Run on Target Hardware

Run model on target hardware

Topics

Run Model on Arduino Hardware

Run a Simulink^® model on Arduino^® hardware.

Stop or Restart a Model on the Arduino Hardware

The Arduino hardware runs the application created from your model in the flash memory.

Tune and Monitor Model Running on Hardware

Use your host computer to monitor and control an application running on the target hardware.

Signal Monitoring and Parameter Tuning

Overview of the operation of external with attached hardware boards.

Signal Monitoring and Parameter Tuning Using Third-Party Product like CANape

Use XCP-based External mode simulation over serial for calibrating parameters in third-party product like CANape^®.

Deploy Arduino Functions to Arduino Hardware Using MATLAB Function Block

Code generation of MATLAB Arduino IO functions inside a MATLAB Function block.

Additional Capabilities with Simulink Coder and Embedded Coder

Include additional capabilities for code generation.

Examples and How To

Create and Deploy Interactive Dashboard on Arduino

This example shows how to use the Simulink® Support Package for Arduino® Hardware to create and deploy an interactive dashboard panel using the Push Button, Circular Gauge, and Display blocks on your Arduino hardware.

Featured Examples

Communicating with Arduino Hardware

Tune the parameters and monitor the signals of an algorithm running on Arduino® board.

Open Example

Code Verification and Validation with PIL

Use Simulink Support Package for Arduino Hardware for code verification and validation using PIL.

Open Example

Communicating with Arduino Hardware Using XCP-Based Simulation

Tune the parameters and monitor the signals of an algorithm running on the Arduino® Mega 2560 board using XCP-based simulation.

Open Example

Heart Rate Sensor Using Arduino

How MATLAB® Function is used in Simulink® models to read the analog voltage from a heart rate sensor. The MATLAB function reads the analog voltage from a REES52 Heart Rate sensor connected to 'A0' pin on the Arduino® Uno board. Arduino Uno board can read voltage between 0 to 5V and returns a number in the range of 0-1023. The MATLAB Function block in the model returns this number. If you hold the sensor, the reading changes. Heart rate can be calculated based on the change in this reading.

Open Script

Pitch and Roll Calculation on Arduino Using IMU Sensor

Read the acceleration and angular velocity data from IMU sensor mounted on Arduino® hardware and calculate the pitch and roll angles.

Open Example

Calibrate ECU Parameters in CANape Using XCP-based Serial Interface

Monitor signals and tune parameters of a Simulink model on Arduino™ Mega 2560 board using CANape® software. CANape is primarily used in optimizing parameterization (calibration) of electronic control units (ECU). By using CANape, you can calibrate parameter values and acquire measurement signals during system run time.

Open Example

Code Execution Profiling for Arduino Hardware in External Mode

Use the Simulink® Support Package for Arduino® Hardware to profile the real-time execution of generated code running as an executable on ARM® architecture-based Arduino hardware boards with XCP communication interface in External mode.

Open Example

Identify Punch and Flex Hand Gestures Using Machine Learning Algorithm on Arduino Hardware

Use the Simulink® Support Package for Arduino® Hardware to identify punch and flex hand gestures using a machine learning algorithm. The example is deployed on an Arduino Nano 33 IoT hardware board that uses an onboard LSM6DS3 6DOF IMU sensor to identify the hand gestures. The output from the machine learning algorithm, after identifying whether a hand gesture is a punch or a flex, is transmitted to the serial port where 0 represents a punch and 1 represents a flex.

Open Example

Identify Shapes Using Machine Learning Algorithm on Arduino

Use the Simulink® Support Package for Arduino® Hardware to identify shapes such as triangles and circles using a machine learning algorithm. The example is deployed on an Arduino Nano 33 IoT hardware board that uses an onboard LSM6DS3 IMU Sensor to identify shapes. The output from the machine learning algorithm, after identifying shapes, is transmitted to the serial port to publish the output in the MATLAB® Command Window.

Open Example