Processor-in-the-Loop Verification of MATLAB Functions

This example uses:

This example shows you how to use the Embedded Coder® Support Package for STMicroelectronics® STM32 Processors for Processor-in-the-Loop (PIL) verification of MATLAB® functions.

The STM32F4-Discovery board used in this example supports two different communication interfaces for PIL, namely ST-LINK and Serial (USART2). The ST-LINK communication interface does not require any additional cables or hardware besides a USB type A to Mini-B cable used to connect the STM32F4-Discovery board to the host computer. The serial communication interface requires a USB TTL-232 cable. Running a PIL simulation using the serial communication interface is much faster than the running a PIL simulation using ST-LINK. We recommend using the serial interface, Serial (USART2) for PIL whenever possible.

For other discovery boards such as STM32F746G-Discovery, STM32F769I-Discovery and STM32L475VG-Discovery supported communication interface is Serial.

In this example, you will learn how to generate a PIL MEX function from a simple MATLAB function. When you run the PIL MEX function, the C-code generated from your MATLAB function runs on the STMicroelectronics STM32F4-Discovery board, an ARM Cortex-M4 based microcontroller. The results are transferred to MATLAB for numerical verification. During this process, you can profile the code execution. The PIL verification process is a crucial part of the design cycle to ensure that the behavior of the deployment code matches the design.

Prerequisites

If you are new to Embedded Coder, visit the Embedded Coder product page for an overview and tutorials.
If you are new to code generation from MATLAB code, we recommend completing the Embedded Coder Capabilities for Code Generation from MATLAB Code.
If you are using ST-Link/V2, install the ST-Link/V2 USB drivers by following the steps described in Install Drivers for STMicroelectronics STM32 Boards. MATLAB Coder™

Required Hardware

STMicroelectronics STM32F4-Discovery board
USB type A to Mini-B cable, for ST-LINK
USB TTL-232 cable - TTL-232R 3.3V, for serial communication

Note: This example was tested using the FTDI Friend USB TTL-232R 3.3V adapter.

Task 1 - Create a New Folder and Copy Relevant Files

In this example, you are going to verify a MATLAB function that adds two inputs and returns output. Create a new folder and copy relevant files which required to verify on emulated ARM Cortex-M3 hardware board using QEMU.

Navigate to new folder and create a function file, simple_addition.m, containing a function that adds two inputs and returns the result.

To see the contents of this function:

type simple_addition

The %#codegen directive in this function indicates that the MATLAB code is intended for code generation.

Task 2 - Generate PIL MEX Function from Command Line

The following steps provide commands to generate code and a library for a MATLAB function to verify on STM32F4-Discovery board.

Step 1: Create a coder.EmbeddedCodeConfig object to generate code and create a library for MATLAB function simple_addition.

config = coder.config('lib','ecoder',true);

Step 2: Configure the object for PIL.

config.VerificationMode = 'PIL';

Step 3: Specify the hardware on which the generated code to be verified.

config.Hardware = coder.hardware('STM32F4-Discovery');

Step 4: Choose the PIL communication interface.

To choose 'ST-LINK' as PIL communication interface, below is the step:

config.Hardware.PILInterface = 'ST-LINK';

To choose 'Serial (USART2)' as PIL communication interface, below are the steps.

config.Hardware.PILInterface = 'Serial (USART2)';
config.Hardware.PILCOMPort = 'COM28';

To set PILCOMPort, follow the steps 2 to 4 specified in Code Verification and Validation with PIL and Monitoring and Tuning to find the COM port for serial communication.

Note: For other discovery boards,

Choose 'Serial' as PIL communication interface.

Set the baud rate for PIL communication as

config.Hardware.PILBaudRate = 115200;

Step 5: Limit the stack size to reasonable size, for example 512 bytes, as default size is much larger than the memory available on the hardware.

config.StackUsageMax = 512;

Step 6: You can enable verbose build to view the build log on command line.

config.Verbose = 1;

Step 7: Generate library code for the simple_addition MATLAB function and the PIL interface.

inp = single(zeros(1,30)); codegen('-config', config, '-args',
{inp,inp}, 'simple_addition');

In above commands, inp declares the data type and size for input arguments to MATLAB function 'simple_addition'. The codegen command generates code into following folders

codegen\lib\simple_addition - Standalone code for simple_addition.
codegen\lib\simple_addition\pil - PIL interface code for simple_addition.

Also, this step creates simple_addition_pil PIL MEX function in the current folder. This allows you to test the MATLAB code and the PIL MEX function and compare the results between both.

Task 3 - Run the PIL MEX Function

Run the PIL MEX function to compare its behavior to that of the original MATLAB function and to check for run-time errors.

u1 = single(rand(1,30)); u2 = single(rand(1,30)); y =
simple_addition_pil(u1,u2);

Terminate PIL execution with the following command.

clear simple_addition_pil;

Task 4 - Verify Generated Code

To verify the numerical accuracy of the generated code, compare MATLAB results with those of the PIL MEX function:

norm(y - simple_addition(u1,u2))

Task 5 - Profile Generated Code

To enable code execution profiling, set CodeExecutionProfiling of the coder.EmbeddedCodeConfig coder configuration object to true before generating code for the MATLAB function in Step 7 of Task 2.

config.CodeExecutionProfiling = true;

When profiling is enabled, the generated code is instrumented with timing information. The profiling results are transferred to MATLAB when the PIL MEX function is cleared from memory.

To accumulate profiling results, run simple_addition function 100 times in a loop:

for k=1:100, y = simple_addition_pil(u1,u2); end

The profiling results are available after clearing the PIL MEX function:

clear simple_addition_pil

Bring up the profiling report:

ProfileResultsWithoutCRL = getCoderExecutionProfile('simple_addition');
report(ProfileResultsWithoutCRL)

Task 6 - Use 'ARM Cortex-M' Code Replacement Library (CRL)

To take advantage of optimized CRL for ARM Cortex-M processors, assign CodeReplacementLibrary library 'ARM Cortex-M (CMSIS)' and re-build the PIL MEX function following Step 7 of Task 2:

config.CodeReplacementLibrary = 'ARM Cortex-M (CMSIS)';

Run the simple_addition function 100 times in a loop to accumulate profiling results:

for k=1:100, y = simple_addition_pil(u1,u2); end

The profiling results are available after clearing the PIL MEX function:

clear simple_addition_pil

Bring up the profiling report:

ProfileResultsWithCRL = getCoderExecutionProfile('simple_addition');
report(ProfileResultsWithCRL)

Compare the profiling results to those obtained in Task 5.

Other Things to Try

Run the example on STM32F746G-Discovery, STM32F769I-Discovery and STM32L475VG-Discovery boards for code verification of MATLAB functions using PIL.