Software Intensive Complex Control Systems

Autonomous Systems LaboratoryAutonomous Systems Laboratory

A

Software Intensive Complex Software Intensive Complex Control SystemsControl Systems

Ricardo SanzRicardo SanzUniversidad Politécnica de MadridUniversidad Politécnica de Madrid

Exystence WorkshopExystence WorkshopMachine Consciousness: Complexity AspectsMachine Consciousness: Complexity Aspects

29th September – 1st October29th September – 1st OctoberISI, TorinoISI, Torino

22Exystence Workshop / R.Sanz / Torino 2003Exystence Workshop / R.Sanz / Torino 2003

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Autonomous Systems LaboratoryAutonomous Systems LaboratoryA

MotivationMotivation

Control system complexity is continuously Control system complexity is continuously increasing and reaching consciousness increasing and reaching consciousness levelslevels


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Purpose of the TalkPurpose of the Talk

Provide an overview of the field of control Provide an overview of the field of control systemssystems

Provide an overview on the role of Provide an overview on the role of software in control systemssoftware in control systems

Describe the trends toward conscious Describe the trends toward conscious controllerscontrollers


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ContentsContents

Introduction to control systemsIntroduction to control systemsBasic control structuresBasic control structuresSoftwareSoftware−−intensive controllersintensive controllersComplex control systemsComplex control systems

Exystence Workshop / R.Sanz / Torino 2003Exystence Workshop / R.Sanz / Torino 2003


A

Introduction to Introduction to control systemscontrol systems

A fast overviewA fast overview


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What is Automatic Control ?What is Automatic Control ?

Science and technology Science and technology of of artificial autonomyartificial autonomy


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Why Autonomy?Why Autonomy?

SafetySafety: put humans in the safe side: put humans in the safe sidePerformancePerformance: superhuman speed or : superhuman speed or

tolerancestolerancesSizeSize: necessary miniaturization: necessary miniaturizationEconomyEconomy: humans should be paid: humans should be paid

... today, “... today, “totaltotal” autonomy is not ” autonomy is not (economically) advisable for a complex (economically) advisable for a complex systemsystem


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Automatic ControlAutomatic Control

DomainDomainKnowledgeKnowledge

ElectronicsElectronics

MathematicsMathematics

ComputingComputing



A

Basic Control StructuresBasic Control Structures

Common control patternsCommon control patterns


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Open loop controlOpen loop control

PlantControllersetpointcontrolaction output


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Closed loop controlClosed loop control

PlantControllersetpointcontrolaction output

feedback

This is called a “feedback controller”

Xerror

disturbances


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Adaptive controlAdaptive control

PlantControllersetpoint

controlaction

output

feedback

Xerror

disturbances

Controlleradjustment

controllerparameters


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FeedForward controlFeedForward control

PlantControllersetpoint

controlaction

output

feedback

Xerror

disturbancesPlantModel

Predicteddisturbance

X



A

A General Control StructureA General Control Structure

Extracting CommonalitiesExtracting Commonalities


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General Structure (I)General Structure (I)

Plant

Sensor ActuatorThinker

Model

Controller


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General Structure (II)General Structure (II)

Plant


Model


Model


Model

Level 1

Level 2

Level 3


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ControllerController

General Structure (III)General Structure (III)




Controller

Controller

Controller Controller Controller

From hierachies to heterarchies and beyond

Plant

Exystence Workshop / R.Sanz / Torino 2003Exystence Workshop / R.Sanz / Torino 2003 1818


A

Control Structure EvolutionControl Structure Evolution

Fathers and sons in control Fathers and sons in control systemssystems


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Flight ControlFlight Control (I) (I)

Airplane

Movements of control surfaces Airplane attitude

Feedback of airplane status (visual, vestibular)


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Flight Control Flight Control (II)(II)

Flight Control Airplane

Feedback of airplane status (sensors)

Airplane attitudeMovements of

control surfaces

Desired airplane attitude


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Flight Control Flight Control (III)(III)

OperationsControl

Desired Course


Feedback of airplane status (sensors)

Airplane attitude

Movements of control surfaces



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Flight Control (Flight Control (IVIV))

MissionControl

Desired Route

FMSFlight Management

Systems

OperationsControl

Desired Course


Feedback

Attitude

MoveSurfaces



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Flight Control SystemsFlight Control SystemsLockheed L-749 ConstellationLockheed L-749 Constellation 19451945 Crew: 5 menCrew: 5 men

Pilot,Pilot, Co-pilot, Co-pilot, Flight engineer,Flight engineer, Navigation, Navigation, RadioRadio

Boeing 777Boeing 777 19951995 Crew: 2 peopleCrew: 2 people

Pilot,Pilot, Co-pilotCo-pilot

What for 2045?



