Control Co-design: Algorithms and Their Implementation

RELIABLE SOFTWARE TECHNOLOGIESRELIABLE SOFTWARE TECHNOLOGIESADAADA--EUROPE 2010EUROPE 2010

Control Co-design: Algorithms and Control Co-design: Algorithms and g gtheir Implementation

g gtheir Implementation

P. Albertos, A. P. Albertos, A. CrespoCrespo, J. , J. SimóSimóDpt. Dpt. IngIng. de . de SistemasSistemas y y AutomáticaAutomática

I iI i dd A á iA á i I f á iI f á i I d i lI d i l

P. AlbertosP. Albertos A. A. FernándezFernándezDpt. Dpt. AutomáticaAutomática y y ComputaciónComputación

C A b C bC A b C bInstitutoInstituto de de AutomáticaAutomática e e InformáticaInformática IndustrialIndustrialUniversidad Universidad PolitécnicaPolitécnica de Valenciade Valencia

[email protected]@aii.upv.es

CUJAE, Habana. CubaCUJAE, Habana. [email protected]@electrica.cujae.edu.cu

VALENCIA, SPAIN, VALENCIA, SPAIN, 1414--18 18 JUNE JUNE 20102010

Thanks to:Thanks to:n

Thanks to:Thanks to:m

enta

tion My My CoCo--workers workers ::

KarlKarl--Erik Erik ÅrzénÅrzénMy My CoCo--authorsauthors::AlfonsAlfons CrespoCrespo

heir

Impl

em

AntonAnton CervinCervinJosé José SimóSimóAdelAdel FernándezFernández

hms a

nd th Marina VallésMarina Vallés

AngelAngel ValeraValera

n: A

lgor

ith Raúl Raúl SimarroSimarroPatricia Patricia BalbastreBalbastre

l Co-

desi

gn

Pedro GarcíaPedro García

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trol

© P. Albertos, 2010© P. Albertos, 2010

MotivationMotivationn

human/machine

MotivationMotivationm

enta

tion

monitoredvariables

referencevariables

machineinterfaceClassical control loopClassical control loop

Control

heir

Impl

em

measuredvariablesControl

variables information flow

Controlsystem

hms a

nd th

sensorsMass transfer &

energy flowinformation flow

actua-

n: A

lgor

ith

sensorsenergy convertertors

l Co-

desi

gn

energysupply

energycon-

sumer

auxiliaryenergysupply

Con

trol


mechanicalhydraulicthermal

electrical

MotivationMotivationn

human/machine

MotivationMotivationm

enta

tion

monitoredvariables

referencevariables

machineinterfaceClassical control loopClassical control loop

i f ti

heir

Impl

em

measuredvariablesControl

variables information flow

informationprocessing

hms a

nd th

sensorsMass transfer &

energy flowinformation flow

actua-

Basic DT ControllerBasic DT Controller

n: A

lgor

ith

sensorsenergy convertertors

l Co-

desi

gn

energysupply

energycon-

sumer

auxiliaryenergysupply

Con

trol


mechanicalhydraulicthermal

electrical

Basic Control LoopBasic Control Loopn

Basic Control LoopBasic Control Loopm

enta

tion

f rk Regulator

heir

Impl

em

ControlAlgorithm

D/A

referencer(t) uk

yk

rkA/DRegulator

hms a

nd th A/D Algorithmk

DTDT

n: A

lgor

ith

y(t) u(t)CT

DTDT

l Co-

desi

gn Sensor ActuatorProcess

Con

trol


Disturbance

Control System Development TodayControl System Development Todayn

Control System Development TodayControl System Development Todaym

enta

tion

heir

Impl

emhm

s and

thn:

Alg

orith

l Co-

desi

gnC

ontr

ol


RegulatorRegulatorn

RegulatorRegulatorm

enta

tion Control viewpoint: Control viewpoint:

Signal processorSignal processor RegulatorRegulator

heir

Impl

em

Dynamic behaviorDynamic behaviorProcess interactionProcess interaction

RegulatorRegulatoruu yy

hms a

nd th

Computer viewpoint: Computer viewpoint:

rr

n: A

lgor

ith

p pp pSet of tasksSet of tasksResourceResource allocationallocation RegulatorRegulator

l Co-

desi

gn

RT constraintsRT constraints

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trol


ProblemsProblemsn

ProblemsProblemsm

enta

tion

The control engineer does not care about implementationsThe control engineer does not care about implementations

heir

Impl

em “trivial”“trivial”“buy a faster computer”“buy a faster computer”

hms a

nd th The software engineer does not understand controller The software engineer does not understand controller

timingtiming

n: A

lgor

ith

gg“ = (T“ = (Tii, D, Dii, C, Cii)”)”“hard deadlines”“hard deadlines”

iτ

l Co-

desi

gn

Control theory and realControl theory and real--time scheduling theory have time scheduling theory have evolved as separate subjects for thirty yearsevolved as separate subjects for thirty years

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evolved as separate subjects for thirty yearsevolved as separate subjects for thirty years

OutlineOutlinen

OutlineOutlineIntroduction: Basic Digital ControlIntroduction: Basic Digital Control

men

tatio

n ggMain assumptions, Main concernsMain assumptions, Main concerns

Computing requirements for control applicationsComputing requirements for control applications

heir

Impl

em Computing requirements for control applicationsComputing requirements for control applicationsControl requirements for RT implementationControl requirements for RT implementationNew control scenariosNew control scenarios

hms a

nd th

New control scenariosNew control scenariosEmbedded, networked, eventEmbedded, networked, event--drivendriven

Algorithmic issuesAlgorithmic issues

n: A

lgor

ith

ggAsynchronous sampling, Delays, Control effortAsynchronous sampling, Delays, Control effortHybrid systemsHybrid systems

l Co-

desi

gn Implementation issuesImplementation issuesControl KernelControl Kernel

Con

trol


ConclusionsConclusions

IntroductionIntroductionn

IntroductionIntroductionm

enta

tion Digital control comes from SD ControlDigital control comes from SD Control

Discretization of CT controllersDiscretization of CT controllers

heir

Impl

em

Control is applied to CT plants Control is applied to CT plants Plants are discretized for control design purposesPlants are discretized for control design purposes

hms a

nd th DC implies plant in open loop between samplingsDC implies plant in open loop between samplings

DC is implemented in ComputersDC is implemented in Computers

n: A

lgor

ith Controller is no more one single deviceController is no more one single deviceSerial operation Serial operation –– Tasks conflictsTasks conflicts

l Co-

desi

gn

Sharing resourcesSharing resourcesControl design Control design implementationimplementation

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gg pp

Basic Digital ControlBasic Digital Controln

Basic Digital ControlBasic Digital Controlm

enta

tion

The plant is without control between sampling/updatingThe plant is without control between sampling/updatingSampling and updating should be as fast as possibleSampling and updating should be as fast as possible

heir

Impl

em Sampling and updating should be as fast as possibleSampling and updating should be as fast as possibleControl is computed (updated) periodicallyControl is computed (updated) periodicallyC t l t kC t l t k

hms a

nd th Control task Control task

parameters are stored in the memoryparameters are stored in the memoryt l l i lit l l i li

n: A

lgor

ith control law sequence is cycliccontrol law sequence is cycliccontrol law is validated in CT operationcontrol law is validated in CT operation

P t d t iblP t d t ibl

l Co-

desi

gn Past data are accessible Past data are accessible Communication channels are continuously operatingCommunication channels are continuously operating

Con

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DT controller emulates CT controllerDT controller emulates CT controller

