Transition Control of a Double-Inverted Pendulum System Using Sim2Real Reinforcement Learning
This study presents a sim2real reinforcement learning-based controller for transition control in a double-inverted pendulum system, addressing the limitations of traditional control methods that rely on precomputed trajectories and lack adaptability to strong external disturbances. By introducing th...
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| Main Authors: | Taegun Lee, Doyoon Ju, Young Sam Lee |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
|
| Series: | Machines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1702/13/3/186 |
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