A

ExamplesExamples

Concrete examples of control Concrete examples of control systemssystems


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Sensor ActuatorModel-derivedThinker

Controller

Cruise speed controlCruise speed controlDesired Speed

Real Speed Gas


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Space Robotic ArmSpace Robotic ArmG

lob

al M

em

ory

Glo

bal

Me

mo

ryG

lob

al M

em

ory

Glo

bal

Me

mo

ry

Op

era

tor

Inte

rfa

ceO

pe

rato

r In

terf

ace

Op

era

tor

Inte

rfa

ceO

pe

rato

r In

terf

ace

G1G1G1G1 M1M1M1M1 H1H1H1H1ServoServo

SenSensese ActAct

G2G2G2G2 M2M2M2M2 H2H2H2H2PrimitivPrimitivee

G3G3G3G3 M3M3M3M3 H3H3H3H3MovMovementement

G4G4G4G4 M4M4M4M4 H4H4H4H4TaTasksk

G5G5G5G5 M5M5M5M5 H5H5H5H5ServicServicee

SenseSense ModelModel ActAct

NASREMNASREM


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Teleoperation with a touchTeleoperation with a touch


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RCSRCS

OP

ER

AT

OR

IN

TE

RF

AC

E

SP WM BG

SP WM BG

SP WM BG

SP WM BG

Points

Lines

Surfaces

SP WM BG SP WM BG

SP WM BG

0.5 second plans Steering, velocity

5 second plans Subtask on object surface Obstacle-free paths

SP WM BGSP WM BG

SP WM BGSP WM BG SP WM BG

SERVO

PRIMITIVE

SUBSYSTEM

SURROGATE SECTION

SURROGATE PLATOON

SENSORS AND ACTUATORS

Plans for next 2 hours

Plans for next 24 hours

0.05 second plans Actuator output

SP WM BGSP WM BG SP WM BG SP WM BG SP WM BG SP WM BG SP WM BG SP WM BG

Objects of attention

LocomotionCommunication Mission Package

VEHICLE Plans for next 50 seconds Task to be done on objects of attention

Plans for next 10 minutes Tasks relative to nearby objects

Section Formation

Platoon Formation

Attention

Battalion Formation SURROGATE BATTALION

Hiearchical Robotic ControllerHiearchical Robotic Controller


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Process Control (I)Process Control (I)

Cooler

Feed

Product

Cooler

stir

CSTRCSTR


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Process Control (II)Process Control (II)

Basic controlBasic control Single variable feedbackSingle variable feedback

Advanced controlAdvanced control Multivariable control loopsMultivariable control loops Model-based control loopsModel-based control loops

Supervisory controlSupervisory control Human monitorisation of controlled system Human monitorisation of controlled system

statestate


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Sense

Act

ControlControl

PlantPlant

SupervisorSupervisor

Process Control (III)Process Control (III)

Sense

Act


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Process Control (IV)Process Control (IV)


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Process Control (V)Process Control (V)

Strategic ControlStrategic Control

Complex LoopsComplex Loops

Advanced ControlAdvanced Control

Operational ControlOperational Control

Tactical ControlTactical Control

Sensors & ActuatorsSensors & Actuators

Simple LoopsSimple Loops

Management Information SystemManagement Information System

PlantPlant

Optimization

Plan execution

Reactivity

Conventional Process Control

Use

r In

terf

ace

Use

r In

terf

ace



A

Software intensive controlSoftware intensive control

Increasing the intelligence of Increasing the intelligence of controllerscontrollers


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Elements of IntelligenceElements of Intelligence

Behavior GenerationBehavior Generation -- Planning and Execution -- Planning and ExecutionWorld ModelingWorld Modeling -- Data Management, -- Data Management, Estimation,Estimation,

PredictionPredictionSensory ProcessingSensory Processing -- Group, Filter, Compare -- Group, Filter, CompareValue JudgmentValue Judgment -- Compute value and confidence -- Compute value and confidenceKnowledgeKnowledge -- Images, Symbols, Objects, -- Images, Symbols, Objects, CommunicationsCommunications -- Syntax, Semantics, Connectivity -- Syntax, Semantics, Connectivity

Elements of Consciousness ?