Real Time Task modelReal Time Task modeln

Real Time Task modelReal Time Task modelm

enta

tion A task (TA task (Tkk) is defined by four parameters:) is defined by four parameters:

CCkk: Worst Case Execution Time (WCET): Worst Case Execution Time (WCET)Ck

heir

Impl

em

DDkk: Deadline: Deadline

PPkk: Period: Period

Ck

hms a

nd th ΦΦκκ:: PhasePhase Pk

DkΦk

n: A

lgor

ith

k

Computation timeCk 3 C1 + C2 + C4 = Ck

Jitter on input Jitter on output

l Co-

desi

gn

Tt

Taskk 1 2 41 23

4C1 + C2 + C4 Ck

5

Con

trol


kT

Period

Deadline

Phase

Control Loop TimingControl Loop Timingn

Control Loop TimingControl Loop Timingm

enta

tion

•• Classical control assumes deterministic samplingClassical control assumes deterministic samplingi t i dii t i di

heir

Impl

em –– in most cases periodicin most cases periodic•• Classical Classical control assumes negligible or constant inputcontrol assumes negligible or constant input--output output

latency (from sampling to actuation )latency (from sampling to actuation )

hms a

nd th latency (from sampling to actuation )latency (from sampling to actuation )

–– if the latency is small compared to the sampling interval it can if the latency is small compared to the sampling interval it can be ignoredbe ignored

n: A

lgor

ith be ignoredbe ignored–– if the latency is constant it can be included in the control designif the latency is constant it can be included in the control design

too long latency or too much latency jitter give poortoo long latency or too much latency jitter give poor

l Co-

desi

gn –– too long latency or too much latency jitter give poor too long latency or too much latency jitter give poor performance or instabilityperformance or instability

•• Not always possible to achieve with limited computing resourcesNot always possible to achieve with limited computing resources

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Not always possible to achieve with limited computing resources Not always possible to achieve with limited computing resources that are shared with other applicationsthat are shared with other applications

Sampling rate selectionSampling rate selectionn

Sampling rate selectionSampling rate selection

Regular Sampling:Regular Sampling: Influences and is determined by desired closed loopInfluences and is determined by desired closed loop

men

tatio

n Regular Sampling: Regular Sampling: Influences and is determined by desired closed loop Influences and is determined by desired closed loop performanceperformance

Fast sampling converges to CT but …Fast sampling converges to CT but …

heir

Impl

em Computation load increases, Computation load increases, Numerical errorsNumerical errorsSame sampling rate for all processes?Same sampling rate for all processes?

MultirateMultirate controllerscontrollers

hms a

nd th MultirateMultirate controllerscontrollers

Control computation is not required anytime: Control computation is not required anytime: EventEvent based control Hybrid controlbased control Hybrid control

n: A

lgor

ith EventEvent--based control, Hybrid controlbased control, Hybrid control

Classical control assumes negligible or constant inputClassical control assumes negligible or constant input--output delaysoutput delays

l Co-

desi

gn

p yp ysmall delays can be ignored, included in the control designsmall delays can be ignored, included in the control designdifficult to predict the required time (WCET)difficult to predict the required time (WCET)

WARNINGSWARNINGS

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© P. Albertos, © P. Albertos, 20102010

WARNINGSWARNINGSlong sampling interval or delay may cause poor performance or instability …long sampling interval or delay may cause poor performance or instability …Resources infraResources infra--useuse

Main Concerns in Computer ControlMain Concerns in Computer Controln

Main Concerns in Computer ControlMain Concerns in Computer Controlm

enta

tion Unavoidable delays between sampling & updatingUnavoidable delays between sampling & updating

Sampling period may be changedSampling period may be changed

heir

Impl

em

Signal transmission may be delayed (or missing)Signal transmission may be delayed (or missing)Time sequencing may depend on other tasksTime sequencing may depend on other tasks

hms a

nd th Additional tasks may change the allocated resources: Additional tasks may change the allocated resources:

computation time, memory, data accesscomputation time, memory, data access

n: A

lgor

ith as a result as a result Non conventional sampling/updating patternNon conventional sampling/updating pattern

l Co-

desi

gn

Delays and missing dataDelays and missing dataModes and sampling rate changes (alternatives)Modes and sampling rate changes (alternatives)

Con

trol


Modes and sampling rate changes (alternatives)Modes and sampling rate changes (alternatives)EventEvent--based controlbased control

ApplicationsApplicationsn

ApplicationsApplicationsm

enta

tion

Automotive IndustryAutomotive IndustryMany, distributedMany, distributed

heir

Impl

em y,y,

hms a

nd th

Aerospace and Fly ControlAerospace and Fly Control

n: A

lgor

ith Safety, reliabilitySafety, reliability

l Co-

desi

gn

Industrial ProcessesIndustrial ProcessesMM ff iff i

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trol


Many many, costMany many, cost--effectiveeffective

Computer-based controlComputer-based controln

Computer based controlComputer based controlm

enta

tion

heir

Impl

em

face

face

hms a

nd th

ProcessProcessComputerComputer

nter

fnt

erf

n: A

lgor

ith InIn

l Co-

desi

gnC

ontr

ol


Control loop implementationControl loop implementationn

p pp pm

enta

tion

SpecificationSpecification

heir

Impl

em SpecificationSpecification

hms a

nd th

n: A

lgor

ithl C

o-de

sign ComputationComputation

Con

trol


Computer Control TaskComputer Control Taskn

Computer Control TaskComputer Control Task

I iti li tiI iti li ti

men

tatio

n InitializationInitialization……

looploop

heir

Impl

em

convert _sensor _analog_ digital (y); read reference (r);convert _sensor _analog_ digital (y); read reference (r);compute _control _action (u); compute _control _action (u);

hms a

nd th compute _error (e)compute _error (e)

compute _control _action (u) compute _control _action (u)

n: A

lgor

ith send _ converted _ control_ action (u); send _ converted _ control_ action (u); update_internal_variablesupdate_internal_variables (y,u, …); (y,u, …);

l Co-

desi

gn Next _Iteration:= Next _Iteration + Period; Next _Iteration:= Next _Iteration + Period; delay until Next _Iteration;delay until Next _Iteration;

Con

trol


end loop;end loop;……

Computing Requirementsf l li iComputing Requirementsf l li i

n

for Control Applicationsfor Control Applicationsm

enta

tion

To have a quick an secure dispatch of a control actionTo have a quick an secure dispatch of a control action

heir

Impl

em

To get a basic “picture” of the current situationTo get a basic “picture” of the current situation

T i l d f l i b i dT i l d f l i b i d

hms a

nd th To compute a simple and fast control action to be improved To compute a simple and fast control action to be improved

if resources are availableif resources are available

n: A

lgor

ith

To switch to the appropriate control mode, based on the To switch to the appropriate control mode, based on the resources availabilityresources availability

l Co-

desi

gn

yy

To reconfigure under detected faultsTo reconfigure under detected faults

Con

trol


Some RT OptionsSome RT Optionsn

Some RT OptionsSome RT Options

SubSub--task modelstask models

men

tatio

n SubSub--task modelstask modelsSample & deliver, compute, refineSample & deliver, compute, refine

Imprecise task modelImprecise task model

heir

Impl

em Imprecise task modelImprecise task modelmandatory + optional partmandatory + optional part

i l i h l i l ii l i h l i l i

hms a

nd th anytime algorithms or multiple versionsanytime algorithms or multiple versions

only applicable to control in special casesonly applicable to control in special cases

n: A

lgor

ith Alternatives for deadline overruns?Alternatives for deadline overruns?Continue with the computations of the controller jobContinue with the computations of the controller job

l Co-

desi

gn

p jp jAbort the job (lost sample Abort the job (lost sample doubled samp. interval)doubled samp. interval)Postpone remaining computations until the beginningPostpone remaining computations until the beginning

Con

trol


Postpone remaining computations until the beginning Postpone remaining computations until the beginning of the next sample (increased latency)of the next sample (increased latency)….….

