The document discusses model-based design for developing motor control applications. It describes modeling motor control systems using Simulink, simulating the models to analyze system behavior, and automatically generating C code to run on an embedded platform. Key aspects covered include modeling the motor, electronics, interfaces and control algorithm, generating generic C code, and interfacing this code to the embedded target using device drivers. The approach allows debugging the application through offline simulation and testing on the embedded hardware in real-time.

1. The World Leader in High Performance Signal Processing Solutions
Model-Based Design For
Motor Control Development
Paul Crook – Analog Devices

2. Topics
 Developing
motor control applications using modelbased design and automatic code generation
Hardware platform
 Model-Based Design overview
 Modeling of motor control systems
 Simulation and automatic code generation
 Running generic C-code on embedded platform
 When to use MBD and when to use “traditional” design
methods

2

3. ADI Demo Platforms
Motor Drive hardware
 3 phase PM motor
 PC with MATLAB®, Simulink®, and IAR Embedded Workbench

3

4. HW Platform
100V-250V AC input with PFC, 5A
 Isolated current, position, voltage and diagnostic feedback
 3-phase, 0.55kW, permanent magnet synchronous motor

4

5. ADSP-CM40x  Embedded Target
 Key
Points
ARM CORTEX M4F
 240MHz
 Two 16-bit ADCs
 380ns conversion
time
 SINC filter
 384kB SRAM
 2MB Flash
 20 DMA channels
 Peripherals for
motor control
 Communication
interfaces

5

6. MODEL-BASED DESIGN
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7. Why Model-Based Design?
•
•
•
•
7
Requirements Development
System Simulation
Automatic Code Generation
Continuous Verification

8. The Traditional Design Process
Requirements Phase
Design Phase
Realization Phase
Testing Phase
8

9. Traditional Design of a Multi-Domain System
Research & Requirements
Hardware
Software
Mechanical
Requirements
Requirements
Requirements
Design
Design
Design
Realization
Realization
Realization
Testing
Testing
Testing
Integration, Test & Certification
9

10. The Cost of a Traditional Design Process
Source: ROI for IV&V, NASA
10

11. Model-Based Design
RESEARCH
• Model multi-domain systems
REQUIREMENTS
• Explore and optimize system
behavior in floating point and fixed
point
DESIGN
Environment Models
Algorithms
IMPLEMENTATION
TEST & VERIFICATION
Physical Components
• Collaborate across teams and
continents
• Generate efficient code
• Explore and optimize
implementation tradeoffs
C, C++
ARM
• Automate regression testing
• Detect design errors
• Parameter tuning
INTEGRATION
11
• Support certification and standards

12. Model-Based Design for Embedded System
Development
Executable models
- Unambiguous
-“One Truth”
Executable
Specifications
Simulation
- Reduces “real” prototypes
- Iterative “what-if” analysis
Design
with
Simulation
Models
Continuous
Test and
Verification
Automatic
Code Generation
Automatic code generation
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- Minimizes coding errors
Test with Design
- Detects errors earlier

13. Steps in MBD approach
1. Plant modeling
- Motor, load, power electronics etc.
2. Interface modeling
- Sensors, device drivers
3. Controller modeling
- Field oriented control of 3 phase PM motor
4. Analysis and synthesis
- The models created in step 1-3 are used to identify dynamic
characteristics of the plant model.
- Tuning and configuration of system
5. Validation and test
- Offline simulation and/or real-time simulation
- Time response of the dynamic system is investigated
6. Deployment to embedded target
- Automatic code generation
- Test and verification
13

14. Steps in MBD approach
System Model
Test
Signals
Controller
Model
Motor/inverter
Model
Verify
PC
Code
Generation
System
Embedded Controller
Motor/inverter
Target
HW
Motor Drive System
 Simulation
of Controller and Plant model
 Off-line development of algorithms without access to HW
 Code generation and deployment to embedded controller
 Comparison between simulation and actual implementation
14

15. Model complexity
 What
is a good model?
 Represent
the states of interest
 Supports automatic code generation
 Execute fast
 Use existing (trusted) libraries
 Reusable across platforms
Right balance
Too little
5
15
?
Too much

16. Model complexity
 Understanding
strengths and weaknesses of tools is critical
when defining model scope
Strength
Weakness
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- Solving differential equation
- Time domain modeling
- Visualization
- Target specific setup
- Managing system resources
- Time scheduling
- Register setup and control
- Managing System resources
- Time scheduling
- Real time control systems
- Debugging and test
- Visualization

17. Interfacing to Embedded Target
 SW
architecture
C-code needs to be tied to embedded platform
 Utilizing strength of multiple environments
 Graphical environment for application code development
 “Classic” C-code for target specific control
Platform
independent
 Generic
Control Algorithm
Platform
dependent
HW interface layer
Embedded Platform
17

18. Interfacing Embedded Target
 Two
platforms – one implementation
 Common
control algorithm for Simulation and Embedded system
 Platform specific device drivers or behavioral models
 Debug algorithm using simulation and test on embedded platform
18

19. Drive system feedback and control
Feedback
19

20. Motor Control Application Program
Power Inverter and Motor
Device Driver
Auto
code
MC Algorithm
MC Application
Firmware
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MC „C‟ code
CC & Link Device drivers
Application code
Sensors, interfaces and
Device Drivers

21. AC Motor Algorithm (Field Oriented Control)





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Shaft position sensor measures rotor magnet (flux) position – velocity is calculated.
Two/three motor currents measured (two is enough).
Clarke-Park transfer calculate Torque (Iq) and Flux (Id) components of current.
Speed loop generates Iq reference; Id reference set to zero for PMSM.
Current loops and Field alignment generates a,b,c voltage commands.

22. Field oriented control
22

23. Simulation
Simulink scopes
Code debugging
Data analysis in MATLAB
Magnitude [dB]
0
-50
-100
-150
-200
-250
0
1000
2000
3000
Frequency [kHz]
4000
5000
0
1000
2000
3000
Frequency [kHz]
4000
5000
Phase [Degrees]
0
-1000
-2000
-3000
23

24. Generating C-code
24

25. Building and Linking – IAR EWB
25

26. Building and Linking
ARM Library
Motor Control
- M3/M4 support
- FOC functions
Matlab/Simulink
Legacy code
Device Drivers
- Existing code
- Functional model
C-code
Device drivers
System resources
- SW enablement
package
- Allocation & setup
C-code
Workbench
Application code
- State machines
Scheduling
Executable
CM40x
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C-code
- IRQs/RTOS

27. Running target
 MATLAB
GUI + embedded engine
 Streaming data back to MATLAB
Captured runtime data
Duty-cycle
1000
500
0
-500
-1000
Phase current
4
0
20
40
60
80
100
120
140
160
180
200
0
20
40
60
80
100
120
140
160
180
200
0
20
40
60
80
100
120
Sample number
140
160
180
200
x 10
4
3.5
3
2.5
Rotor angle
8
6
4
2
0
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28. Sampling domains
10 kHz
1 kHz
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29. Summary
 Model-Based
Design
 System modeling and simulation
 Automatic code generation
 Modeling of motor control systems
 Electronics/mechanical
 Interfaces
 Control algorithm
 Interfacing
generic C-code to embedded target
 Use
of different environments
 Device drivers
 Debugging
 Off-line
 In
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real-time
and test

30. Questions
30