University of California, Santa Cruz
CPS Applications
Power Conversion for Smart Grids
! Renewables provide power with highfluctuation
! DC/DC conversion is required beforeinjection to the grid
! Adaptive DC/AC conversion
sos4
s3 s2
s1
vDC
iL io
vc
vgL,R
c
DC/AC
HybridController
...
...
~
~
DC bus
AC busPhotovoltaicarray
DC
DC
DC
DC
DC
DC
AC
AC
AC
AC
Diesel generator
Turbine
Fuel cells
Storage
AC loads
DC loads
Ricardo Sanfelice - University of California, Santa Cruz
CPS Applications
Power Conversion for Smart Grids
! Renewables provide power with highfluctuation
! DC/DC conversion is required beforeinjection to the grid
! Adaptive DC/AC conversion
sos4
s3 s2
s1
vDC
iL io
vc
vgL,R
c
DC/AC
HybridController
High Penetration of RenewablesU.S.: 20% by 2030
...
...
~
~
DC bus
AC busPhotovoltaicarray
DC
DC
DC
DC
DC
DC
AC
AC
AC
AC
Diesel generator
Turbine
Fuel cells
Storage
AC loads
DC loads
Ricardo Sanfelice - University of California, Santa Cruz
CPS Applications
Power Conversion for Smart Grids
! Renewables provide power with highfluctuation
! DC/DC conversion is required beforeinjection to the grid
! Adaptive DC/AC conversion
sos4
s3 s2
s1
vDC
iL io
vc
vgL,R
c
DC/AC
HybridController
High Penetration of RenewablesU.S.: 20% by 2030
...
...
~
~
DC bus
AC busPhotovoltaicarray
DC
DC
DC
DC
DC
DC
AC
AC
AC
AC
Diesel generator
Turbine
Fuel cells
Storage
AC loads
DC loads
Ricardo Sanfelice - University of California, Santa Cruz
CPS Applications
dynamic communication
network Adversaries
Static and Mobile Agents
Control of Reconfigurable Multi-Robot Systems
! Groups of heterogeneousnetworked agents
! Adversaries can disruptthe network(jamming, destructive actions)
! Locations and capabilitiesunknown
Scenarios of DoD interest:
! Electronic warfare
! Satellite communications
! Disaster reliefRicardo Sanfelice - University of California, Santa Cruz
CPS Applications
Reconfigurable Satellite Communications
! Dynamic ground-satellite links
! Dynamic signal-to-noise ratio oncommunication channels
! Jamming attacks (MILSATCOM)
GEO
LEOground station
adversary
satellite
dynamicnetwork
Ricardo Sanfelice - University of California, Santa Cruz
CPS Applications
Reconfigurable Satellite Communications
! Dynamic ground-satellite links
! Dynamic signal-to-noise ratio oncommunication channels
! Jamming attacks (MILSATCOM)
GEO
LEOground station
adversary
satellite
dynamicnetwork
Recent initiatives, such asthe National BroadbandPlan, challenge the tradi-tional FCC approach to allo-cating spectrum, requestinga new U.S. spectrum policyallowing for dynamic alloca-tion and utilization.
Ricardo Sanfelice - University of California, Santa Cruz
CPS Applications
Control of Aerial Vehicles with Limited and Faulty Sensors
! Autonomous recovery control
! Low cost sensing for autonomous navigation
! Sensor failures affect stability and performance
Ricardo Sanfelice - University of California, Santa Cruz
CPS Applications
Control of Aerial Vehicles with Limited and Faulty Sensors
! Autonomous recovery control
! Low cost sensing for autonomous navigation
! Sensor failures affect stability and performance
Ricardo Sanfelice - University of California, Santa Cruz
CPS Applications
Control of Aerial Vehicles with Limited and Faulty Sensors
! Autonomous recovery control
! Low cost sensing for autonomous navigation
! Sensor failures affect stability and performance
UAVs in the National Air Space(NAS): 2012 bill giving FAA threeyears to “integrate” UAVs into theNAS (set policies, standards, etc.)
Ricardo Sanfelice - University of California, Santa Cruz
CPS Challenges
The U.S. National Academy of Engineering has listed 14 grandchallenges that relate environmental, health, and societal issues;these issues will clearly benefit from advances achieved incyber-physical systems.1
“The control engineering research community can play aleading role in the development of cyber-physical systems.”2
1http://www.engineeringchallenges.org/challenges.aspx
2The Impact of Control Technology, T. Samad and A.M. Annaswamy (eds.), 2011.
Ricardo Sanfelice - University of California, Santa Cruz
CPS Challenges3
Compositionality
! Compositionality that cuts across the heterogeneous cyberand physical aspects of CPS is a major scientific challenge.
! Modeling and predicting performance of composition.