New Trends in Control ImplementationNew Trends in Control Implementationn

New Trends in Control ImplementationNew Trends in Control Implementationm

enta

tion RT Operating SystemRT Operating System

RT MiddlewareRT Middleware

Secure Systems and isolation. Secure Systems and isolation. Hypervisor SystemHypervisor System

Dynamic load managementDynamic load management

heir

Impl

em

Communication SystemsCommunication SystemsDDSDDS

QoSQoS management according management according to the to the QoCQoC observed (Quality observed (Quality

of Control)of Control)

hms a

nd th Virtual machinesVirtual machines

Objects and AgentsObjects and Agents

of Control)of Control)

Distributed execution Distributed execution environments.environments.

n: A

lgor

ith Control MiddlewareControl MiddlewareLocal, emergency, switchingLocal, emergency, switching

environments.environments.Physical MetaphorPhysical Metaphor

Environment where control Environment where control

l Co-

desi

gn services are provided.services are provided.Control MetaphorControl Metaphor

Con

trol


Control requirements for RT implementations: Basic AssumptionsControl requirements for RT implementations: Basic Assumptions

nimplementations: Basic Assumptionsimplementations: Basic Assumptions

men

tatio

n The Data Acquisition system provides the required dataThe Data Acquisition system provides the required dataThe actuators’ drivers deliver the control actionsThe actuators’ drivers deliver the control actions

heir

Impl

em

The CPU is fully available for the control taskThe CPU is fully available for the control taskThe CPU computes onThe CPU computes on--time (no errors) the control actiontime (no errors) the control action

hms a

nd th

pp ( )( )The required data are stored in the memoryThe required data are stored in the memoryThe sampling pattern is regular (constant synchronousThe sampling pattern is regular (constant synchronous

n: A

lgor

ith The sampling pattern is regular (constant, synchronous The sampling pattern is regular (constant, synchronous and uniform for any control task)and uniform for any control task)The control algorithm is well definedThe control algorithm is well defined

l Co-

desi

gn The control algorithm is well definedThe control algorithm is well definedAlternative controllers are independentAlternative controllers are independentPower supply is guaranteedPower supply is guaranteed

Con

trol


Power supply is guaranteedPower supply is guaranteed

Control activities’ priorityControl activities’ priorityn

Control activities priorityControl activities prioritym

enta

tion

Backup CA CAuser

bu

kr

heir

Impl

em

kvkuCACA

hms a

nd th

Plantdelivcomputation

x y

n: A

lgor

ith kx

kmky

DA

l Co-

desi

gn

Safe operation in any condition

Con

trol


Safe operation in any condition

Control activities’ priorityControl activities’ priorityn

Control activities priorityControl activities priority

Ensure control action (CA) deliveringEnsure control action (CA) delivering

men

tatio

n Ensure control action (CA) deliveringEnsure control action (CA) deliveringSafe (backSafe (back--up) CA computationup) CA computationSafe CA computation based on previous dataSafe CA computation based on previous data

heir

Impl

em p pp pData acquisition of major signalsData acquisition of major signals

Safe CA computation based on current dataSafe CA computation based on current data

hms a

nd th

ppTransfer to new control structureTransfer to new control structure

Basic control structure parameters computationBasic control structure parameters computation

n: A

lgor

ith CA computation CA computation

Full DA Full DA

l Co-

desi

gn

Control Control structuresstructures evaluation and selectionevaluation and selectionCA computation (different levels)CA computation (different levels)

Con

trol


p ( )p ( )Communication facilitiesCommunication facilitiesCoordination facilitiesCoordination facilities

Highest priorityHighest priorityn

Highest priorityHighest prioritym

enta

tion

Control action deliveringControl action deliveringDetect missing dataDetect missing data

heir

Impl

em Detect missing dataDetect missing dataEvaluate control performanceEvaluate control performanceE l t lt ti t l tiE l t lt ti t l ti

hms a

nd th Evaluate alternative control optionsEvaluate alternative control options

Determine the best CADetermine the best CA

n: A

lgor

ith Detect faulty conditionsDetect faulty conditionsChange the operating modeChange the operating mode

l Co-

desi

gn Compute backCompute back--up signalsup signals

Con

trol


Influence on Control PerformanceInfluence on Control PerformancenScheduling &Scheduling & C lC l

men

tatio

nScheduling &Scheduling &NetworkNetwork

ParametersParametersTask TimingTask TimingParametersParameters

ControlControlPerformancePerformance

( i i i( i i i

heir

Impl

em ParametersParameters(T,D,Prio, (T,D,Prio,

Protocol )Protocol )

ParametersParameters(latencies, jitter, …)(latencies, jitter, …) (variance, rise time, (variance, rise time,

overshoot, ….)overshoot, ….)

hms a

nd th

In general:In general:

Protocol,…)Protocol,…)Complex relationshipComplex relationship Complex relationshipComplex relationship

n: A

lgor

ith sampling jitter has a negative effect on performancesampling jitter has a negative effect on performancea short latency is better than a long latencya short latency is better than a long latencylatency jitter is bad, but a short jittery latency is in most cases better latency jitter is bad, but a short jittery latency is in most cases better

l Co-

desi

gn

y j j y yy j j y ythat a longer constant latency, also if the latter is compensated forthat a longer constant latency, also if the latter is compensated for

However, anomalies existsHowever, anomalies existssampling jitter may improve performancesampling jitter may improve performance

Control Effort ConceptControl Effort Concept

Con

trol


sampling jitter may improve performancesampling jitter may improve performancelatency can sometimes have a stabilizing effectlatency can sometimes have a stabilizing effecta shorter varying latency can be worse than a longer constant latencya shorter varying latency can be worse than a longer constant latency

Performance degradingPerformance degradingn

Performance degradingPerformance degradingm

enta

tion

The maximum allowable time delay is given by the The maximum allowable time delay is given by the phase margin derived from the frequency analysis ofphase margin derived from the frequency analysis of

heir

Impl

em phase margin, derived from the frequency analysis of phase margin, derived from the frequency analysis of the open loop output feedback controlled systemthe open loop output feedback controlled systemTheThe Control EffortControl Effort defined as the shift indefined as the shift in

hms a

nd th The The Control EffortControl Effort, defined as the shift in , defined as the shift in

damping from the open loop poles to the closed damping from the open loop poles to the closed loop poles provides a useful way to obtain theloop poles provides a useful way to obtain the

n: A

lgor

ith loop poles, provides a useful way to obtain the loop poles, provides a useful way to obtain the maximum allowable time delay, for both, maximum allowable time delay, for both, continuous and discrete systemscontinuous and discrete systems

l Co-

desi

gn continuous and discrete systems.continuous and discrete systems.The longer the sampling period T is, the more The longer the sampling period T is, the more

i i h i d l h d i ii i h i d l h d i i

Con

trol


sensitive to the time delay the design is.sensitive to the time delay the design is.

MIMO controlled plant:Signals relevanceSignals relevanceMIMO controlled plant:Signals relevanceSignals relevancen

men

tatio

n

yiujProcess

)()( K

heir

Impl

em

H ....

