摘要
This paper proposed an optimal control scheme based on the actor-critic neural network(NN) for the complex mechanical manipulator system with dynamic disturbance. The actor's goal is to optimize control behavior, while the critic's goal is to evaluate control performance. The optimal control update law in the scheme can guarantee the system error and the weight estimation error SGUUB, and its stability and convergence are proved based on the direct Lyapunov method. Finally, the connecting rods on two degrees of freedom are tested to verify the effectiveness of the proposed optimal control scheme.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | Proceedings of the 40th Chinese Control Conference, CCC 2021 |
| 编辑 | Chen Peng, Jian Sun |
| 出版商 | IEEE Computer Society |
| 页 | 1556-1561 |
| 页数 | 6 |
| ISBN（电子版） | 9789881563804 |
| DOI | |
| 出版状态 | 已出版 - 26 7月 2021 |
| 活动 | 40th Chinese Control Conference, CCC 2021 - Shanghai, 中国 期限: 26 7月 2021 → 28 7月 2021 |
出版系列
| 姓名 | Chinese Control Conference, CCC |
|---|---|
| 卷 | 2021-July |
| ISSN（印刷版） | 1934-1768 |
| ISSN（电子版） | 2161-2927 |
会议
| 会议 | 40th Chinese Control Conference, CCC 2021 |
|---|---|
| 国家/地区 | 中国 |
| 市 | Shanghai |
| 时期 | 26/07/21 → 28/07/21 |
指纹
探究 'Optimal Tracking Control for Robotic Manipulator using Actor-Critic Network' 的科研主题。它们共同构成独一无二的指纹。引用此
Hu, Y., Cui, L., & Chai, S. (2021). Optimal Tracking Control for Robotic Manipulator using Actor-Critic Network. 在 C. Peng, & J. Sun (编辑), Proceedings of the 40th Chinese Control Conference, CCC 2021 (页码 1556-1561). (Chinese Control Conference, CCC; 卷 2021-July). IEEE Computer Society. https://doi.org/10.23919/CCC52363.2021.9549419