Introduction to Cyber-physical Systems (CPSs)disc-cps15.imtlucca.it/pdf/Sanfelice_Intro.pdf · Modeling Cyber-Physical Systems Frameworks for modeling of CPSs include not an exhaustive

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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Ricardo Sanfelice - University of California, Santa Cruz


Systems of today feature:

! Heterogeneous components and interfaces(e.g. humans, networks, analog/digital devices).

! Modular hardware for flexibility andreconfigurability.

! Distributed coordination and control.







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controller







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logic for decision making multiple control laws

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interfaceinterface


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D/A

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perturbations

human interaction

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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

!

...


Discrete-time models


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


Consider QEQ where Qissfniteset

q+=8( 9 ,v) 8 : theaterFI @¥@ Q=lAD}

qtLqNotAVHv=O⇒8iqM={ a

niBf••T SCQMafter Teflon

Continuous-time models


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


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MCIR"

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ifcx ) t -4 LTIII ,

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xltithglxttill tetti )i=

Measure-driven differential equations


Event-driven systems


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


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

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DC/AC

HybridController

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~

~

DC bus


DC

DC

DC

DC

DC

DC

AC

AC

AC

AC

Diesel generator

Turbine

Fuel cells

Storage

AC loads

DC loads


CPS Applications





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s1

vDC

iL io

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DC/AC

HybridController

High Penetration of RenewablesU.S.: 20% by 2030

...

...

~

~

DC bus


DC

DC

DC

DC

DC

DC

AC

AC

AC

AC

Diesel generator

Turbine

Fuel cells

Storage

AC loads

DC loads


CPS Applications





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s3 s2

s1

vDC

iL io

vc

vgL,R

c

DC/AC

HybridController

High Penetration of RenewablesU.S.: 20% by 2030

...

...

~

~

DC bus


DC

DC

DC

DC

DC

DC

AC

AC

AC

AC

Diesel generator

Turbine

Fuel cells

Storage

AC loads

DC loads


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


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.


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


CPS Applications






CPS Applications





UAVs in the National Air Space(NAS): 2012 bill giving FAA threeyears to “integrate” UAVs into theNAS (set policies, standards, etc.)


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.


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.


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?


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.


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.


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.


Looking Ahead


Looking Ahead

! Systems that combine physical and cyber components,potentially networked and with computations integrated withphysical process


Looking Ahead

! Systems that combine physical and cyber components,potentially networked and with computations integrated withphysical processphysical = physical plant/process/networkcyber = software/algorithm/computation


Looking Ahead


! Modeling of the physical and the cyber


Looking Ahead



! Tools to analyze the behavior of systems with bothcomponents


Looking Ahead




tools solely for the physical or for the cyber do not apply


Looking Ahead





! Understand core theoretical concepts needed to study CPS


Looking Ahead





! Understand core theoretical concepts needed to study CPS

! Apply tools and concepts to a CPS application


Documents

Introduction to Cyber-physical Systems (CPSs)disc-cps15.imtlucca.it/pdf/Sanfelice_Intro.pdf · Modeling Cyber-Physical Systems Frameworks for modeling of CPSs include not an exhaustive