Reinforcement learning transition control of a double inverted pendulum скачать в хорошем качестве

Reinforcement learning transition control of a double inverted pendulum

This video shows the experimental results of the transition control of a double inverted pendulum. The control law was developed using a Sim-to-Real reinforcement learning approach. It demonstrates exceptional recovery performance, a feature lacking in classical transition control methods. Control was implemented using LW-RCP02 (Light-weight Rapid Control Prototyping 02), which was developed by Embedded Control Lab, and Simulink. The sampling time is 1 ms. The double inverted pendulum and LW-RCP02 can be purchased from Sungjin Techwin. For purchase inquiries, please contact sales@switch-vr.com. Academic paper : Taegun Lee, Doyoon Ju, and Young Sam Lee, Transition control of a double inverted pendulum system using Sim2Real reinforcement learning, Machines, vol. 13, no. 3, 2025. https://doi.org/10.3390/machines13030186 이 영상은 2단 도립진자의 천이제어(transition control)에 대한 실험결과를 보여준다. 제어법칙은 Sim-to-real 방식의 강화학습을 이용하여 개발되었다. 영상에서 볼 수 있듯이 매우 뛰어난 recovery 성능을 가지고 있는데 이에 비해 전통적인 천이제어 기법들은 recovery 성능을 가지고 있지 못하다. 제어기는 Embedded Control Lab에서 개발한 LW-RCP02 (Light-weight Rapid Control Prototyping 02)와 Simulink를 이용하여 구현하였다. Sampling time은 1 ms이다. 2단도립진자와 LW-RCP02는 성진테크윈으로부터 구입할 수 있습니다. 구매문의는 sales@switch-vr.com로 해주세요.