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Reaching the limitsReaching the limits

ODE and PDE modeling and control do ODE and PDE modeling and control do not fulfill our needs for high autonomynot fulfill our needs for high autonomy

New computing technologies from New computing technologies from different sources are used in controller different sources are used in controller implementationimplementation

AI technologies are common in industrial AI technologies are common in industrial control todaycontrol today


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Intelligent ControlIntelligent Control

Fusion of Fusion of Automatic ControlAutomatic Control and and Artificial Artificial IntelligenceIntelligence??

Soft approachesSoft approaches to control systems: to control systems: Expert, fuzzy, neural, genetic, etcExpert, fuzzy, neural, genetic, etc

Control systems with a Control systems with a high content of high content of sophisticated ITsophisticated IT


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Examples of technologiesExamples of technologies Intelligent control Intelligent control

architecturesarchitectures Knowledge based Knowledge based

systems systems Temporal logicsTemporal logics Learning control Learning control Agent technologyAgent technology Planning systemsPlanning systems Machine learningMachine learning Neural networks Neural networks Genetic algorithmsGenetic algorithms Fuzzy logic Fuzzy logic

Pattern recognition Pattern recognition Knowledge-based sensor Knowledge-based sensor

fusionfusion Neuro-fuzzy and neuro-Neuro-fuzzy and neuro-

adaptiveadaptive Intelligent sensors and Intelligent sensors and

actuatorsactuators Evolutionary controlEvolutionary control Distributed and Distributed and

embedded systemsembedded systems Expert systemsExpert systems Distributed intelligenceDistributed intelligence


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RiskRisk ManManagementagement


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Strategic Process ControlStrategic Process Control

Operator Wrappers

Support Core Functions

IRDB

VM IM

CIM21 LABUIOI

Object Request BrokerObject Request Broker

PPSI AMOAQDED


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Millitary Robotic ScoutsMillitary Robotic Scouts

XUV IIXUV II


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““Ultimate” ArchitecturesUltimate” Architectures

Soar, BB1, ACT, EPIC, Prodigy, TCA, Soar, BB1, ACT, EPIC, Prodigy, TCA, Subsumption, ATLANTIS, RAP, PRS, Subsumption, ATLANTIS, RAP, PRS, RCS, NASREM, AFREB, Entropy RCS, NASREM, AFREB, Entropy Reduction Engine, NMRA, 3T, GLAIR, Reduction Engine, NMRA, 3T, GLAIR, Theo, Phoenix, CONEX, Icarus, IRMA, Theo, Phoenix, CONEX, Icarus, IRMA, PRS, EPAM, CIRCA, SIMPLEX, Jam!, PRS, EPAM, CIRCA, SIMPLEX, Jam!, OCA, OSACA, OPENDreams, …OCA, OSACA, OPENDreams, …

etc., etc, etc.etc., etc, etc.



A

Complex control systemsComplex control systems

Complexity raising in controllersComplexity raising in controllers


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Software Control ContextSoftware Control Context

Control systems do perform a Control systems do perform a dynamical dynamical interactioninteraction with real world entities (they are with real world entities (they are closed loop systems). closed loop systems).

Their Their complexitycomplexity can range from a simple can range from a simple thermostatthermostat or or pacemakerpacemaker to an to an Airbus AFCSAirbus AFCS or or a a country-wide energy management systemcountry-wide energy management system. .

Control systems do pose Control systems do pose problems of wider and problems of wider and deeper scopedeeper scope than most other software systems: than most other software systems: e.g. distribution, hard real-time behavior, fault-e.g. distribution, hard real-time behavior, fault-

tolerance, embedded, long life-span (10-40 years), tolerance, embedded, long life-span (10-40 years), model-based construction, formal verification, model-based construction, formal verification, scalability, dependable systems of systems, scalability, dependable systems of systems, complexity, etc.complexity, etc.


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Complex Control SystemsComplex Control Systems

Control systems are Control systems are software-intensivesoftware-intensive applications that are becoming extremely applications that are becoming extremely complex as new functionality is required from complex as new functionality is required from them. them.