)()( tKxtu =

hms a

nd th Hj

.... .... ........ Si

n: A

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ith

⎤⎡ k

vj ziControl

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gn

[ ]⎥⎥⎥⎤

⎢⎢⎢⎡

==kk

kkkK L 2

1

21ref

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[ ]⎥⎥

⎦⎢⎢

⎣ k

kkkK

m

nM

21

Reactor: modelReactor: modeln

Reactor: modelReactor: modelm

enta

tion

; 216.89-200.3020.928.71-23.088

00.2519- 1.705-

⎥⎥⎥

⎦

⎤

⎢⎢⎢

⎣

⎡=A

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Impl

em

415.29-0

028.6-0 2.918

⎥⎥⎥

⎦

⎤

⎢⎢⎢

⎣

⎡=

⎦⎣

B

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nd th

⎦⎣

n: A

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ithl C

o-de

sign

[ ] [ ]

Con

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[ ] [ ]TjT

ja FFuTTCx == ;

Reactor: controlReactor: controln

Reactor: controlReactor: controlm

enta

tion

{ } { } { }987.236,73.7,5878.2)( −−−== Aeigai 3.247−=nA

C l G lC l G l {{ 320320 340340 360360}}

heir

Impl

em Control Goal: Control Goal: pp = {= {--320320, , --340340, , --360360} ; } ; PPnn= = --10201020

⎤⎡

hms a

nd th

..⎥⎦

⎤⎢⎣

⎡−−−

=5505.02238.4463.40

6683.45676.685.858K

AA FF ti dti d FF

n: A

lgor

ith Assume Assume FF active and active and FFjj open open

{ } { };5.49,1.336,7.405).( 11 −−−=− kbAeig 4.7912 −=→ S

l Co-

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gn

7.2282 =− nPS{ } { };,,)( 11g 2

Con

trol


Give highest priority to most degrading signal failure Give highest priority to most degrading signal failure

New Control ScenariosNew Control Scenariosn

New Control ScenariosNew Control Scenariosm

enta

tion

E b dd d C l SE b dd d C l S

heir

Impl

em Embedded Control SystemsEmbedded Control Systems

hms a

nd th Networked Control SystemsNetworked Control Systems

n: A

lgor

ith

NonNon--regular sampling regular sampling EventEvent--driven controldriven control

l Co-

desi

gnC

ontr

ol


Embedded systemsEmbedded systemsn

men

tatio

nhe

ir Im

plem

hms a

nd th

n: A

lgor

ithl C

o-de

sign

Con

trol



men

tatio

nhe

ir Im

plem

hms a

nd th

n: A

lgor

ithl C

o-de

sign

Control is present in 99% of the Control is present in 99% of the embedded applicationsembedded applications

Con

trol


embedded applicationsembedded applications


Embedded systemsEmbedded systemsm

enta

tion Device:Device:

StandStand--alonealone

heir

Impl

em

NetworkedNetworkedRT operationRT operation

hms a

nd th ES:ES:

Compact and reduced size Compact and reduced size A tA t

n: A

lgor

ith AutonomyAutonomyMissing data operationMissing data operationFaultFault toleranttolerant

l Co-

desi

gn DEVICEFaultFault--toleranttolerantReconfigurabilityReconfigurabilitySafetySafety

Con

trol


SafetySafetyEmbedded control systemsEmbedded control systems


yym

enta

tion Information processing systems embedded into a larger Information processing systems embedded into a larger

productproduct

heir

Impl

em

Main purpose of the product is Main purpose of the product is notnot information information processingprocessing

hms a

nd th Must be Must be

DependableDependable

n: A

lgor

ith DependableDependableEfficientEfficient

l Co-

desi

gn Interactive with its environmentInteractive with its environmentRT constrainedRT constrained

Con

trol


RT constrainedRT constrainedApplication orientedApplication oriented

ES Ch llES Ch lln

ES ChallengesES Challenges

M i i f E b dd dM i i f E b dd d S fS f

men

tatio

n Main issues refer to Embedded Main issues refer to Embedded SoftwareSoftware(not microelectronics / mechatronics)(not microelectronics / mechatronics)

heir

Impl

em Most requirements / applications involve Most requirements / applications involve controlcontrolReactive systemsReactive systems

hms a

nd th

yyRT constraintsRT constraintsEnergy consumptionEnergy consumption

n: A

lgor

ith

Energy consumptionEnergy consumptionEnvironmental adaptationEnvironmental adaptationES controlES control

l Co-

desi

gn ES controlES controlPure control Pure control applicationsapplications

Con

trol


Strong interaction: control and its SW implementationStrong interaction: control and its SW implementation

Embedded Control SystemsEmbedded Control Systemsn

Embedded Control SystemsEmbedded Control Systemsm

enta

tion Embedded systems with:Embedded systems with:

hard RT constraintshard RT constraints

heir

Impl

em

guarantee of safe operationbest possible performances

hms a

nd th best possible performances

Additional issues from viewpoint of:Additional issues from viewpoint of:

n: A

lgor

ith implementationimplementationcomputationcomputation

l Co-

desi

gn

ppalgorithmicalgorithmic

Con

trol


ECSECSn

ECSECSm

enta

tion

heir

Impl

em

ComputerControl under

hms a

nd th

pRT issues

under uncertaintyECS

n: A

lgor

ith

NetworkedSystems

l Co-

desi

gnC

ontr

ol


Embedded Control CharacteristicsEmbedded Control Characteristicsn

Embedded Control CharacteristicsEmbedded Control Characteristicsm

enta

tion What distinguishes embedded control?What distinguishes embedded control?

Limited computing and communication resourcesLimited computing and communication resources

heir

Impl

em

Often massOften mass--market products, market products, e.ge.g, automobiles, automobilesCPU time, communication bandwidth, memory, energy, …CPU time, communication bandwidth, memory, energy, …

hms a

nd th Autonomous operationAutonomous operation

No human ”operator”No human ”operator”

n: A

lgor

ith

ppComplex functionalityComplex functionalityOften large amounts of softwareOften large amounts of software

l Co-

desi

gn

ggNeed for formal approachesNeed for formal approachesNeed for design methodologyNeed for design methodology

Con

trol


g gyg gy

Networked Control SystemsNetworked Control Systemsn

Networked Control SystemsNetworked Control Systemsm

enta

tion

heir

Impl

emhm

s and

thn:

Alg

orith

l Co-

desi

gn

Networked Control SystemsNetworked Control Systems

Con

trol


Networked Control SystemsNetworked Control Systems

N k d C l SN k d C l Sn


enta

tion

11 Identification of control tasks and mapping betweenIdentification of control tasks and mapping between

Basic Approach:Basic Approach:

heir

Impl

em 11. Identification of control tasks and mapping between . Identification of control tasks and mapping between tasks and processing nodes.tasks and processing nodes.

After this mapping the worst case execution time (WCET) of each taskAfter this mapping the worst case execution time (WCET) of each task

hms a

nd th After this mapping, the worst case execution time (WCET) of each task After this mapping, the worst case execution time (WCET) of each task

can be computed as resulting from the target processing architecture.can be computed as resulting from the target processing architecture.

22. Identification of shared information and bus scheduling.. Identification of shared information and bus scheduling.

n: A

lgor

ith

22. Identification of shared information and bus scheduling. . Identification of shared information and bus scheduling. Once the bus access protocols and scheduling have been determined the Once the bus access protocols and scheduling have been determined the worst case for communication delays can be obtained.worst case for communication delays can be obtained.

l Co-

desi

gn 33. Tasks scheduling for each node. . Tasks scheduling for each node. If some task cannot meet its deadline, return to Step If some task cannot meet its deadline, return to Step 1 1 and reassigand reassignn tasks tasks

Con

trol


to nodes.to nodes.

