Cyber Physical Systems – Collaborating Systems of Systems

1© 2012 The MathWorks, Inc.
Complex Systems as Collaborating
Systems of Systems
Pieter J. Mosterman
Joachim Schlosser
3rd International Conference on Complex
Systems Design & Management
Dec 12-14, Paris

3
<
Photos: audrey_sel, oomlout on Flickr, License CC-BY-SA, AMagill on Flickr, License CC-BY

4
The Importance of Computation
Today, about 98 percent of microprocessors are
embedded, connected with the outside world
through sensors and actuators. They are
increasingly connected with one another and the
internet. The physical world and the virtual
world – or cyberspace – are merging.
Today, about 98 percent of microprocessors are
embedded, connected with the outside world
through sensors and actuators. They are
increasingly connected with one another and the
internet. The physical world and the virtual
world – or cyberspace – are merging.
Source: acatech: agendaCPS.

5
Source: European Commission: ICT FP7 Work Programme 2013, ICT Challenge 2: Cognitive Systems and Robotics
[…] initiates a research and innovation
agenda, aiming to develop artificial
systems operating in dynamic real life
environments, reaching new levels of
autonomy and adaptability and interacting
in a symbiotic way with humans.
[…] initiates a research and innovation
agenda, aiming to develop artificial
systems operating in dynamic real life
environments, reaching new levels of
autonomy and adaptability and interacting
in a symbiotic way with humans.
[…] next generations of ICT systems and
products with more intelligence will open
the door to a wide range of opportunities
for ICT-based applications in a range of
sectors.
ICT systems – including robot and
robotic systems – need to be more
robust, context-aware and easy-to-
use.
[…] next generations of ICT systems and
products with more intelligence will open
the door to a wide range of opportunities
for ICT-based applications in a range of
sectors.
ICT systems – including robot and
robotic systems – need to be more
robust, context-aware and easy-to-
use.

6
Source: Forschungsunion: Where the New Growth Comes From.
Information and communication technology (ICT)
will play an ever greater active role in value-
creation processes. Intelligent networks will
simulate, monitor and optimise products and
systems.
Information and communication technology (ICT)
will play an ever greater active role in value-
creation processes. Intelligent networks will
simulate, monitor and optimise products and
systems.

7
Simulation saves money
Source: M. Broy, H. Krcmar, J. Zimmermann, S. Kirstan: Economical impact of model-based development of embedded software systems in
cars. ATZ elektronik worldwide, 2/06, April 2011 (link)
Correlation modeling degree and test intensity in the software design
versus changes in the total costs
… say Broy et.al. in ATZ elektronik:

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Outline
1. Introduction – Cyber-Physical Systems
2. Value of computational semantics –
Model-Based Design
3. Heterogeneity of computational
semantics
4. Best Practices

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Introduction – Cyber-Physical Systems

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Computation as main feature differentiator
Image: SketchUp Trimble 3D Gallery, rendered in Kerkythea

13

14

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System integration
System Integration
Timing
Concurrency
Interfaces
Shared resources
…

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System integration
Image: Pieter Mosterman in SketchUp, with elements from Trimble 3D Gallery, rendered in Kerkythea

20
Image: Pieter Mosterman in SketchUp, with elements from Trimble 3D Gallery, rendered in Kerkythea

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Cyber-Physical Systems
Open
Robust
Natural

30
Information
Network
Physics
Information

31
Cyber-physical systems
Information
Network
Physics

32
Physics
Information
Network
Electronics

33
RatingRating
Lift off
accelerator
↓
Roll to
accelerate
↓
Scania Develops Fuel-Saving Driver
Support System for Award-Winning
Long-Haulage Trucks
―Simulink is particularly helpful
in two stages of our
development process. Early on,
it helps us try new ideas and
visualize how they will work.
After generating code and
conducting in-vehicle tests, we
can run multiple simulations,
refine the design, and regenerate
code for the next iteration.‖
Jonny Andersson
Scania
―Simulink is particularly helpful
in two stages of our
development process. Early on,
it helps us try new ideas and
visualize how they will work.
After generating code and
conducting in-vehicle tests, we
can run multiple simulations,
refine the design, and regenerate
code for the next iteration.‖
Jonny Andersson
Scania
The Scania Driver Support display panel.
Image: Jonny Andersson, Scania. MathWorks Automotive Conference 2010

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Value of Computational Semantics –
Model-Based Design

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Physics
Information
Network
Electronics

36
Design of heterogeneous systems
 Executable models
– Quick feedback on design options
– Automate design tasks
– Automate synthesis tasks
– …
 Computational semantics
Physics
Information
Electronics
Network

