Real-Time Testing – Deploying a Reinforcement Learning Agent for Field-Oriented Control - MATLAB
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    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.

    Published: 6 Dec 2021

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