Adaptable Field-Oriented Control

This high-performance electric drives app brings the right level of integration and density to achieve hard real-time performance into mission-critical motor control applications. By offloading CPU tasks for independent space vector modulation, analog acquisition, and other related motor I/O tasks, this implementation of a rich Field-Oriented Control (FOC) and Sliding Mode SFOC algorithm in HDL offers an extremely versatile platform for learning and designing.



  • Drive implements a rich FOC and sliding mode SFOC algorithm in HDL with powerful networking and hardware-in-the-loop capabilities
  • RPFM low EMI power modulation technique that makes it easier for drives to comply with IEC 61800 and CISPR 11 electromagnetic compatibility standards
  • Platform supports MATLAB®, NI-LabStudio, Scilab, .NET, and C++ remote hardware-in-the-loop environments
  • HDL implementation allows over-the-air updates of any function and upgradable system capabilities

Hardware Needed:

Additional Tools and Resources
Frequently Asked Questions

No, the app does not require any experience in FPGA design.

MakarenaLabs can support all AMD FPGA-based platforms with standard solutions. Solutions are also available for other platforms. For more detailed platform support information, please contact MakarenaLabs using the “Contact Vendor" button above.

MakarenaLabs solutions are motor agnostic in that they integrate with most brushless DC motors on the market. If you are developing a new motor control application or need assistance with an existing motor, please contact MakarenaLabs using the “Contact Vendor" button above.

While the K24 SOM can support multiple motors and the application infrastructure can support multiple motors, the KD240 carrier is limited to only a single motor control drive stage. For help with your carrier customization, please contact MakarenaLabs using the “Contact Vendor" button above.

The sizing and resources required for motor control will vary with application and motor control requirements. MakarenaLabs can optimize the IP to fit your required solution and implementation.

Featured Documents
Adaptive Computing in Electric Drives
Powering Electric Drive Control & Sustainability with Adaptive Computing

Kria™ adaptive System-on-Module (SOM) devices from AMD play an important role in electric drive control. They can optimize performance, help a motor run more efficiently, reduce power consumption, mitigate noise, cut vibration, and detect potential failures before they happen. Download our new motor control eBook to learn more!

Accelerate Your AI-Enabled Edge Solution with Adaptive Computing
Accelerate Your AI-Enabled Edge Solution with Adaptive Computing

Learn all about adaptive SOMs, including examples of why and how they can be deployed in next-generation edge applications, and how smart vision providers benefit from the performance, flexibility, and rapid development that can only be achieved by an adaptive SOM.

Adaptive Computing in Robotics
Adaptive Computing in Robotics

Demand for robotics is accelerating rapidly. Building a robot that is designed to be safe and secure and can operate alongside humans is difficult enough. But getting these technologies working together can be even more challenging. Complicating matters is the addition of machine learning and artificial intelligence, which is making it more difficult to keep up with computational demands.

Roboticists are turning toward adaptive computing platforms, which offer lower latency and deterministic, multi-axis control with built-in safety and security features on an integrated, adaptable platform that is expandable for the future. Read the eBook to learn more.