Parameters for TD3 approach [60].

<div><p>Enhancing the performance of 5ph-IPMSM control plays a crucial role in advancing various innovative applications such as electric vehicles. This paper proposes a new reinforcement learning (RL) control algorithm based twin-delayed deep deterministic policy gradient (TD3) algorith...

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محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Ahmed M. Hassan (8893106) (author)
مؤلفون آخرون:	Jafar Ababneh (20501230) (author), Hani Attar (20501233) (author), Tamer Shamseldin (20501236) (author), Ahmed Abdelbaset (20501239) (author), Mohamed Eladly Metwally (17811093) (author)
منشور في:	2025
الموضوعات:	Cell Biology Genetics Pharmacology Biotechnology Mathematical Sciences not elsewhere classified xlink "> enhancing relatively low values new reinforcement learning constant torque region constant power region reinforcement learning algorithm improving speed response obtained using four maximum overshoot percentage ipmsm control plays speed response overshoot percentage maximum time control methodology transit search settling time rise time paper proposes optimization techniques mpc ). max time main purpose four mhot electric vehicles dm ), crucial role
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Parameters for TD3 approach [60].

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