N k d C l SN k d C l Sn


enta

tion

1 Off1 Off line schedulingline scheduling too rigid and not optimaltoo rigid and not optimal

DrawbacksDrawbacks

heir

Impl

em 1. Off1. Off--line scheduling line scheduling too rigid and not optimaltoo rigid and not optimalNeighbor nodes, memory overNeighbor nodes, memory over--consumption. consumption. Control problems in switching between nodes.Control problems in switching between nodes.

hms a

nd th

Control problems in switching between nodes.Control problems in switching between nodes.

2. Resources infra2. Resources infra--utilizationutilizationEverything should be scheduled for the worst case condition withEverything should be scheduled for the worst case condition with

n: A

lgor

ith

Everything should be scheduled for the worst case condition, with Everything should be scheduled for the worst case condition, with random and multiple switchingrandom and multiple switching

3. Control delays over estimation. 3. Control delays over estimation.

l Co-

desi

gn

yyControl algorithms should be design for the longest communication delay,Control algorithms should be design for the longest communication delay,

not being able to change under switching.not being able to change under switching.

Con

trol


… and Improvements: under development!… and Improvements: under development!

Event-driven controlEvent-driven controln

Event driven controlEvent driven controlm

enta

tion

heir

Impl

emhm

s and

thn:

Alg

orith

EventEvent--driven as opposite to timedriven as opposite to time--driven:driven:Event generator (regular sampling data)Event generator (regular sampling data)

l Co-

desi

gn Event generator (regular sampling data)Event generator (regular sampling data)Event processor (data preprocessor)Event processor (data preprocessor)Control action generator (controller)Control action generator (controller)

Con

trol


E D i C lE D i C ln

Event-Driven ControlEvent-Driven Controlm

enta

tion

Natural in networked embedded systemsNatural in networked embedded systems

heir

Impl

em describes the reality (e.g., networked control loops)describes the reality (e.g., networked control loops)a possible modeling formalism for analyzing jittera possible modeling formalism for analyzing jitter

hms a

nd th

p g y g jp g y g jMode changesMode changesDiscrete (binary sensors)Discrete (binary sensors)

n: A

lgor

ith Discrete (binary sensors)Discrete (binary sensors)Can it be combined with Can it be combined with aperiodicaperiodic schedulabiliyschedulabiliy theory?theory?

l Co-

desi

gnC

ontr

ol


Event-driven controlEvent-driven controln

men

tatio

nhe

ir Im

plem

hms a

nd th

F

n: A

lgor

ith F

l Co-

desi

gn

θ

Con

trol


Networked Embedded Control TimingNetworked Embedded Control Timingn

Networked Embedded Control TimingNetworked Embedded Control Timingm

enta

tion

heir

Impl

em

b dd d l f i li lb dd d l f i li l d i id i i

hms a

nd th Embedded control often implies temporal nonEmbedded control often implies temporal non--determinismdeterminism

resource sharing resource sharing preemptions blocking varying computation times nonpreemptions blocking varying computation times non--deterministicdeterministic

n: A

lgor

ith

preemptions, blocking, varying computation times, nonpreemptions, blocking, varying computation times, non deterministic deterministic kernel primitives, …kernel primitives, …

Networked control often implies temporal nonNetworked control often implies temporal non--determinismdeterminism

l Co-

desi

gn network interface delay, queuing delay, transmission delay, propagation network interface delay, queuing delay, transmission delay, propagation delay, link layer resending delay, transport layer ACK delay, ...delay, link layer resending delay, transport layer ACK delay, ...lost packetslost packets

Con

trol

© P. Albertos, 2010© P. Albertos, 2010How should we handle this?How should we handle this?

Design ApproachesDesign Approachesn

Design ApproachesDesign Approaches

SeparationSeparation--ofof--concernsconcerns

men

tatio

n SeparationSeparation--ofof--concernsconcernsTimeTime--triggered approachestriggered approachesSimple, deterministic, dependability, …Simple, deterministic, dependability, …

Control ConcernsControl Concerns

heir

Impl

em

p , , p y,p , , p y,But, difficult to achieve in practice due toBut, difficult to achieve in practice due to

Lack of resourcesLack of resourcesI iI i

hms a

nd th Incorrect assumptionsIncorrect assumptions

Technology incompatibilityTechnology incompatibility

IntegrationIntegration

Computing & Computing & CommunicationCommunication

ConcernsConcerns

n: A

lgor

ith

IntegrationIntegrationOptimize performance subject to limited resourcesOptimize performance subject to limited resourcesCodesign of control computing and communicationCodesign of control computing and communication

l Co-

desi

gn Temporal robustness analysis techniquesTemporal robustness analysis techniquesImplementationImplementation--aware control techniquesaware control techniquesControlControl--aware computing and communication techniquesaware computing and communication techniques

Con

trol


ControlControl--aware computing and communication techniquesaware computing and communication techniquesNew analysis and design toolsNew analysis and design tools

ECS DesignECS Designn

ggm

enta

tion

Taking into account resources constraints

(d l i i d t h i th i d )

heir

Impl

em (delays, missing data, changes in the period …)

the goal of the temporal design methods is to

hms a

nd th

g p g

maintain/maximize the control performance :

n: A

lgor

ith Maximize the time determinismMaximize the time determinismRobust DesignRobust Design

l Co-

desi

gn Active Robust designActive Robust designPrioritize control subtasks: Control KernelPrioritize control subtasks: Control Kernel

Con

trol


RT constraintsRT constraintsn

RT constraintsRT constraints

E i l ithE i l ith

men

tatio

n Economic algorithmsEconomic algorithmsOptional tasks Optional tasks

heir

Impl

em

ppHybrid systems Hybrid systems CPU d i i iCPU d i i i

hms a

nd th CPU use measurement and optimisationCPU use measurement and optimisation

OnOn--line schedulingline scheduling

n: A

lgor

ith

ggMemory saving Memory saving

l Co-

desi

gn Economic hardware redundancyEconomic hardware redundancyFault detection and isolationFault detection and isolation

Con

trol


Fault detection and isolationFault detection and isolation

Control algorithm designControl algorithm design

Models, signals and controllersModels, signals and controllersn

, g, g

d d d d ld d d d l

men

tatio

n Reduced order models Reduced order models NonNon--conventional sampling and updating patternsconventional sampling and updating patterns

heir

Impl

em

Missing data controlMissing data controlEventEvent--triggered controltriggered control

hms a

nd th Decision and supervisory controlDecision and supervisory control

Hybrid control systems Hybrid control systems

n: A

lgor

ith Multimode controlMultimode controlSampling rate changesSampling rate changes

F ltF lt t l t t lt l t t l

l Co-

desi

gn FaultFault--tolerant control tolerant control Degraded and backDegraded and back--up (safe) control strategiesup (safe) control strategies

Con

trol


Battery monitoring and controlBattery monitoring and control

Reduced Order Modeln PP

men

tatio

n ProcessProcess

heir

Impl

em

S1S1KK

hms a

nd th

S2 S3S2 S3S2 S3S2 S3

n: A

lgor

ithl C

o-de

sign

Con

trol

Reduced Order ModelReduced Order Modeln

Reduced Order ModelReduced Order Modelm

enta

tion Model reduction:Model reduction:

Partial control (parts of Partial control (parts of S1

heir

Impl

em the plant)the plant)u y

hms a

nd th

Partial phenomena (fast/slow dynamics)Partial phenomena (fast/slow dynamics)