37
Design of heterogeneous systems
 Executable models
– Quick feedback on design options
– Automate design tasks
– Automate synthesis tasks
– …
 Computational semantics
 Execution engine
– Combines many formalisms
Executionengine

38
Heterogeneity in computational solutions
Information
ODE
Statemachine
Discrete time
Control flow
Electronics
Discrete event
DAE
Network
Discrete event
Statemachine
Physics
DAE
Statemachine

39
Modeling domains Disciplines
Simulink
Simulink
SimEvents
Stateflow
Simscape
SimElectronics
SimMechanics
SimHydraulics
SimDriveline
MATLAB
ODEODE
Discrete timeDiscrete time
Discrete eventDiscrete event
StatemachineStatemachine
DAEDAE
Control flowControl flow
Physical environmentPhysical environment
Digital hardwareDigital hardware
Analog/RF hardwareAnalog/RF hardware
Embedded softwareEmbedded software
Mechanical hardwareMechanical hardware
Electrical hardwareElectrical hardware
Heterogeneity in computational solutions

40
Computational semantics of heterogeneous
systems
?
Extensive code base
Approximating and interacting solvers
Extensive code base
Approximating and interacting solvers
Approximations
Numerical integration
Algebraic equations
Zero crossings
Chattering
Timing
Magnitude
Numerical algorithms
…

41
systems
?
Approximations
Numerical integration
Algebraic equations
Zero crossings
Chattering
Timing
Magnitude
Numerical algorithms
…
Point solutions
Generate individual behaviors separately
Point solutions
Generate individual behaviors separately

42
systems
Works (well) for standard scenarios
Environment is treated as a disturbance
Works (well) for standard scenarios
Environment is treated as a disturbance

43
systems
An open system must work for all scenarios
Gaps are exposed
An open system must work for all scenarios
Gaps are exposed

44
systems
<S,R>
Static analysis?
O(M) lines of code … ?
Static analysis?
O(M) lines of code … ?

45
systems
Model the execution engine!
Separate semantics from implementation
Model the execution engine!
Separate semantics from implementation

46
systems
!
Analyze classes of behavior
Prove absence of holes

47
systems
!

48
Fabrycky: ―Synthesis is the interesting thing
in system design‖
!
IMPLEMENTATION
Structured
Text
VHDL, VerilogC, C++
MCU DSP FPGA ASIC PLC
(quote from yesterday)
Information
ODE
Statemachine
Discrete time
Control flow

49
Heterogeneity
of Computational Semantics

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Towers of Hanoi – Not a Centralized System?

A Cyber-Physical System!
Justyna Zander and Pieter J. Mosterman, “Technical Engine for Democratizing Modeling, Simulation, and Prediction," in
Winter Simulation Conference, December, 2012, in review
Justyna Zander and Pieter J. Mosterman, “Technical Engine for Democratizing Modeling, Simulation, and Prediction," in
Winter Simulation Conference, December, 2012, in review

57
slider
nozzle
rails
block R
block B
nozzle motor
slider motor
block G
air pump
gravity

59
Local Control Rules (simplified)
 Red Block: wants to be on top
– If on top  move 1 left, wait, then 1 left with low prio
– If not on top  move 1 left, 1 right, 2 left
 Green (Yellow) Block: wants to be middle
– Move 1 left, then 1 left
 Blue Block: wants to be on bottom
– Move 2 left
– Should have the highest priority

60
Scenarios—emerging behavior

61
informationinformation
networknetwork
physicsphysics
nozzle motor
slider motor
air pump
scene view
slider position
stereo camsstereo cams
block camblock cam
computing
node
computing
node
NCAPNCAP
NCAPNCAP
NCAPNCAP
base
computing
node
base
computing
node
slider
computing
node
slider
computing
node

62
left
camera
left
camera
right
camera
right
camera
slider
motor
slider
motor
nozzle
motor
nozzle
motor
slider ECUslider ECU
pump
actuator
pump
actuator
pressure
slider force
wireless networkwireless network
nozzle_mode,
left_video, right_video
found, picked,
placed, nozzle_force
found, picked, placed
block_status, position
nozzle_mode,
slider_force, pressure
position
sensor
position
sensor
supervisory
control
supervisory
control
slider
control
slider
control
detection
logic
detection
logic
nozzle
control
nozzle
control
stereo
analysis
stereo
analysis
pump
control
pump
control
NCAPNCAPNCAPNCAPNCAPNCAP
position
block_service
left_video right_videonozzle_force
block
camera
block
camera
block ECUblock ECU
service
requests
service
requests
scenescene
An Architecture
base ECUbase ECU

