SimulinkRunner

SimulinkRunner is an automation tool designed to streamline the process of running and managing Simulink models. This provides a simple API to simulate the model multiple times for further recording and testing, helpful for control system design and analysis.

Prerequisite

To enable this library, the Matlab engine for Python should be manually installed on your PC, according to your MATLAB version, a simple installation tutorial can be found here.

Installation

The package can be installed via pip

pip install simulinkRunner

And it can also be installed from source code:

git clone git@github.com:PACRian/SimulinkRunner.git
cd simulinkRunner
pip install -e .

Quickstart

Firstly, import related utiltis from simulinkRunner and initialize the matlab.engine object

import matlab.engine
from simulinkRunner import Model, Runner, OutputPortProcessor, HDF5Recorder

eng = matlab.engine.start_matlab()

Two main classes should be utilized, one is Model used to initialize a Simulink model reference object:

model = Model(eng, MODEL_NAME)

Then you need to introduce a Runner instance to construct the simulation framework, for parameter management, data processing, recording, etc.

runner = Runner(model, 
        model_path=MODEL_PATH,
        model_args=MODEL_MULTI_ARGS,
        sim_args=SIM_ARGS,
        rec_path=HDF5_PATH,
        rec_cls=HDF5Recorder,
        proc_cls=OutputPortProcessor)

Call runner to perform the simulation, and close the content by calling close():

runner()
runner.close()

Check the simple demo run_batch_test.py along with a simple Simulink model test.slx(located in tests/simulink_model), execute the script to run the Simulink model multi-batch.

python .\run_batch_test.py

Command line tool

A simple script run_model.py provides CLI tools for running Simulink models. The syntax is as follows:

python run_model.py [-h] [-p PATH] [-s SIMULATION_ARGS [SIMULATION_ARGS ...]] [-m MODEL_ARGS [MODEL_ARGS ...]] [-a MODEL_ARGS_FILE] [-o OUTPUT] [-c CONFIG] [-l LOG] [-v] [-e] model

Options

• -p, --path: Specify the model path.
• -s: Provide simulation arguments.
• -m: Provide multiple model parameters.
• -a: Specify a file containing model arguments.
• -o: Specify the output path.
• -c: Provide a configuration file.
• -l: Specify a log file.
• -v: Enable verbose mode.
• -e: Enable error logging.

Example Usage

To run the test.slx model with a discrete step of 0.001:

python run_model.py test -p tests/simulink_model -s FixedStep=.001

To run it with multiple batches configured by arguments stated after the -m flag:

python run_model.py test -p tests/simulink_model -m DUnit/DelayLength=2 oGain/Gain=2 1 dGain/Gain=2 3 4 -s FixedStep=.001 -v