Emergent complexityEmergent complexity is a major engineering is a major engineering challenge as embedded distributed systems challenge as embedded distributed systems technology raises massive concurrency and technology raises massive concurrency and interaction issuesinteraction issues

Control systems complexity is of Control systems complexity is of HOTHOT type more type more than than SOCSOC type type


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Field Management

Process Management

Business Management

Continuous Process Plant

Fieldbus

Control Network

Enterprise Network

Process Control

MIS

Data Storage

Process Operation

Field Configuration

Sensing and Acting

Safety

Plant-wide ControlPlant-wide Control


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Total-Ship SystemsTotal-Ship SystemsTotal Ship C&C Center


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Car Control SystemsCar Control SystemsBody Electronics Network

DriverInterface

CC

PowerTrain

CC

I/O

AssistantSystem

CC

SteeringManager

CC

I/O

GatewayBody

CC

I/O

Suspen-sion

CC

I/O

BrakeManager

CC

I/O


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Object Request Broker

Browser

Application

JTIDS

Controls &

Displays

Link 16 Interface Software

F-15 JTIDS TerminalC2 JTIDS Terminal

Virtual TargetFolder

Open Weapon SystemsOpen Weapon SystemsCollaboration

ServerC4I

Simulation

Quality of Service Management

Quality ObjectFramework

Link 16 Interface Software

Pluggable ProtocolPluggable Protocol

CollaborationClient

Link 16

C2C2 F-15F-15

Resource Mgmt

Adaptive

September 2003September 2003


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Level(6) Platoon

Level(5) Section

Level(2) Prim

Level (3) Subsystem

Level(4) Vehicle

Level(1) Servo

ImagesTopological Entity Frames

Generic Class Frames

Specific Class Frames

Planner: Look_ahead(1 hour) every 5 min Generate 10 waypoints(5 min apart) Executor: Compute output every (100s)

Task: Go_to_point(aijkm1) Arrive at t + 30 msec

Task: Go_to_point(aijk1) Arrive at t + 300 msec

Task: Go_to_point(aij1) Arrive at t + 3 seconds

Task: Go_to_point(ai1) Arrive at t + 30 seconds

Task: Go_to_point(a) Arrive at t + 1 hour

Planner: Look_ahead(300ms) every 30 ms Generate 10 waypoints(30ms apart) Executor: Compute output every (10ms)

Planner: Look_ahead(3s) every 300 ms Generate 10 waypoints(300ms apart) Executor: Compute output every (100ms)

Planner: Look_ahead(30s) every 3 s Generate 10 waypoints(3s apart) Executor: Compute output every (1s)

Planner: Look_ahead(5 min) every 30 s Generate 10 waypoints(30s apart) Executor: Compute output every (10s)

Planner: Look_ahead(30ms) every 10 ms Generate 10 waypoints(3ms apart) Executor: Compute output every (3ms)

3 ms

Read Sensors

and Goal

Compute Output

Send to Actuator

Wait

Position, Orientation, Velocity, Acceleration Sensors

Estimated State Variables Position Velocity Acceleration

Pixel attributes

SP level 1 classify pixels compute pixel attributes measure pixel attributes

SP level 2 classify list entities confirm patch & edge entities compute patch & edge attributes group pixels into list entities

SP level 3 classify surface entities compute 100x100 m map compute surface attributes group into surface entities

SP level 4 classify object entities compute 1x1 km map compute object attributes group into object entities

SP level 1 Filter and compute state variables

SP level 5 classify section entities compute 10x10 km map compute squad attributes group into squad entities

SP level 6 classify platoon entities compute 100x100 map compute platoon attributes group into platoon entities

SENSORY PROCESSING

SHORT TERM KNOWLEDGE DATABASE

BEHAVIOR GENERATION

Task: Go_to_point(a1) Arrive at t + 5 minutes

Eg

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he

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oo

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ate

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ActuatorsCameras and LADAR

Wo

rld

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ate

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Platoon Image

100x100 km map 30 m res

Maps

LONG TERM KNOWLEDGE DATABASE

10x10 km map 3 m res

Section Image

Object Image 100x100 m

map 30 cm res

Image with labled entities

Surface & Boundary Images

Edge Patch Vertex Images

Image with labled entities

Pixel attribute images

IMMEDIATE EXPERIENCE

WORLD MODELING

4-D/RCS System Architecture4-D/RCS System Architecture


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Complex SoftwareComplex Software

Types of systemsTypes of systems ConventionalConventional Real-timeReal-time EmbeddedEmbedded Fault TolerantFault Tolerant DistributedDistributed IntelligentIntelligent

Special ProblemsSpecial Problems SizeSize IntegrationIntegration HeterogeneityHeterogeneity

What is complex software?What is complex software?