S2

n: A

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ith -- Partial phenomena (fast/slow dynamics)Partial phenomena (fast/slow dynamics)

[ ] xCC

BxAAx⎥⎤

⎢⎡

⎥⎤

⎢⎡

⎥⎤

⎢⎡⎥⎤

⎢⎡

⎥⎤

⎢⎡ 11112111

l Co-

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gn [ ]k

kkkk x

CCuBxAAx ⎥

⎦⎢⎣

=⎥⎦

⎢⎣

+⎥⎦

⎢⎣⎥⎦

⎢⎣

=⎥⎦

⎢⎣ + 2

121

2

1

2

1

2221

1211

12

1 y ;

Con

trol


modes slow : modes;fast : 21 xx •• Flexible Flexible armarm•• NavigationNavigation

Reduced Order Models: ExampleReduced Order Models: Examplen

ppm

enta

tion No obstacles: manipulator control

Obstacle detection. Navigation controlFinal position: manipulator control

heir

Impl

em Final position: manipulator control

mEnd

hms a

nd th m

n: A

lgor

ith

ECS

l Co-

desi

gn M

Con

trol


Ini

InterventionsInterventionsn

InterventionsInterventions

BrakingBraking

men

tatio

n BrakingBraking

heir

Impl

em

SteeringSteering

hms a

nd th

n: A

lgor

ith

CombinedCombined

l Co-

desi

gn CombinedCombinedsteering andsteering andbrakingbraking

Con

trol


55

ECS: Control Algorithm viewpointECS: Control Algorithm viewpointn

ECS: Control Algorithm viewpointECS: Control Algorithm viewpoint

d d d d ld d d d l

men

tatio


heir

Impl

em


hms a



n: A

lgor



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Con

trol



Non-uniform samplingNon-uniform samplingn

Non uniform samplingNon uniform samplingm

enta

tion

YkSampling patternSampling pattern

heir

Impl

em

y1k y2

k yskys

k-1

hms a

nd th kT0 (k+1)T0

u1k u2

k urk

n: A

lgor

ith

Uk

l Co-

desi

gn

Irregular samplingIrregular samplingTi d lTi d l

k

Con

trol


Time delaysTime delaysRelevance of variablesRelevance of variables

Non- Conventional Sampling & UpdatingNon- Conventional Sampling & Updatingn

Non Conventional Sampling & UpdatingNon Conventional Sampling & Updatingm

enta

tion Non synchronismNon synchronism

Different timingDifferent timingEnvironment

heir

Impl

em

ggCPU sharing &CPU sharing &Communication channelsCommunication channels

ECS

S1 A1

hms a

nd th Communication channels Communication channels

V i bl tiV i bl ti d ld lProcess to

controlSi Ai

n: A

lgor

ith Variable timeVariable time--delaysdelaysDelay counteractionDelay counteraction

B tt

Memory

l Co-

desi

gn Multirate controlMultirate controlCPUBattery

Con

trol


Small changes in the code

Missing data & Event-triggeredMissing data & Event-triggeredn

Missing data & Event triggeredMissing data & Event triggeredm

enta

tion

heir

Impl

em

Sensors failureSensors failureC Ch lC Ch l

Output predictionOutput predictionParameter estimationParameter estimation

hms a

nd th Com. ChannelsCom. Channels

congestioncongestion

Parameter estimationParameter estimation“Virtual sensors”“Virtual sensors”

n: A

lgor

ith Convergence, stabilityConvergence, stability

l Co-

desi

gn

SteadySteady--statestate Compute nothingCompute nothing

Con

trol


Missing DataMissing Datan Th t t i l il bl t ti i t t { }10;1 rr

Missing DataMissing Datam

enta

tion

uk yk

The output is only available at some time instants:

KALMAN Filter

{ }1,0;1 == kk rr

heir

Impl

em

ek +G(q)

L

KALMAN Filter

hms a

nd th

-$kx̂

rkL1ˆ +kx

n: A

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ith

rk1r

ykk

b Iq-1 C

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yk

rk1-rkA

Con

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yk



d d d d ld d d d l

men

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Decision & supervisory controlDecision & supervisory controlnp yp y

Decision based onDecision based on

men

tatio

n

PerformancesPerformancesProcess modelProcess modelOperating conditionsOperating conditionsdecision O ti

heir

Impl

em Operating conditionsOperating conditionsChanges in controllersChanges in controllersChanges in stored dataChanges in stored dataTransientTransient

decisionlogic

Operating conditions

hms a

nd th

TransientTransientHybrid controlHybrid controlStability issuesStability issuesPerformance degradingPerformance degrading

n: A

lgor

ith

Performance degradingPerformance degrading… CPU optimization… CPU optimization

σswitch signalπ

Param. updating

Goalsdisturbance

l Co-

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gn multi-controller process

ucontrol

i l

y measuredoutput

Goals

HT

Con

trol


signalT

Controller commuting: Stability issuesController commuting: Stability issuesn

Controller commuting: Stability issuesController commuting: Stability issuesm

enta

tion

Each controller may stabilize the plant under control

heir

Impl

em Each controller may stabilize the plant under control,But ... what under commuting?

hms a

nd th

Common Lyapunov functionCommon Lyapunov function

n: A

lgor

ith

y py pController initializationController initializationController resettingController resetting

l Co-

desi

gn

gg

Not a problem if seldom changesNot a problem if seldom changes

Con

trol


p gp g

Supervision: Sampling rateSupervision: Sampling raten

men

tatio

nhe

ir Im

plem CPU availabilityCPU availability

Battery levelBattery level

hms a

nd th

Commuting problemsCommuting problemsSt bilitSt bilit

Battery levelBattery levelMode changes Mode changes

n: A

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ith StabilityStabilityTransientTransientChanges in sampling rateChanges in sampling rate

l Co-

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gn Changes in sampling rateChanges in sampling rate

Con

trol




d d d d ld d d d l

men

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Impl

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n: A

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Con

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Fault tolerant controlFault tolerant controln

Fault-tolerant controlFault-tolerant controlm

enta

tion Use the control design freedom toUse the control design freedom to

Ensure stability under sensors/actuators failureEnsure stability under sensors/actuators failure

heir

Impl

em yyGuarantee minimal performancesGuarantee minimal performances

Supervision based faultSupervision based fault tolerant controltolerant control

hms a

nd th Supervision based faultSupervision based fault--tolerant control tolerant control

FDIFDI

n: A

lgor

ith Controller commutingController commutingSafe (backSafe (back--up) operationup) operation

l Co-

desi

gn

(( p) pp) pPower awarenessPower awareness

P il bilit i iP il bilit i i

Con

trol


Power availability supervisionPower availability supervisionMode changesMode changes

RT control implementationRT control implementationn

RT control implementationRT control implementationm

enta

tion The same resources must be The same resources must be sharedshared between between

different tasksdifferent tasks

heir

Impl

em

AlternativeAlternative control control algorithmsalgorithms should be ready to should be ready to get the control of the processget the control of the process

hms a

nd th

g pg pWorking conditionsWorking conditions, such as priority, allocated time , such as priority, allocated time and memory or signals availability may changeand memory or signals availability may change

n: A

lgor

ith and memory or signals availability may changeand memory or signals availability may changeVariable delaysVariable delays should be consideredshould be consideredP i iP i i ff kk

l Co-

desi

gn Priority to Priority to safetysafety taskstasksValidationValidation and certificationand certification

