Real-Time Testing – Deploying a Reinforcement Learning Agent for Field-Oriented Control
Deploy a trained reinforcement learning policy to a Speedgoat system for real-time testing. Use the capabilities for implementing deep learning inference in Simulink® and plain C code generation for deep learning networks to deploy a trained reinforcement learning agent.
In this demo, a pretrained reinforcement learning agent for field-oriented control of a permanent magnet synchronous motor (PMSM) is used to showcase this workflow. Refer to "reinforcement learning for field-oriented control of a permanent magnet synchronous motor" to learn how to set up and train an agent for this application.
You can also select a web site from the following list:
How to Get Best Site Performance
Select the China site (in Chinese or English) for best site performance. Other MathWorks country sites are not optimized for visits from your location.