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Software Design ChallengesSoftware Design Challenges

PredictabilityPredictabilityPerformancePerformanceScalabilityScalabilityOpennessOpennessCoordinationCoordinationTransparencyTransparencyNamingNamingCostCost

ConsistencyConsistencyFailure handlingFailure handlingSecuritySecurityHeterogeneityHeterogeneityMobilityMobilityLoad sharingLoad sharingFootprintFootprintetc.etc.


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Complexity and developmentComplexity and development

Complexity affects developmentComplexity affects developmentEffort grows with complexity much more than Effort grows with complexity much more than

linearlylinearlyThere are There are systems we cannot buildsystems we cannot build::

24x365 (total availability)24x365 (total availability) One-shot (at the first try)One-shot (at the first try) HF-LC (High Performance / Low Cost)HF-LC (High Performance / Low Cost)

In search of In search of silver bulletssilver bullets:: Complex control software engineering ?Complex control software engineering ?


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ComplexityComplexityHigher technical complexity - Embedded, real-time, distributed, fault-tolerant - Custom, unprecedented, architecture reengineering - High performance, conscious

Lower technical complexity - Mostly 4GL, or component-based - Application reengineering - Interactive performance

Highermanagement complexity - Large scale - Contractual - Many stake holders - “Projects”

Lowermanagement complexity - Small scale - Informal - Single stakeholder - “Products”

Plant-wide DCS

Star WarsSatellite

Telephone

CASE Tool

European ATCSystem

MIS

CommercialCompiler

PID

DOC BusinessApplication

UnitSimulation

Plant Simulation

EmbeddedAutomotive

Software

GUI/RDB

Sojourner

Self-raisingrobot

TelephoneNetwork


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The Control ChallengesThe Control Challenges

Solve “artistic” problemsSolve “artistic” problems Like Hilbert’s 20 problemsLike Hilbert’s 20 problems

Build Build autonomous + reflectiveautonomous + reflective entities entities Plants operating in 365x24 regimesPlants operating in 365x24 regimes Mobile systems in real environmentsMobile systems in real environments Fault-tolerant systemsFault-tolerant systems Auto-optimizing systemsAuto-optimizing systems


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Complexity ForcesComplexity Forces Intelligence Intelligence

Expert, fuzzy, neuralExpert, fuzzy, neural RobustnessRobustness

Adaptive, robust, fault-tolerant, reflectiveAdaptive, robust, fault-tolerant, reflective Non-linearityNon-linearity

Non-Linear, Hybrid Non-Linear, Hybrid SizeSize

Multivariable, distributedMultivariable, distributed ConcurrencyConcurrency

Agent-based, networkedAgent-based, networked IntegrationIntegration

Systems of systems, legacies Systems of systems, legacies


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Any hope ?Any hope ?

New control software paradigms are New control software paradigms are needed to tackle complexityneeded to tackle complexity Componentize and composeComponentize and compose

• An approach based on systems engineeringAn approach based on systems engineering• Problems of composabilityProblems of composability

Evolve and protectEvolve and protect• An approach based on emergent systemsAn approach based on emergent systems• Problems of unpredictabilityProblems of unpredictability

Strong emphasis on architectureStrong emphasis on architecture Control + software + intelligenceControl + software + intelligence


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Some Complexity AttacksSome Complexity Attacks

Brute forceBrute force: : MoneyMoney It needs power: It needs power: SupercomputingSupercomputing

ApproximationApproximation: : WorkWork Poor man approach: Poor man approach: LinearizationLinearization

Divide and conquerDivide and conquer: : EngineeringEngineering Needs knowledge: Needs knowledge: ModularizationModularization

Change of viewChange of view: : TheoryTheory It needs It needs deepdeep insight: insight: Conceptual revolutionConceptual revolution


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Conscious Complex ControllersConscious Complex Controllers

Dr. Chandra ... ?Dr. Chandra ... ?

Software Intensive Complex Control Systems

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Transcript of Software Intensive Complex Control Systems