an introduction to model based design -hardware in loop

1. REAL TIME EMBEDDED CONTROL SYSTEMS
USING MBD CONCEPT
Eng. Mahmoud Hussein
18-oct-19 RTECS 2019
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2. Contact Person
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 Course Instructor
 Mahmoud Hussein
 Lecturer assistant, French university
 Email: Mahmoud.ahmed2013@gmail.com
 Mobile: 01007148378
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3. Rules
13
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4. ‫الذكية‬ ‫للصواريخ‬ ‫القومى‬ ‫المشروع‬
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Which methodology will you use to develop a SAM?
A: Manually Write Assembly
B: Manually Write C-Code
C: MBD: Auto-Code Generation
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5. Welcome to
Real Time Embedded Control Systems
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6. Course Objective
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 The course shows one design path for real time embedded systems.
 It starts by system level simulation based design.
 It ends by real time implementation of control algorithms.
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7. Course Syllabus
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 Part 1 : Introduction to Matlab and Simulink
 Recognize MATLAB and Simulink Environment
 MATLAB Fundamentals and Basic Operations
 M-File and Programming Basics
 Data Visualization (2D/3D)
 State flow.
 S-function
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8. Course Syllabus
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Part 2 : Basics and Modelling
 Introduction to Real Time Embedded Control Systems
 Physical System Modelling of Mechanical Systems
 Dynamic SystemAnalysis
 Physical System Modelling of Electrical Systems
 Modelling Electric Motors
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9. Course Syllabus
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Part 3: Control and PID
 Control Systems
 PID Controller
 Tuning PID Controllers
 Numerical Integration
 PID Advanced Topics
 Digital Controller Design
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10. Course Syllabus
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Part 4: Advanced Topics
 Embedded Coder .
 State Machine Concept.
 MathWorks Automotive Advisory Board- MAAB(Optional)
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11. Tools
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 Matlab & Simulink
 Control System Toolbox
 Simulink Control Design
 State Flow
 Embedded Coder
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12. Domains of Appplication of Embedded
Systems
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Control Systems
• Vehicles
• Appliances
General Computing
• ATM
• Video Games
Signal Processing
• Radar, Sonar
• Video Processing
Communication &
Networking
• Moblie Phones
• Servers

13. Real Time Embedded Control Systems Applications
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Steam Turbine
Control
Flight Control
Print Head
Control
Navigation
Control
Engine Control
Dryer Cycle
Control
Medical Device
Control

14. Model Based Design
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15. Model Based Design
• In Model-Based Design, a system model is at the center of the
development process, from requirements development, through
design, implementation, and testing.
• The model is a graphical representations of math-based simulation
methods.
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16. Elements of Model Based Design
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17. Elements of Model Based Design
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Model
Executable
Specificatio
n
Design with
Simulation
Automatic
Code
Generation
Continuous
Test and
Verification

18. Executable Specification
• Executable
• The model can be simulated to illustrate functional behavior.
• Specification
• An explicit design intended to meet certain requirements.
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19. Elements of Model Based Design
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Model
Executable
Specification
Design with
Simulation
Automatic
Code
Generation
Continuous
Test and
Verification

20. Design with Simulation
• Use simulate during the design stage to verify that the model meets
the requirements, detect and correct errors early in the design stage
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21. Elements of Model Based Design
21
Model
Executable
Specificatio
n
Design with
Simulation
Automatic
Code
Generation
Continuous
Test and
Verification

22. Coding Traditional Approach
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Problems:
• Communication
• Ambiguity of specs
• Resource conflicts
 Large turnaround time!
Production
Code
Specs
Function Developer
 algorithm
knowledge
#include <math.h>
if (a > 0)
ki = 0.4*x+z1;
Software Specialist
 implementation
& coding knowledge
Time

23. Automatic Code Generation
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Function Developer
 algorithm
knowledge
Software Specialist
 implementation
knowledge
Coding knowledge:
• ANSI-C
• language extensions
• assembly language
• processor architecture
 … and how to
optimally use it!
Code Generator
 coding knowledge

24. Automatic Code Generation Features
• Scheduling and integration with RTOS
• MISRA C
• Autosar
• Customizable code
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25. Automatic Code Generators
• TargetLink from dSPACE, since 1999
• Real-Time Workshop Embedded Coder from
MathWorks
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26. Automatic Code Generation
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Implementation Model
(fixed-point)
C CodeCode generator
Compiler
(Linker)
Host PC
Target
Physical Model
(floating-point)
Cross-compiler
(Linker / Loader)

27. Automatic Code Generation
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Implementation Model
(fixed-point)
C CodeCode generator
Compiler
(Linker)
Host PC
Target
Physical Model
(floating-point)
Cross-compiler
(Linker / Loader)

