Tutorials and Videos
Learn how to use MATLAB and Simulink for student projects.
Aerospace
Learn how to use MATLAB and Simulink to design airplanes, unmanned aerial vehicles, and other aerospace vehicles for student projects. MathWorks experts and users share information on how to perform engineering design calculations, develop simulation models, and deploy code to hardware targets.
Learn how to identify the most sensitive design variables and modify code for appropriate design choices to maximize student competition scores.
Optimize the design of your model aircraft using MATLAB. Set up an optimization problem and define your objective function and design variables. Use the fixed-wing object to compute stability derivatives and use them as optimization constraints.
Build interactive design tools to reduce development time. Zachary Leitzau from Embry-Riddle Aeronautical University demonstrates the use of a self-built app to help design a model airplane.
Follow Joshua Williams from Cornell University Unmanned Air Systems (CUAir) as he demonstrates the use of a genetic algorithm to optimize airframe sizing for model airplanes.
Simulation is a great way to test and tune control algorithms for quadcopters. Julien Cassette talks about using Simulink, Robotics Operating System (ROS), and Gazebo to simulate quadcopter missions from student competitions.
Claudio Conti of Sapienza Flight Team at Sapienza University of Rome joins Connell D’Souza to talk about using Model-Based Design and real-time simulation to design a custom autopilot.
Code Generation
Learn how to generate readable, standalone C/C++ code from MATLAB functions and Simulink models. Navigate and customize the generated code before deploying directly onto target hardware boards. Use Simulink as an integration environment and generate code for multirate systems.
Overview
Training
Learn how to generate editable, customizable code from MATLAB code using MATLAB Coder.
Learn how to prepare and optimize MATLAB code for code generation.
Learn how to generate editable, customizable code from Simulink models using Simulink Coder.
Learn how to customize the code generated from Simulink models to balance various design considerations.
Learn how Simulink can be used as an integration platform for design, simulation, and code generation of multiple software components.
Learn how to generate and deploy code directly from Simulink models to embedded computing systems.
Hybrid Electric Vehicles
Learn to develop hybrid electric vehicle (HEV) systems using MATLAB and Simulink. Explore motor control design and how to use equivalent circuits for representing the dynamic behavior of battery cells. Explore battery pack electro-thermal modeling and battery thermal management system design. Learn about modeling and simulating HEV systems, creating plant models, developing control systems, and optimizing your models.
Identify core pieces of a field-oriented controller in a Simulink model, and learn how to autotune PI controller gains. Distinguish between dynamic decoupling control and flux weakening control.
Learn how to build a battery pack using Simscape Battery and conduct battery cell characterization using multiple characterization experiments at once.
Identify the challenges associated with HEV design and with architecture selection. Understand energy consumption and performance estimates over different drive cycles and identify the impact of component selection.
Learn about different methods for creating HEV component models. See how Powertrain Blockset and Simscape tools can be used for HEV modeling, and learn best practices for creating new plant models.
Get an overview of HEV control systems and the concept of energy management. Understand control algorithm implementation in Simulink and Stateflow, test your controller, and learn best practices.
Get an introduction to optimization and learn about MATLAB and Simulink optimization tools. Simultaneously optimize control and component parameters. Find a common set of control parameters for various driving conditions.
Learn about battery management system tasks. See how Simulink can model a physical plant and the controller for a battery pack. Identify how a nonlinear observer block from the controls library can keep track of the state of charge of a cell.
Explore the components of a battery thermal management system for a small four-passenger EV. Examine a Simscape model for this system, and use the model to diagnose and correct a problem with the control algorithm and investigate energy usage.
Making Vehicles and Robots See
Get started with fundamental computer vision techniques that enable your vehicles and robots to see the environment. Watching these tutorials, learn practical approaches to working with perception algorithms to design your autonomous systems.
Learn how to work with images in MATLAB.
Learn how to perform color-based segmentation, refine image masks, and analyze regions using interactive apps.
Learn how to perform object tracking in a video using the feature matching and the point tracker techniques.
Learn what a point cloud is and the basics of point-cloud processing, including preprocessing and segmentation.
Learn how to work with large amounts of image data and create neural networks to classify images.
MATLAB and Simulink Racing Lounge
The MATLAB and Simulink Racing Lounge features a video series covering topics relevant to automotive student teams. Everything from the basics of MATLAB and Simulink to in-depth details on improving your racecar development is explored. Automotive student teams also share their keys to success with examples.
MATLAB and Simulink Robotics Arena
Learn how to use MATLAB and Simulink to design algorithms, create simulations, and speed up development for student projects in robotics and unmanned systems.
Mobile Robotics
Learn how to design and simulate common mobile robotics algorithms in MATLAB and Simulink, such as open- and closed-loop feedback control systems, for your robot to perform tasks such as dead reckoning, line following, and obstacle detection. Use custom simulation tools to test algorithms within Simulink before deploying them to an actual robot.
Overview
Training
Learn how to control a robot to move on its wheels autonomously using dead reckoning.
Learn how to design and tune a PID controller to perform navigation tasks like dead reckoning.
Learn how to design line following algorithms for a mobile robot.
Learn how to design obstacle detection algorithms for a mobile robot.
Learn how to design a supervisory logic that navigates a robot through a predefined path.
Simscape Essentials for Automotive Student Teams
Get started with the fundamentals of vehicle development for student competitions like Formula Student using Simscape. Create a basic vehicle model with brakes and simulate its behavior on a slope. Dive into electric powertrain modeling with a simplified battery model. Develop a motor cooling model for automotive student competitions.
In this video, we guide students to create a simple model with Simscape where a free-falling vehicle applies brakes to stop while descending a slope.
This video shows students how they can start modeling electric powertrains in Simscape, including a battery, motor, and differential.
The video introduces students to the process of building motor cooling systems with Simscape for automotive student competitions, such as Formula Student.
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YouTube Series
Dozens of videos provide walk-throughs on tackling interesting projects and using new features. Topics range from Monte Carlo analysis to speeding up MATLAB code.
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