2023
DOI: 10.36227/techrxiv.22032578
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Finite-Set Direct Torque Control via Edge Computing-Assisted Safe Reinforcement Learning for a Permanent Magnet Synchronous Motor

Abstract: <p>Advances in the field of reinforcement learning (RL)-based drive control allow formulation of holistic optimization goals for the data-driven training phase. The resulting controllers feature efficient drive operation without the necessity of an a priori known plant model but, so far, conduction of the corresponding training phase in real-world drive systems has been applied only sparsely due to safety concerns. This contribution targets the challenging problem of self-learning torque control for a pe… Show more

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