Reinforcement Learning-Based PID Gain Optimization for Delta Parallel Robot Trajectory Tracking
In this study, a PID gain tuning approach using Deep Deterministic Policy Gradient (DDPG), a reinforcement learning (RL) algorithm, is proposed for trajectory tracking of delta parallel robots. Owing to their 3-degree-of-freedom (3-DOF) parallel kinematic structure, delta robots offer higher stiffne...
保存先:
| 主要な著者: | , |
|---|---|
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
MDPI AG
2026-01-01
|
| シリーズ: | Applied Sciences |
| 主題: | |
| オンライン･アクセス: | https://www.mdpi.com/2076-3417/16/3/1453 |
| タグ: |
タグなし, このレコードへの初めてのタグを付けませんか!
|