65
Example: Slider
Electric drive
Camera controlled

67
Slider control
 Exert a motor force to move the slider to a give position
 Compute a Gaussian (lqg) regulator (output feedback)
– r = desired slider position
– u = motor force
control plant
r y
vw
u
 






















 
dtxQx
u
x
QXUux
T
EuJ
T
iii
Tu 0
,
1
lim)(min
 dtyrx
T
i  
0

68
Slider control
 Plant model
 Requires a linear plant model
– The slider/rail friction ruins it …
plant
y
vw
u
vDuCxy
wBuAx
dt
dx



69
rightleft
left
right
left
right
Stereopsis
dx dx
cameras
field of view

70
rightleft
Stereopsis
cameras
field of view
a
b
c
x
(a-b)/c = a/x
x = ac/(a-b)
http://www.alexandria.nu/ai/blog/entry.asp?E=32

71
Stereoscopic analysis
 Embarrassingly parallel
XORXOR
left video frame right video frame

72
Example: Nozzle
Air flow actuators
State logic

74
Nozzle control
 Feedforward (very fast) control
 Two phases (down/up)
– Staged force profiles
– Predetermined profiles for set of possible lowpoints
 Top of a stack of two blocks
 Top of a stack of one block
– Lookup table for each lowpoint

75
Nozzle control coordinator
 Provide as a service
– Profile must be defined in relative time
– Reset operation state after completion
 Allows initialization of relative variables
– Hold off pick or place operation till the service is available

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Example: The Blocks
Self contained logic

82
A Cyber-Physical System?

86
―Accurate modeling is essential not only for planning
investments but also to detect situations that can cause
an outage. […] we can simulate power electronics,
mechanics, and control systems in one environment,
and our models respond like the turbines we have in the
field.‖
Richard Gagnon
Hydro-Québec
―Accurate modeling is essential not only for planning
investments but also to detect situations that can cause
an outage. […] we can simulate power electronics,
mechanics, and control systems in one environment,
and our models respond like the turbines we have in the
field.‖
Richard Gagnon
Hydro-Québec
Link to user storyTurbines on a wind farm

87
CAD and Functional Simulation

88
25 years ago CAD disrupted construction.
Image Sources: customized030 on Flickr, License CC-BY-ND, Siemens PLM Software on Flickr, License CC-BY-ND

89
Now Model-
Based Design &
Simulation
disrupt engineering.

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4 Practices of Early Verification

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Create and
simulate a
high-level system
model during the
specification stage.
#1

92
Image Sources: Peter Jackson on Flickr, License CC-BY
 Dynamic behavior
 System insight

93
#2 Test from
day one with
multidomain
simulation.

94
Image Sources: eha1990 on Flickr, License CC-BY
vs.
Model
• wires
• steel
• C code

95
#3Create virtual
test suites
that stress the
system.

96
Simulations are
easier to scale.
Image Sources: torkildr on Flickr, License CC-BY-SA

97
Technische Universität München Uses Model-Based Design to Drive
Research, Problem-Based Learning, and Industry Collaboration
Link to user story
Professor Holzapfel, research fellow Markus Hornauer, and a student test flight control
algorithms in the Research Flight Simulator.
―Flight controls and flight system
dynamics are multidomain engineering
disciplines. MathWorks tools enable our
students to build upon our fundamental
research to develop solutions that fly in
real aircraft. With Model-Based Design
we can close the gap between the
theoretical foundation and the practical
application.‖
Prof. Dr.-Ing. Florian Holzapfel
Technische Universität München
―Flight controls and flight system
dynamics are multidomain engineering
disciplines. MathWorks tools enable our
students to build upon our fundamental
research to develop solutions that fly in
real aircraft. With Model-Based Design
we can close the gap between the
theoretical foundation and the practical
application.‖
Prof. Dr.-Ing. Florian Holzapfel
Technische Universität München

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#4Use the model
and test suites as a
reference
design.

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INTEGRATION
IMPLEMENTATION
DESIGN
TEST&VERIFICATION
RESEARCH REQUIREMENTS
Environment Models
Mechanical
Control Algorithms
Electrical
Supervisory Logic
TEST
SYSTEM
TEST
SYSTEM
Structured
Text
VHDL, VerilogC, C++
MCU DSP FPGA ASIC PLC
Start Testing on Day One

Cyber Physical Systems – Collaborating Systems of Systems

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