Con

trol


nm

enta

tion

heir

Impl

em

ControlControl KernelKernelControlControl KernelKernel

hms a

nd th Control Control KernelKernelControl Control KernelKernel

n: A

lgor

ithl C

o-de

sign

Con

trol

Kernel ConceptKernel Conceptn

Kernel ConceptKernel Concept

Basic services:Basic services:OS kernel:OS kernel:

men

tatio

n Basic services:Basic services:Task and time managementTask and time managementInterrupt handlingInterrupt handling

OS kernel:OS kernel:

heir

Impl

em Interrupt handlingInterrupt handlingInterface to the applications (API) Interface to the applications (API) Mode changesMode changesOS Kernel str ct reOS Kernel str ct re

hms a

nd th Mode changesMode changes

Fault toleranceFault toleranceAdditional servicesAdditional servicesApplicat ion Tasks

OS Kernel structureOS Kernel structure

n: A

lgor

ith Additional servicesAdditional servicesFile managementFile managementQuality of serviceQuality of service

API

l Co-

desi

gn

Qua ty o se v ceQua ty o se v ceTracing and debuggingTracing and debugging

I t t iTask m anagem ent

M ode t asks

Con

trol

© P. Albertos, 2010© P. Albertos, 2010Hardware

Int errupt services

Kernel ConceptKernel Conceptn

Kernel ConceptKernel Concept

B i iB i iOS kernel:OS kernel:

men

tatio

n Basic services:Basic services:Task and time managementTask and time management

OS kernel:OS kernel:

heir

Impl

em

Interrupt handlingInterrupt handlingInterface to the applications Interface to the applications

hms a

nd th

e ce o e pp c o se ce o e pp c o s(API) (API) Mode changesMode changesMode changesMode changes

n: A

lgor

ith Mode changesMode changesFault toleranceFault tolerance

Additi l iAdditi l i

Mode changesMode changesFault toleranceFault tolerance

l Co-

desi

gn Additional servicesAdditional servicesFile managementFile managementQ lit f iQ lit f i

Con

trol


Quality of serviceQuality of serviceTracing and debuggingTracing and debugging

OS Kernel for controlOS Kernel for controln

OS Kernel for controlOS Kernel for controlm

enta

tion The OS Kernel provides the minimal services that should The OS Kernel provides the minimal services that should

be included in any embedded be included in any embedded controlcontrol system.system.

heir

Impl

em

Fault toleranceFault toleranceDegrade task activity (when a task does not guarantee some timingDegrade task activity (when a task does not guarantee some timing

hms a

nd th Degrade task activity (when a task does not guarantee some timing Degrade task activity (when a task does not guarantee some timing

constraints, the degraded behavior is executed)constraints, the degraded behavior is executed)Change mode events raised when some faults can not be managed.Change mode events raised when some faults can not be managed.

n: A

lgor

ith Mode changesMode changesMode definition (set of tasks associated to a mode) Mode definition (set of tasks associated to a mode)

d h ( h f d h )d h ( h f d h )

l Co-

desi

gn Mode change events (event to change from one mode to another) Mode change events (event to change from one mode to another) Mode change protocolMode change protocol

Con

trol


The control kernel conceptThe control kernel conceptn

The control kernel conceptThe control kernel conceptm

enta

tion

Backup CA Backup CA CACAuseruser

bu

kr

heir

Impl

em

kvkuCACACACA

hms a

nd th

PlantPlantdelivdelivcomputationcomputation

x y

n: A

lgor

ith kx

kmky

DADA

l Co-

desi

gn

Safe operation in any conditionSafe operation in any condition

Con

trol


Safe operation in any conditionSafe operation in any condition

Control KernelControl Kerneln

Control KernelControl Kernelm

enta

tion Ensures control action (CA) deliveringEnsures control action (CA) delivering

Safe (backSafe (back--up) CA computationup) CA computationSafe CA computation based on previous dataSafe CA computation based on previous data

heir

Impl

em Safe CA computation based on previous dataSafe CA computation based on previous dataData acquisition of major signalsData acquisition of major signals

Safe CA computation based on current dataSafe CA computation based on current data

hms a

nd th Transfer to new control structureTransfer to new control structure

Basic control structure parameters computationBasic control structure parameters computationCA t tiCA t ti

n: A

lgor

ith CA computation CA computation

Full DA Full DA

Control KernelControl Kernel

ControllerController

l Co-

desi

gn

Control structures evaluation and selectionControl structures evaluation and selectionCA computation (different levels)CA computation (different levels)

C i ti f ilitiC i ti f iliti


Con

trol


Communication facilitiesCommunication facilitiesCoordination facilitiesCoordination facilities

Control ApplicationControl Applicationn controllercontroller

men

tatio

n

definedefinesend actionssend actions


heir

Impl

em

APIAPIeventseventssend actionssend actions

hms a

nd th DATDAT OATOAT

PeriodPeriodValue, TimeValue, Time

PeriodPeriodOffsetOffset Control KernelControl Kernel

n: A

lgor

ith

Value, TimeValue, TimeThresholdThreshold

Max_latencyMax_latencySafe ValueSafe Value

BackupBackupCurrentCurrent

l Co-

desi

gn

RTOSRTOS

Con

trol


RTOSRTOS

Layers and Interactions of the CKLayers and Interactions of the CKn

Layers and Interactions of the CKLayers and Interactions of the CKm

enta

tion

heir

Impl

em

–– ADQ: Samples of variables.ADQ: Samples of variables.–– REF: Control references.REF: Control references.

hms a

nd th –– ESM: Outputs, references and ESM: Outputs, references and

inputs estimation.inputs estimation.CO: Control commands includingCO: Control commands including

n: A

lgor

ith –– CO: Control commands, includingCO: Control commands, including• Controller commuting• Controller commuting• Change of controllers’• Change of controllers’

l Co-

desi

gn

ggparameters.parameters.

–– SCA: Sending of control actions.SCA: Sending of control actions.d di i fd di i f

Con

trol


–– SDI: State and diagnostic ofSDI: State and diagnostic ofinputs.inputs.

CK MiddlewareCK MiddlewareController

n

Control Kernel

Controllerm

enta

tion

Ap p lic a t io n

heir

Impl

em Ap p lic a t io n

hms a

nd th

N e t w o rk CK

Co m m . M id d le w a re CK M id d le w a re

n: A

lgor

ith

OS

s u p p o rt s u p p o rt

l Co-

desi

gn

H w

Con

trol


CK Middleware functionalitiesCK Middleware functionalitiesn

CK Middleware functionalitiesCK Middleware functionalitiesm

enta

tion

Provides object classes for sensors, actuators, Provides object classes for sensors, actuators,

heir

Impl

em

controllerscontrollers

Remote communication through Comm. MiddlewareRemote communication through Comm. Middleware

hms a

nd th

Remote communication through Comm. MiddlewareRemote communication through Comm. Middleware

Pool of threads at different priority levels (acquisition, Pool of threads at different priority levels (acquisition, data acquisition basic computation)data acquisition basic computation)

n: A

lgor

ith data acquisition, basic computation)data acquisition, basic computation)

Admission control (negotiation)Admission control (negotiation)

l Co-

desi

gn Mode change (task + controllers commutation)Mode change (task + controllers commutation)

Con

trol


CK Middleware functionalities (II)CK Middleware functionalities (II)n

CK Middleware functionalities (II)CK Middleware functionalities (II)m

enta

tion Definition of controller parameters:Definition of controller parameters:

Reduced model controller Reduced model controller

heir

Impl

em

Backup actuationBackup actuation

Sensor characteristics (virtual/real, range, acquisition Sensor characteristics (virtual/real, range, acquisition

hms a

nd th

( / , g , q( / , g , qperiod, filter, threshold, ...period, filter, threshold, ...

