Adaptive Control for Industrial Welding Robot with Muti-degree of Freedom Using the Improved Neural Network PID
文献类型：会议论文
| 作者 | Wang, Rui1; Jiang, Li1; Lin, Yuanchang2; Peng, Jinshan1; Xu, Xinping1 |
| 出版日期 | 2018 |
| 会议日期 | May 25, 2018 - May 27, 2018 |
| 会议地点 | Xi'an, China |
| DOI | 10.1109/IMCEC.2018.8469345 |
| 页码 | 40-44 |
| 英文摘要 | A24 at the problem that the traditional control algorithm is not effective to track control of industrial robot in multi-degree of freedom (multi-DOF), a improved adaptive control method based on neural network PID was proposed. On the basis of the backward error propagation of BP algorithm, the method adjusted the BP network weight and thresholds corresponding to PSGA(Predator Search Genetic Algorithm). The PSGA is taken to choose the initial weights and threshold of network, which will improve the speed and precision of network training. The simulation results show that method overcomes the difficulty of traditional PID control by optimizing the dynamic process and reducing the steady-state error of the system. © 2018 IEEE. |
| 会议录 | 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018
 |
| 语种 | 英语 |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/7949]  |
| 专题 | 中国科学院重庆绿色智能技术研究院 |
| 作者单位 | 1.Chongqing Academy of Metrology and Quality Inspection, China; 2.Chongqing Institute of Green Intelligent Technology, Chinese Academy of Sciences Chongqing, China |
| 推荐引用方式 GB/T 7714 | Wang, Rui,Jiang, Li,Lin, Yuanchang,et al. Adaptive Control for Industrial Welding Robot with Muti-degree of Freedom Using the Improved Neural Network PID[C]. 见:. Xi'an, China. May 25, 2018 - May 27, 2018. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。