! An potential solution could be “plug & play” cyber-physicalcomponents that integrate seamlessly.
3Cyber-Physical Systems Summit, 2008.Report of the Steering Committee for Foundations in Innovation for Cyber-Physical Systems, 2013.
Ricardo Sanfelice - University of California, Santa Cruz
CPS Challenges
Distributed Event-based Sensing and Control
! Collecting adequate information and asserting control in adistributed environment.
! New science and theory is needed regarding howcommunication can facilitate safe operation, failure interlocks,and adaptation.
! Integration of information and actions across time (withunderstanding of uncertainty at different scales) is essential.
! When do samples need to be collected for distributeddecisions? What information needs to be collected? Whereshould the computations be performed?
Ricardo Sanfelice - University of California, Santa Cruz
CPS Challenges
Physical and Cyber Constraints
! Current algorithm designs seldom include the computationallimitations of the hardware/software on which they areimplemented as explicit constraints. Computationalcapabilities, such as computer architecture and processingpower are not typically explicitly considered during design.
! Current “one-size-fits-all” approach typically rules out viablesolutions or leads to very conservative solutions, affecting thesystem?s performance and robustness.
! Need to generate tools for systematic analysis and design ofcomputationally aware algorithms for CPSs.
Ricardo Sanfelice - University of California, Santa Cruz
CPS Challenges
Physical, Human Interfaces and Integration
! A hierarchy of models of physical contact with varying levelsof resolution and degrees of freedom (e.g., continuous,discrete, etc).
! The mathematical properties the models in the hierarchy, thecorresponding algorithms with known performance properties,and the couplings of the contact models to the cyber andother physical components of the system.
! A unified model including all components is needed.
! New science and theory is needed to define safe hand-offsbetween human and cyber-based control, cyber-physicalinterlocks, protocols for mixed initiative inter-operation, andmaintaining the operator’s mental model and appropriateskepticism.
Ricardo Sanfelice - University of California, Santa Cruz
CPS Challenges
Robustness, Adaptation, Reconfiguration
! Contrary to well-established methods of robust control, whichcan handle modeling uncertainty, we need new notions ofrobust system design that address uncertainty at the cyberlevel (computing decision or scheduling choices), and areresilient with respect to massively uncertain/untrusted dataand structural/topological uncertainties and reconfiguration.
! CPS will also need to be reconfigurable and adaptive toovercome faults in both physical and cyber levels.
Ricardo Sanfelice - University of California, Santa Cruz
Looking Ahead
Ricardo Sanfelice - University of California, Santa Cruz
Looking Ahead
! Systems that combine physical and cyber components,potentially networked and with computations integrated withphysical process
Ricardo Sanfelice - University of California, Santa Cruz
Looking Ahead
! Systems that combine physical and cyber components,potentially networked and with computations integrated withphysical processphysical = physical plant/process/networkcyber = software/algorithm/computation
Ricardo Sanfelice - University of California, Santa Cruz
Looking Ahead
! Systems that combine physical and cyber components,potentially networked and with computations integrated withphysical processphysical = physical plant/process/networkcyber = software/algorithm/computation
! Modeling of the physical and the cyber
Ricardo Sanfelice - University of California, Santa Cruz
Looking Ahead
! Systems that combine physical and cyber components,potentially networked and with computations integrated withphysical processphysical = physical plant/process/networkcyber = software/algorithm/computation
! Modeling of the physical and the cyber
! Tools to analyze the behavior of systems with bothcomponents
Ricardo Sanfelice - University of California, Santa Cruz
Looking Ahead
! Systems that combine physical and cyber components,potentially networked and with computations integrated withphysical processphysical = physical plant/process/networkcyber = software/algorithm/computation
! Modeling of the physical and the cyber
! Tools to analyze the behavior of systems with bothcomponents
tools solely for the physical or for the cyber do not apply
Ricardo Sanfelice - University of California, Santa Cruz
Looking Ahead
! Systems that combine physical and cyber components,potentially networked and with computations integrated withphysical processphysical = physical plant/process/networkcyber = software/algorithm/computation
! Modeling of the physical and the cyber
! Tools to analyze the behavior of systems with bothcomponents
tools solely for the physical or for the cyber do not apply
! Understand core theoretical concepts needed to study CPS
Ricardo Sanfelice - University of California, Santa Cruz
Looking Ahead
! Systems that combine physical and cyber components,potentially networked and with computations integrated withphysical processphysical = physical plant/process/networkcyber = software/algorithm/computation
! Modeling of the physical and the cyber
! Tools to analyze the behavior of systems with bothcomponents
tools solely for the physical or for the cyber do not apply
! Understand core theoretical concepts needed to study CPS
! Apply tools and concepts to a CPS application
Ricardo Sanfelice - University of California, Santa Cruz