Demo Stations

How to Build Custom Motor Controllers for Zynq SoCs with MATLAB and Simulink

Motor control algorithms such as field-oriented controllers increasingly require more performant hardware platforms. Many designers are adopting SoC FPGA devices to integrate processor and FPGA functions on a single device, reducing system power, cost, and board size. The complexity of implementing algorithms on SoCs, however, creates a challenge for algorithm developers and software developers and hardware designers.

This demo shows how to optimize your design process to:

  • Model and simulate motor control systems to evaluate controller designs before testing in hardware
  • Automatically generate HDL and C code to program control algorithms into a Zynq®-7020
  • Use a new MATLAB IP core generation workflow to rapidly create IP cores that implement high-speed I/O processing and offload math-intensive tasks to the FPGA fabric
  • Prototype motor control algorithms using the Avnet® Zynq Intelligent Drives Kit II


  • Simulink®
  • Simscape™
  • Stateflow®
  • Fixed-Point Designer™
  • Embedded Coder™
  • HDL Coder™

Vision Algorithm Design and Hardware Implementation on FPGAs

Vision is increasingly becoming the “eyes” in robotics, ADAS, medical and many industrial applications. Often these vision algorithms have to be implemented on FPGA- or SoC-based platforms because of performance requirements.

This demo shows how to optimize your design process to:

  • Model and simulate pixel-streaming vision algorithms
  • Automatically generate HDL code to program FPGAs
  • Prototype vision algorithms on FPGAs using FPGA-in-the-loop verification techniques


  • Simulink
  • Stateflow
  • Fixed-Point Designer
  • Embedded Coder
  • HDL Coder
  • HDL Verifier™
  • Vision HDL Toolbox™

Data Analytics: A Predictive Maintenance Application

More and more companies are becoming aware of the importance of predictive maintenance of their equipment: the ability to intelligently schedule maintenance based on live machine health condition. The ability to build a data analytics model based on historical machine data that reliably predicts the time-to-failure of your asset is a key ingredient for success.

In this demonstration, learn how to:

  • Use the machine learning methodology to build predictive maintenance models
  • Iterate easily to find the machine learning algorithm best suited to your scenario
  • Import large amounts of historical data into MATLAB without running into out-of-memory issues
  • Allow users to concurrently access your predictive maintenance software by deployment into an enterprise-wide IT infrastructure


  • Statistics and Machine Learning Toolbox™
  • Curve Fitting Toolbox™
  • MATLAB Compiler SDK™
  • MATLAB Production Server™

MATLAB Speaks FLIR: Toward Smart Image Processing and Computer Vision

Thermal sensing is a rapidly growing area of imaging technology. Object detection and tracking are important in many computer vision applications including activity recognition, automotive safety, and surveillance.

This demonstration shows a sensor fusion approach to detect the eyes on a face and measure body temperature system using built-in, ready-to-use functionalities. You’ll see how to:

  • Acquire images into MATLAB
  • Visualize images
  • Perform automatic image registration
  • Perform feature detection using Viola-Jones detector
  • Add temperature (text) annotation on the image


  • Image Acquisition Toolbox™
  • Image Processing Toolbox™
  • Computer Vision Toolbox™

Automatically Generate Code and Tune Parameters for a Flying Drone

This demonstration highlights a complete workflow for Model-Based Design of control systems including design and simulation, real-time testing, and final implementation on an AR Parrot 2.0 Drone. To further enhance the control of the drone, this demonstration illustrates how to access not only the IMU on the drone but also the front and bottom cameras to help with the real-time control.


  • Simulink
  • Stateflow
  • Embedded Coder
  • Computer Vision Toolbox

MathWorks in Education and Academia

MathWorks is deeply rooted in education and research, with more than 5000 universities around the world using our MATLAB and Simulink for engineering and math courses and lab work. MATLAB and Simulink are also frequently used in compelling student assignments and competitions like Robocup and the Solar Challenge. Students and professors like to work with MATLAB as it gives them the opportunity to work on more interesting real-life problems and examples. It also provides a running start for graduates at the many technological companies that are using MATLAB and Simulink as part of their development process.

Learn about the activities MathWorks supports at universities such as:

  • Project-based learning with low-cost hardware
  • MATLAB Online and MATLAB Mobile™
  • MathWorks Academic Online Training Suite

MathWorks Consulting Services

MathWorks creates software for people who are experts in their own field, but not necessarily experts in technical computing or in leveraging software tools to optimize their model-based designs.

MathWorks Consulting Services can help you get the most out of the MATLAB and Simulink by jumpstarting your project or setting up best practices for improved design flows, freeing up your time for solving the problems you care about. Connect with one of our experienced consultants and ask about our most successful engagements.

MathWorks Training Services

Discover how MathWorks training offerings can accelerate your use of MATLAB and Simulink products:

  • Take one (or all) of our tests, and see if you are up-to-date on your MATLAB and Simulink knowledge
  • Get an idea of the diversity of training paths that exist for users with specific job roles or application areas
  • Compare the options for instructor-led training (on your site or in one of our training locations) or the self-paced training offerings
  • Browse the free training material in MATLAB Academy, which allows new users to get up to speed in only a few hours

Technical Support

MATLAB comes with technical support: have you already used it?

Although the documentation of MATLAB and Simulink products is often praised as a great resource for getting started and explaining how things work, it is not always sufficient to solve a problem you may run into. In these cases, Technical Support can help you to “get unstuck” and find out if what you are trying to do can be achieved and possibly provide an example. If, you run into a genuine bug or have some suggestions on how to improve our software, Technical Support help you work around the issue or limitation and report it to our development team. Our staff consists of academic-level engineers with a passion for MATLAB and Simulink: come and meet the people behind the “Request Support” button.