embracing complexity - mathworks · embracing complexity the festo bionic handling ... student...

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Embracing Complexity Embracing Complexity

Embracing Complexity

Gavin Walker

Development Manager

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1970 Stanford Ph.D. thesis,

with thousands of lines of

Fortran code

MATLAB and Simulink Proven Ability to Make the Complex Simpler

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MATLAB and Simulink Proven Ability to Make the Complex Simpler

Credit: SwRI

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So why am I talking about

EMBRACING complexity?

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Possible Grand Challenges

Zero automotive traffic fatalities, injuries minimized, and

significantly reduced traffic congestion and delays

Blackout-free electricity generation and distribution

Perpetual life assistants for busy, older or disabled people

Energy-aware buildings

Location-independent access to world-class medicine

Raj Rajkumar, Carnegie Mellon University

Kang Shin, University of Michigan

Insup Lee, University of Pennsylvania

Excerpted, with permission

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Collaborate

Model

Simulate

Automate

How do we do it?

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Power

Management

Transmission

Engine Ride Control

ABS

Steering

Stability Controls

Traction Control

Obstacle

Detection

Adaptive

Cruise Control

Crash

Avoidance

Airbags

Adaptive Front

Lighting Systems

Passenger

Detection

Windows Doors

Lights

Climate Controls

Driver Drowsiness Infotainment

Instrumentation

Voice

Recognition

Navigation

Wireless

Connectivity

Functions in Today’s Automobile

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Automatic Cruise

Control (ACC)

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Automatic Cruise

Control (ACC)

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ACC integrates with

engine control

electronic stability

program

braking system

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Platform for Collaboration

Behaviour Modelling

& Code Generation

Software Architecture Definition

BSW Configuration

& RTE Generation

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Neuroimaging of Brain Activity

PET

SPECT

EEG

MEG

fMRI

Function?

Structure?

Connectivity?

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Courtesy: Wellcome Trust Centre

for Neuroimaging, UCL, UK

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Courtesy: Wellcome Trust Centre

for Neuroimaging, UCL, UK

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Physical

Sensors

Data

Information

Knowledge

Action

Data Analysis

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Observation

Organization

Understanding

Application

Physical

Sensors

Data

Information

Knowledge

Action

Data Analysis

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Observation • Sensing

• Collecting

• Data Acquisition

Organization

Understanding

Application

Data Analysis

DAQ and

instrumentation

Cameras

Files, programs,

Web

Databases

Data warehouses

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Organization • Filtering

• Signal Analysis

• Data Reduction

• Plotting

Understanding

Application

Data Analysis

MPG Acceleration Displacement Weight Horsepow er

MP

GA

ccel

erat

ion

Dis

plac

emen

tW

eigh

tH

orse

pow

er

50 1001502002000 4000200 40010 2020 40

50

100

150

200

2000

4000

200

400

10

20

20

40

Data

Processing

Visualization

Exploratory

Analysis


• Collecting


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Application

Understanding • Visualization

• Predictive Analytics

• Frequency/Time-domain

Data Analysis

Estimation and

Prediction

Analytics • Pre-built algorithms

• Evaluate, compare, customize

Domains • Time & Frequency

• Image, video

• Geospatial

• etc.

Decision Tree

Ensemble

Method

Neural Network

Support Vector

Machine

Classification

Linear

Non-linear

Non-

parametric

Regression

0 20 40 60 80 100 120 140 160 180 200

0.5

0.6

0.7

0.8

0.9

1

time secs

activ

e po

wer

per

-uni

t

NN

measured

0 5 10 15 20 25 30 35 40 450

0.2

0.4

0.6

0.8

1

1.2x 10

-4

turbine number

MS

E


• Signal Analysis

• Data Reduction

• Plotting


• Collecting


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Application • Reporting

• Apps

• Scalable Deployment

Data Analysis

Reports

MATLAB

Apps

Integration into

Existing

Systems Excel

Feedback for

Design &

Operations

Understanding • Visualization

• Predictive Analytics

• Frequency/Time-domain


• Signal Analysis

• Data Reduction

• Plotting


• Collecting


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From Data to Knowledge to Action

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Modelling and Simulation

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Modelling and Simulation

Simulink Master Class:

Physical

Modelling with

SimScape

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Collaborate

Model

Simulate

Automate

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Automation

Automated task can be done by

anyone

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Automation

Automation brings mistake-

proofing

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Automation

Automate the common but

especially the complex

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The Festo Bionic Handling

Assistant. Image © Festo AG.

■ PLCs

■ FPGAs

■ DSPs

■ Microcontrollers

■ Rapid prototyping

■ HIL testing

■ Embedded systems

Automatic Code Generation

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Video © Festo AG.


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“Using Simulink for Model-Based Design enables us

to develop the sophisticated pneumatic controls

required for the Bionic Handling Assistant and other

mechatronic designs. With Simulink PLC Coder, it is

now much easier to get from a design to a product.”

Dr. Rüdiger Neumann, Festo

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The Festo Bionic Handling

Assistant. Image © Festo AG.

■ PLCs

■ FPGAs

■ DSPs

■ Microcontrollers

■ Rapid prototyping

■ HIL testing

■ Embedded systems


The Alenia Aermacchi M-346.

■ Automatic Code

Generation

■ Certified Process

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Challenge Develop the company’s first DO-178B Level A certified

autopilot system

Solution Use Model-Based Design to model the system and

software design, verify requirements coverage, generate

code, and produce reports and other artifacts for the

certification authority

Results Requirements review for certification up to 30% shorter

Time-to-flight reduced by 20%

Low-level certification activities automated

Alenia Aermacchi Develops Autopilot

Software for DO-178B Level A Certification

“For us, a key advantage of

Model-Based Design is the

ability to concentrate on design

and development instead of low-

level coding, verification, and

certification tasks. The result is

higher quality, DO-178B certified

software, and faster iterations.”

Massimiliano Campagnoli

Alenia Aermacchi

The Alenia Aermacchi M-346.

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Building the Foundations

Technical Computing:

Enhancing Numerical

Analysis Education

with MATLAB

Innovative Course Design

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LEGO® MINDSTORMS® NXT Student Contest

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Easy-to-Build Devices Programmable Hardware

+

+ Model-Based Design:

Modelling, Simulation,

and Real-Time Testing

for Model-Based

Design

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LEGO® MINDSTORMS® NXT Student Contest Cambridge University ECO Racing

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Possible Grand Challenges

Zero automotive traffic fatalities, injuries minimized, and

significantly reduced traffic congestion and delays

Blackout-free electricity generation and distribution

Perpetual life assistants for busy, older or disabled people

Energy-aware buildings

Location-independent access to world-class medicine

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Used by permission of Prof. Chris Gerdes,

Stanford University School of Engineering

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“We want to use every bit of the car’s capability to be as safe as possible. We want to develop autonomous vehicles

that can avoid any accident that is physically possible to avoid.”

Professor Chris Gerdes

Stanford University

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… and instinctive driver reactions



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… and instinctive driver reactions



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… adding drift and countersteering



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Autonomous Vehicles

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Autonomous Traffic Management

► Can use information

from other vehicles

when available

► Robust when other

vehicles aren’t

similarly equipped

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Collaborate

Model

Simulate

Automate

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What will you need

to embrace

complexity

embracing complexity - mathworks · embracing complexity the festo bionic handling ... student...

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