摘要
A robot system based on a linkage structure, which can precisely perceive the working state by utilizing a variety of sensors carried on board. A multi-sensor data fusion strategy to integrate more accurate data based on different working states of the robot, thereby enhancing the robot's capabilities in receiving commands and perceiving the environment. Furthermore, at the control level, a neural network control based on radial basis functions is applied to the robot. This algorithm leverages the approximation properties of neural networks to estimate disturbances and uncertainties in the nonlinear system of the robot more accurately, enabling smoother and faster control. Experimental validation demonstrates that the utilization of neural network control on this robot yields superior control performance compared to traditional PID control, affirming its high operational efficiency.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | 2024 IEEE International Conference on Mechatronics and Automation, ICMA 2024 |
| 出版商 | Institute of Electrical and Electronics Engineers Inc. |
| 页 | 1050-1055 |
| 页数 | 6 |
| ISBN(电子版) | 9798350388060 |
| DOI | |
| 出版状态 | 已出版 - 2024 |
| 活动 | 21st IEEE International Conference on Mechatronics and Automation, ICMA 2024 - Tianjin, 中国 期限: 4 8月 2024 → 7 8月 2024 |
出版系列
| 姓名 | 2024 IEEE International Conference on Mechatronics and Automation, ICMA 2024 |
|---|
会议
| 会议 | 21st IEEE International Conference on Mechatronics and Automation, ICMA 2024 |
|---|---|
| 国家/地区 | 中国 |
| 市 | Tianjin |
| 时期 | 4/08/24 → 7/08/24 |
联合国可持续发展目标
此成果有助于实现下列可持续发展目标:
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