Actuator characteristicsActuator characteristics

n: A

lgor

ith

CallCall--back functionback function

Compute RMController (locally)Compute RMController (locally)

l Co-

desi

gn Compute RMController (locally)Compute RMController (locally)

Con

trol


CK Middleware structureCK Middleware structure Controllern

CK Middleware structureCK Middleware structureControl Kernel

men

tatio

nhe

ir Im

plem

hms a

nd th

n: A

lgor

ithl C

o-de

sign

Con

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Controllern

CK Middleware structureCK Middleware structure Control Kernel

Data acquisitionData acquisition

men

tatio

n Data acquisitionData acquisition

heir

Impl

emhm

s and

thn:

Alg

orith

l Co-

desi

gnC

ontr

ol


CK Middleware structureCK Middleware structuren

men

tatio

n

Each physical sensor S has: Each physical sensor S has:

heir

Impl

em

S = {T, B, C, E}, S = {T, B, C, E}, T: sampling period, T: sampling period,

hms a

nd th B: buffer n last values, B: buffer n last values,

C: the controller functionC: the controller function

n: A

lgor

ith E: the sensor state {fail, event, E: the sensor state {fail, event, no_failno_fail}}Acquisition qualityAcquisition quality

l Co-

desi

gn

Via data acquisition interval (DAI) conceptVia data acquisition interval (DAI) concept

Con

trol


CK Middleware structureCK Middleware structure Controllern

CK Middleware structureCK Middleware structureControl Kernel

men

tatio

n ActuationActuation

heir

Impl

emhm

s and

thn:

Alg

orith

l Co-

desi

gnC

ontr

ol


CK Middleware structureCK Middleware structuren

C dd ew e s uc u eC dd ew e s uc u em

enta

tion Each physical actuator A has: Each physical actuator A has:

A= {T, O, B, R, C, E} A= {T, O, B, R, C, E} ActuationActuation

heir

Impl

em

T: sampling period,T: sampling period,O: Offset between delivering of the action and O: Offset between delivering of the action and

hms a

nd th

ggacquisition of data. acquisition of data. B: buffer n last values.B: buffer n last values.

n: A

lgor

ith R: To store the n future references values. R: To store the n future references values. C: the controller function.C: the controller function.

l Co-

desi

gn

E: the sensor state {fail, event, E: the sensor state {fail, event, no_failno_fail}}

Delivering actions quality Delivering actions quality

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e ve g act o s qua tye ve g act o s qua tyVia data acquisition interval (CAI) conceptVia data acquisition interval (CAI) concept

Control Kernel structureControl Kernel structuren

Control Kernel structureControl Kernel structurem

enta

tion

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Impl

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s and

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Alg

orith

S:{T,B,C,E}S:{T,B,C,E}E: FailE: Fail

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gn E: FailE: FailRepeatRepeatNormalNormal

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Control Kernel structureControl Kernel structuren

Control Kernel structureControl Kernel structurem

enta

tion

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Impl

emhm

s and

th

A {T O B R C E}A {T O B R C E}

n: A

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S:{T,B,C,E}S:{T,B,C,E}E: FailE: Fail

A:{T,O,B,R,C,E}A:{T,O,B,R,C,E}E: FailedE: FailedRepeatedRepeated

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gn E: FailE: FailRepeatRepeatNormalNormal

NormalNormal

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CK layoutCK layoutn

CK layoutCK layoutm

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tion

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Impl

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s and

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Alg

orith

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ontr

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CK detailCK detailn

CK detailCK detailm

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AnalyzeAnalyze

S ervice node

C t l K l

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R T OS

C ontrol K ernelMiddleware

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nd th

C ontrol K ernel Middleware

L ight nodeuo(k)us(k)

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S witching

uf(k)P lant

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S implecontroller

us(k)

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Scheduling PoliciesScheduling Policies Controllern

Scheduling PoliciesScheduling PoliciesControl Kernel

men

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n

Several scheduling policies can Several scheduling policies can coexist depending on the thread level.coexist depending on the thread level.

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Kernel threads (Kernel threads (DAThreadDAThread and and OAThreadOAThread) are executed ) are executed as part of the RTOS Both are periodic and ser eas part of the RTOS Both are periodic and ser e

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nd th as part of the RTOS. Both are periodic and serve as part of the RTOS. Both are periodic and serve

acquisition and delivery actionsacquisition and delivery actions

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ith

Both have a Both have a queuequeue were requests are served on deadline were requests are served on deadline basis. basis.

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Values are written/read to/from control kernel Values are written/read to/from control kernel

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middleware. middleware.

ImplementationImplementationn

ImplementationImplementationm

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Current version of the CK Middleware has been implemented Current version of the CK Middleware has been implemented in Cin C

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The RTOS used is The RTOS used is PartiKlePartiKle and openand open--source source rtosrtos which is the which is the new core ofnew core of RTLinux GPLRTLinux GPL

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nd th

new core of new core of RTLinux_GPLRTLinux_GPL

It can be executed in x86 or ARM processorsIt can be executed in x86 or ARM processors

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Different execution platformsDifferent execution platforms

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CONCLUSIONSCONCLUSIONSn

CONCLUSIONSCONCLUSIONSm

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Need of Codesign of Control algorithms and their implementationNeed of Codesign of Control algorithms and their implementationFlexibility in the control scenariosFlexibility in the control scenarios

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em Embedded, networked, eventEmbedded, networked, event--drivendrivenDistribution of the computing resourcesDistribution of the computing resourcesLi it ti i C i ti d C tiLi it ti i C i ti d C ti

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nd th Limitations in Communication and ComputingLimitations in Communication and Computing

Control safetyControl safetyDifferent treatment of:Different treatment of:

n: A

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ith Different treatment of:Different treatment of:Signals: Relevance and Control EffortSignals: Relevance and Control EffortTasks: Control KernelTasks: Control Kernel

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s s: Co o e es s: Co o e eModels and goals: resource availabilityModels and goals: resource availability

Integration of the control algorithm in the computing activitiesIntegration of the control algorithm in the computing activities

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CoCo--DesignDesign

RELIABLE SOFTWARE TECHNOLOGIESRELIABLE SOFTWARE TECHNOLOGIESADAADA--EUROPE 2010EUROPE 2010

nm

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Control Co-design: Algorithms and Control Co-design: Algorithms and

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hms a

nd th

n: A

lgor

ith P. Albertos, A. P. Albertos, A. CrespoCrespo, J. , J. SimóSimóDpt. Dpt. IngIng. de . de SistemasSistemas y y AutomáticaAutomática

I iI i dd A á iA á i I f á iI f á i I d i lI d i l

P. AlbertosP. Albertos A. A. FernándezFernándezDpt. Dpt. AutomáticaAutomática y y ComputaciónComputación

C A b C bC A b C b

l Co-

desi

gn InstitutoInstituto de de AutomáticaAutomática e e InformáticaInformática IndustrialIndustrialUniversidad Universidad PolitécnicaPolitécnica de Valenciade Valencia

[email protected]@aii.upv.es

CUJAE, Habana. CubaCUJAE, Habana. [email protected]@electrica.cujae.edu.cu

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VALENCIA, SPAIN, VALENCIA, SPAIN, 1414--18 18 JUNE JUNE 20102010

Control Co-design: Algorithms and Their Implementation

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Transcript of Control Co-design: Algorithms and Their Implementation