| Identification of fast-steering mirror based on chicken swarm optimization algorithm | |
| Ren, Wei1,2; Deng, Chao1,2; Zhang, Chao3; Mao, Yao1,2 | |
| Source Publication | 1755-1307 |
| Volume | 69 |
| Issue | 1 |
| Pages | 012086 |
| 2017 | |
| Language | 英语 |
| Indexed By | Ei |
| Abstract | According to the transfer function identification method of fast steering mirror exists problems which estimate the initial value is complicated in the process of using, put forward using chicken swarm algorithm to simplify the identification operation, reducing the workload of identification. chicken swarm algorithm is a meta heuristic intelligent population algorithm, which shows global convergence is efficient in the identification experiment, and the convergence speed is fast. The convergence precision is also high. Especially there are many parameters are needed to identificate in the transfer function without considering the parameters estimation problem. Therefore, compared with the traditional identification methods, the proposed approach is more convenient, and greatly achieves the intelligent design of fast steering mirror control system in enginerring application, shorten time of controller designed. © Published under licence by IOP Publishing Ltd. |
| Keyword | Animals - Mirrors - Transfer functions |
| Conference Name | IOP Conference Series: 3rd International Conference on Advances in Energy, Environment and Chemical Engineering |
| EI Classification Number | 2017-2145 |
| Document Type | 会议论文 |
| Identifier | http://ir.ioe.ac.cn/handle/181551/9013 |
| Collection | 光电工程总体研究室（一室） |
| Affiliation | 1.Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu; 610209, China; 2.Key Laboratory of Beam Control, Chinese Academy of Science, Chengdu; 610209, China; 3.University of Academy of Sciences, Beijing; 100039, China |
| Recommended Citation GB/T 7714 | Ren, Wei,Deng, Chao,Zhang, Chao,et al. Identification of fast-steering mirror based on chicken swarm optimization algorithm[C],2017:012086. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| 2017-2145.pdf（769KB） | 会议论文 | 开放获取 | CC BY-NC-SA | Application Full Text | ||
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