1© 2019 MathWorks GmbH

Model-Based Design of Industrial Applications

Invited Speaker Session

Swiss Federal Institute of Technology

Zurich, Switzerland.

September 18, 2019

Vasco Lenzi

Senior Application Engineer

MathWorks Switzerland

Dr. Mohamed Anas

Engineering Group Manager

MathWorks Benelux and Switzerland

Dr. Res Jöhr

Senior Customer Success Engineer

MathWorks Switzerland

2

Expectations, Let’s Interact

▪ Leiv: why does MATLAB index start at 1?

▪ Samuel: See something about Statefow

▪ Michael: why should I spend several thousands, when there is FOSS?

▪ Varin: why do you develop new versions, what is the future of MATLAB?

▪ Manish: I have used Git and Stateflow together, I am unsure as to why this

combination does not work as good as Git directly from terminal

▪ Nicola: we heard in the lecture that more an more C code is generated,

what proportion of the C code is automatically generated, what’s the trend?

▪ Friedrich: how could you use cloud computing from MATLAB, like AWS

3

Campus-Wide License Overview

▪ License covers all faculty, staff, students and their devices

▪ Access on campus, in lab and field, and at home, including off-network

▪ Annual license

▪ Immediate tool availability for end users via self-serve portal

▪ Lower IT administration overhead

▪ Storage of existing perpetual licenses

MATLAB Drive

Online access

University & lab

computers

Personal Computers

& Mobile Devices

Auto-graded homework

Low-cost hardware support

Self-paced online learning

Cloud Storage &

Sharing

Clusters & HPC

4

Free MathWorks Online Training @ ETH Zürich

(https://trainingenrollment.mathworks.com/selfEnrollment?code=2I4DV9S0RY14)

5

Agenda

▪ Model-Based Design in the Industry

▪ Workflows and Example Case Studies

▪ Project and Requirements Management

▪ Techniques for Large-Scale Modelling

▪ Early Verification and Production Code Generation

▪ Software- and Processor- in-the-Loop Techniques

6

Agenda

▪ Model-Based Design in the Industry

▪ Workflows and Example Case Studies

▪ Project and Requirements Management

▪ Techniques for Large-Scale Modelling

▪ Early Verification and Production Code Generation

▪ Software- and Processor- in-the-Loop Techniques

7

Three Things to Takeaway!

1. Verify early through Simulation

2. Elaborate Models Incrementally

3. Code and Data Interfaces! Integration Process

Coding Process

Design Process

Requirements Process

8

CO

NT

INU

OU

S T

ES

TIN

G

& V

ER

IFIC

AT

ION

INTEGRATION

CODE

Structured

Text

VHDL

Verilog

DSP FPGA ASICIndustrial

Control IDE

C, C++

MCU

DESIGN

Multi-Domain Physical Systems

Control Algorithms

Signal Processing Communications

Supervisory Logic

Testing,

Verification,

Validation and

Documentation

Technologies

Multi-Domain

Modelling,

Simulation and

Analysis

Technologies

Code

Generation

Technologies

REQUIREMENTSRESEARCH

Model-Based Design of Industrial Applications

9

Our Customers

Millions of engineers and scientists worldwide use MATLAB and Simulink.

All of the top 10

aerospace companies2

All of the top 10

auto manufacturers1

Three of the top five

internet companies

1OICA: 2016 World Motor Vehicle Production 2PwC: Aerospace and Defense 2017 Year in Review

90,000+ business,

government, and

university sites

10

Aero Automotive Biological Sciences

Biotech and

Pharmaceutical Communications

Electronics Energy Production Financial Services Industrial Machinery Medical Devices

Metals, Materials,

Mining Neuroscience Railway Systems Semiconductors Software and Internet

Serving Customers Across Diverse Industries

11

Industrial Example 1

12

Hyperloop

“What we Simulate is What we Implement” ABB

▪ “…components belonging to

different engineering domains”

▪ “…connect and integrate Simulink

diagrams with hardware”

▪ “…more with less steps along the

way”

Source: ABBhttps://library.e.abb.com/public/.../AC%20800PEC%20Sales%20Brochure.pdf

13

Industrial Example 2Optimizing cost with Simulation and Digital Twins

14

Industrial Example 3

15

Agenda

▪ Model-Based Design in the Industry

▪ Workflows and Example Case Studies

▪ Project and Requirements Management

▪ Techniques for Large-Scale Modelling

▪ Early Verification and Production Code Generation

▪ Software- and Processor- in-the-Loop Techniques

16

Agenda

▪ Model-Based Design in the Industry

▪ Workflows and Example Case Studies

▪ Project and Requirements Management

▪ Techniques for Large-Scale Modelling

▪ Early Verification and Production Code Generation

▪ Software- and Processor- in-the-Loop Techniques

17

Large-scale Modelling

▪ Many teams on the same project

▪ Architecture as the basis of team structure

▪ Incremental planning

▪ Interdependencies

▪ Streamlined sharing

▪ Synchronization among teams

▪ CICD

▪ May more

18

Architect with Components

Subsystems

Libraries

Model Referencing

Data Stores

Composite Signals

Configuration Reuse

Variant Subsystems

A

Model Architecture

Share with Teams

Many More

19

Architect with Components

20

Team Workflows

▪ Source control

▪ Compare and Merge

▪ Dependency analysis

▪ Task automation

21

Team Workflows: Dependency Analysis

Show Model

Structure

List Products

Required

Highlight Issues

22

Team Workflows: Dependency Analysis

Show Model

Structure

List Products

Required

Highlight Issues

23

Metrics DashboardAssess your Project Quality Status

24

Sharing: Package Your Work

25

Agenda

▪ Model-Based Design in the Industry

▪ Workflows and Example Case Studies

▪ Project and Requirements Management

▪ Techniques for Large-Scale Modelling

▪ Early Verification and Production Code Generation

▪ Software- and Processor- in-the-Loop Techniques

26

Validate the Results

Formulate Equations

Identify System Components

System Definition

Construct Simulink Diagram

(Controller and Plant)

Run the Simulation

Tune Controller

Things you have done so far

27

Example Activities around Code Generation

▪ Incremental model elaboration ensuring the model is “embedded

application aware”

▪ Defining data representation

– simulation vs. code generation behaviour

▪ Generating code

▪ Automating build processes

▪ Integrating external code with generated code

▪ Setting up generated code to interface with components in the run-time

environment

▪ Verifying the generated code

28

Concluding Remarks

▪ Identify the problem you are trying to solve

▪ “Rule of Two”

▪ Use models to generate production code

▪ Models are the sole source of truth

▪ Use the transition as a learning opportunity

▪ Focus on design instead of coding

▪ Integrate the development process

▪ Designate a champion

▪ Have a long-term vision

▪ Partner with tools suppliers