Cyber-physical Systems – A UMIC Perspective€¦ · Cyber-physical Systems: Consequences ! The...

Cyber-physical Systems – A UMIC Perspective

Stefan Kowalewski

©Prof. Dr-‐Ing. Stefan Kowalewski

Cyber-physical Systems: Characteristics

§  Integration of control systems with web/internet/cloud services

§  Closing of control loops via networks §  Dynamic changes to the composition, structure,

interconnection, and requirements of CPS at runtime -  Permanent upgrades and additions of functionality („apps“) -  Dynamically changing environments/contexts -  Rapidly changing requirements


Cyber-physical Systems: Consequences

§  The boundary between design-time and run-time is blurring.

§  Changes will be partly unforeseeable and discrete in nature.

§  Success of a control system is critically depending on its ability to efficiently cope with such changes

§  à Need for appropriate methods

§  à Need for appropriate IT platforms

Folie 4 / Westerkamp / Januar 2013

Positionspapier des GMA-Fachausschusses 7.20 „Cyber-Physical Systems“

Thesen und Handlungsfelder „Cyber-Physical Systems: Chancen und Nutzen aus Sicht der Automation“ April 2013

Kowalewski Juli 2014


Von der Automatisierungspyramide zur CPS-basierten Automation

Automatisierungspyramide

Betriebsleitebene

Prozess-leitebene

Steuerungs-ebene

Feld- ebene

CPS-basierte Automation

echtzeit-kritisch

Unternehmens-leitebene


Statusreport des GMA-Fachausschusses 7.20 „Cyber-Physical Systems“

Industrie 4.0 CPS-basierte Automation „Forschungsbedarf anhand konkreter Fallbeispiele“ Juli 2014 •  3 Fallbeispiele •  4 Themenbereiche Als Konkretisierung und Ergänzung des Whitepapers „Forschungs- und Entwicklungsaktivitäten“ der Plattform Industrie 4.0

Statusreport

Industrie 4.0

CPS-basierte Automation

Forschungsbedarf anhand konkreter Fallbeispiele

CPS-basierte Automation: Forschungsbedarf anhand konkreter Fallbeispiele

Juli 2014



Vier Themenbereiche im Überblick

1.  Übertragung von Standard-IT-Lösungen 2.  Anpassung von Automatisierungslösungen 3.  Änderungsfähigkeit zur Laufzeit 4.  Durchgängiges Systems-Engineering



Vier Themenbereiche im Überblick

1.  Übertragung von Standard-IT-Lösungen 2.  Anpassung von Automatisierungslösungen 3.  Änderungsfähigkeit zur Laufzeit 4.  Durchgängiges Systems-Engineering



Three examples

Real-time capable

mobile devices Run-time validation Architecture

DPL

M1 M2 M3

V1 V2 V3 V6V4 V5

Wrapper

Operating System

Hardware Abstraction Layer


Three examples

Real-time capable


DPL

M1 M2 M3

V1 V2 V3 V6V4 V5

Wrapper

Operating System



Android

§  RTAndroid -  Real-time capable scheduling -  Automatic real-time Garbage Collection -  Reliable wireless communication -  Accessing peripheral I/O -  Full backward compatibility

Run9me Libraries

Applica9on Framework

Applica9ons

Linux Kernel


§  Android 2.2 §  CPU: 528 MHz §  RAM: 192 MB

Available Hardware

§  Android 4.2.2 §  CPU: 2 x 1.7 GHz §  RAM: 2 GB

Google G1 Google Nexus 10 Galaxy S4

§  Android 4.2.2 §  CPU: 4 x 1.9 GHz §  RAM: 2 GB


Scheduling Latency

§  Periodic execution: every 5 ms §  Non-RT process vs. RT process §  Additional CPU load

0

200

400

600

800

1000

0 5000 10000 15000 20000

Late

ncy

7780 2449

0 5000 10000 15000 20000 0

200

400

600

800

1000

Late

ncy

[ms] [µs] Non-RT Process RT Process


Proof of concept: Android-PLC

§  Everything on a single device -  Write PLC programs -  Compile -  Generate UI -  Run and simulate I/O

Write Execute

Parse Generate Compile

Shared Library

C++ {}

Abstract Syntax Tree

ST

Original Code Generated Code

§  Model transformation & code generation


Performance Evaluation

PROGRAM PLC_PRG1 VAR i : DINT; counter : DINT; END_VAR VAR_OUTPUT out : BYTE; END_VAR FOR i := 0 TO 10000 DO counter := counter + 1; END_FOR out := out + 1; END_PROGRAM

Structured Text

Device Avg. (µs) Max. (µs)

ABB PM554 5000,0 6000,0

Google G1 1072,3 1220,7

Nexus 10 128,6 182,2

§  PLC: ABB PM554 §  RTAndroid

-  Google G1 and Nexus 10 -  Inside a real-time process -  With or without CPU load


Three examples

Real-time capable


DPL

M1 M2 M3

V1 V2 V3 V6V4 V5

Wrapper

Operating System


Formal Verifica9on of SoRware

Code (or Model)

Formal Model

Requirements

Formal Specifica9on

Checking Algorithm

sa9sfies?

„Yes“ Hint for bug search

Model of PLC Program Execu9on

PLC program

var1=7, var2=10

Inputs Outputs 0 0 12

TRUE

47 FALSE FALSE 0


PLC program

var1=7, var2=10

Inputs Outputs

in out var

0 0 12

TRUE

47 FALSE FALSE 0

“State”:


in out var


in

in’ in’’

out

out’’ out’

var

var’ var’’


in

in’ in’’

out

out’’ out’

var

var’ var’’

... ... ... ...


in

in’ in’’

out

out’’ out’

var

var’ var’’

... ... ... ...

Searching the “State Space”

input0, input1 INPUT

output0 OUTPUT

var0 GLOBAL

Type BYTE 0..255

input0 = 0 3

255

2 255 1

… …

input1 =

0

1 0 0 0 0

… …

… …

IF input0+50 =< 100 THEN output0 := var0;

ELSE var0 := input1;

ENDIF;

Searching the “State Space”: Abstrac9on

25

input0, input1 INPUT

output0 OUTPUT

var0 GLOBAL

Type BYTE 0..255

input0 =

…

input1 =

…

… [0, 49] [0, 255]

[50, 255] [0, 0]

[50, 255] [50, 255] [1, 1] [255, 255]

IF input0+50 =< 100 THEN output0 := var0;

ELSE var0 := input1;

ENDIF;

Example: Value Set Analysis in ARCADE.PLC

26


Three examples

Real-time capable


DPL

M1 M2 M3

V1 V2 V3 V6V4 V5

Wrapper

Operating System



Example: Extra-corporal membrane oxygenation (ECMO)

2.0 l/min 2.0 l/min 2.0 l/min 2.0 l/min 2.0 l/min 2.0 l/min


ECMO: State of the art

•  Completely manual operation

•  Permanent supervision


Automated ECMO à SmartECLA (extra-corporal lung assistance)


Measurement Validation - Blood Gas Sensor


According Simulink Model


Software System Architecture

Operating System


Data Provisioning Layer

Model

Wrapping Layer


Wrapping Layer in Detail

DPL

M1 M2 M3

V1 V2 V3 V6V4 V5

Wrapper

Operating System



Workflow Generation(exhaustive)

Model development

Translation (RTW)

Preprocessor

Compiler

S-Functions

Simulink Model

C-Code

universal DPL

Customised Code (specialized DPL)

Binary (ELF)



Thank you!

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Cyber-physical Systems – A UMIC Perspective€¦ · Cyber-physical Systems: Consequences ! The...

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