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타깃 하드웨어에서 실행

타깃 하드웨어에서 모델 실행

도움말 항목

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
This example shows how to program a MATLAB Function block to access multiple peripherals on the Arduino® hardware.
Additional Capabilities with Simulink Coder and Embedded Coder
Include additional capabilities for code generation.
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.
Publish and Subscribe to Messages on ThingSpeak Using MQTT Blocks on Arduino
This example shows how to use the WiFi MQTT Publish and WiFi MQTT Subscribe blocks from the Simulink® Support Package for Arduino® Hardware to publish to and receive messages from MQTT broker to Arduino board.
Get Started with Arduino SAMD Event System Using PWM and ADC Peripherals
This example shows how to use the event system with Arduino Advanced PWM, Analog Input, and Hardware Interrupt blocks.
Generate Interrupts Using Arduino SAMD PWM Block
This example shows how to use the Hardware Interrupt block to create an interrupt service routine (ISR) to react to the PWM events on your Arduino® hardware.

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Communicating with Arduino Hardware

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

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Code Verification and Validation with PIL on Arduino Hardware

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

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Communicate with Arduino Hardware Using XCP-Based Simulation

Use the Simulink® Support Package for Arduino® Hardware to tune the parameters and monitor the signals of an algorithm running on the Arduino Mega 2560 board using XCP-based simulation.

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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.

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Calculate Pitch and Roll 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.

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Calibrate ECU Parameters in CANape Using XCP-Based Serial Interface on Arduino Hardware

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.

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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.

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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.

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Identify Shapes Using Machine Learning on Arduino Hardware

Use the Simulink® Support Package for Arduino® Hardware to identify shapes such as a triangle and circle using a machine learning algorithm. The model in this example is deployed on an Arduino Nano 33 IoT hardware board with an onboard LSM6DS3 IMU Sensor.

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Signal Logging and Parameter Tuning in XCP External Mode with Packed Mode on Arduino

Perform parameter tuning and data logging with a Simulink® model enabled with Packed Mode running on an Arduino® board.

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Develop Multi-Sensor Dashboard Using Arduino

Measure equivalent carbon dioxide (eCO2) concentration levels and equivalent total volatile organic compound (eTVOC) concentration levels using the CCS811 Air Quality Sensor block from the Simulink® Support Package for Arduino® Hardware. The model notifies you when the eCO2 and eTVOC levels cross the acceptable thresholds through an alarm lamp on the dashboard. You can publish the eCO2 and eTVOC concentration levels on a ThingSpeak™ channel. You can also display the sensor data on an Android™ application using dashboard display. In the latter case, the Arduino hardware board acts as a host that sends the sensor data while the Android device acts as a client that accepts this data over the TCP/IP network and displays the data on the application dashboard.

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