28. Elements of Model Based Design
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Model
Executable
Specification
Design with
Simulation
Automatic
Code
Generation
Continuous
Test and
Verification

29. Continuous Test and Verification
• Deign test cases to test the model
• Reuse test cases to test software implementation
• Simulation models enable to test conditions that would be
destructive or cost-prohibitive to run in the lab or on the road
• Automatically generating test cases from the model to ensure
Modified Condition/Decision Coverage (MC/DC)
• Writing the MC/DC tests would take as least as long as the original design
effort
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30. RTECS 2010
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


test output
result
comparison
physical model
implementation model
test stimuli
C code (target)
ECU
MiL (physical model)
MiL (impl. model)
SiL
PiL
C code (host)

31. Model in the Loop (MIL)
• Proof of Concept and Design Optimization
• Pure simulation
• Modelling of both the application and the
environment may be wrong
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Controller
running in e.g. Simulink
Plant
running in e.g. Simulink

32. Software in the Loop (SIL)
• Compiled application
• Simulation at an early stage
• Accelerated simulation
• Low cost & short development time
• Non real-time
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Controller
running as binary
Plant
running in e.g. Simulink

33. Processor in the Loop (PIL)
• Determining Memory Usage
• Determining the time needed for the Algorithm
• Assures that the tool chain does not cause problems
• Determining problems related to the resolution of
the processor (16 bits, 32 bits, fixed point)
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Controller
running on target HW
Plant
running in e.g. Simulink

34. MIL SIL PIL
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35. Hardware in the Loop (HIL)
• HIL system replaces the real world environment
• Production hardware can be tested without any
changes
• Application is executed in real time on an
appropriate hardware platform
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Controller
running on target
Plant
Running in real-time on a HIL
Simulator

36. HIL Simulator: dSPACE
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Dynamic
Models
Processor Board
I/O Board
GUI and
Automation
Diagn. Tool
ECU
Loads
FIU

37. User Interface for Interactive Use of the HIL System
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38. Networked HIL Simulation
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Vehicle
dynamics
Comfort
(central unit)
Transmission Engine
GigaLink
CAN
2004 Audi A6

39. Networked HIL Simulation
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Mercedes-Benz 2005 A-Class
Breadboard Table
appr. 8 powertrain
and chassis ECUs
appr. 20 body ECUs

40. What is a Model?
RTECS 2014
15
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41. What is a Model?
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A model is a representation of a real system focusing onsome
important aspects
 Scale model
 Represents geometric proportions
 Flight simulator
 Focuses on flight dynamics
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42. What is a Model?
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 In Model-Based Design, a system model is at the center of the
development process, from requirements development, through
design, implementation, and testing.
 What is meant here by model is a graphical representations of
the system
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43. Model Based Design Rationale
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 Think: can you draw a rectangle with 3 lines
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44. Model Based Design Rationale
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 Executable specification
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45. Model Based Design Rationale
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 Automatic Code
Generation
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46. Model Based Design Rationale
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1. Graphical Representation
2. Executable Specification
3. Automatic Code Generation
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47. Physical Systems
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48. Definition of System
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 From engineering point of view, a system is defined as an
interconnection of many components that act together to
perform a certain objective
 Automobile
 Machine tool
 Robot
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49. Physical Systems Classification
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Physical
System
Static System Dynamic
System
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50. Static System
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 Output of the system depends only on the current input
 The system has no memory
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51. Dynamic System
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 Output of the system depends on the current input as well as
previous inputs/outputs
 The system has internal memory
A dynamic system can be represented mathematically
using differential equations
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52. What is a Real Time System?
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53. Real-Time System
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 A real-time system is a software system where the correct
functioning of the system depends not only on the results
produced by the system but also on the time at which these
results are produced.
 The system has "real-time constraints"
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54. Hard Real-Time System
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 A hard real-time system is a system whose operation is incorrectif
results are not produced according to the timing specification.
 Car engine control system is a hard real-time system
 because a delayed signal may cause engine failure or damage
 Flight Control System
 Airbag crash detection system
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55. Hard Real-Time System
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 Delay = Failure
 Time granularity
 Millisecond
 RequiredAnalysis
 Worst possible scenario
 Need for redundancy
 To meet safety requirements
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56. Hard Real-Time System Example
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 Airbag crash detection system
 Airbag must inflate between 10 and 20 msec from the detection of a crash
 Not too early—since this would make the airbag deflate before it can catch
the passenger
 Nor too late—since the airbag could then injure the passenger by blowing up
in his face and/or catch him too late to prevent his head from banging into the
steering wheel
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57. Soft Real-Time System
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 A soft real-time system is a system whose operation is
degraded if results are not produced according to the specified
timing requirements.
 Non-safety-critical system
 Keypad input
 Message visualization
 System status representation
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