Tracking control Scheme for photoelectric tracking platform with predictor-structure ESO | |
Wang, Fan; Wang, Ranjun; Xie, Meilin; Liu, Peng; Jing, Feng; Liu, Bo | |
2021 | |
会议日期 | 2021-07-09 |
会议地点 | Virtual, Chongqing, China |
关键词 | photoelectric tracking platform (PTP) active disturbance rejection control (ADRC) input-delay system predictor-structure extended state observer (PESO) |
DOI | 10.1109/MLISE54096.2021.00028 |
页码 | 117-125 |
英文摘要 | In this paper, a high-precision control scheme based on active disturbance rejection control (ADRC) with predictor-structure extended state observer (PESO) is developed to improve the tracking accuracy of a photoelectric tracking platform (PTP). ADRC controller is designed to estimation and compensation total disturbances which include both the external disturbances and the internal uncertain dynamics. The tracking loop of PTP is considered as an input-delay system through the designed composite control structure, then a PESO is proposed to obtain more accurate states and total disturbance. At the same time, the convergence of PESO is analyzed, and some simulations illustrate the effectiveness of PESO. Finally, the presented controller is realized on embedded microcontroller, and the contrast experiments are carried out. Experimental results show that the presented controller has excellent capability in error rejection, by which the effect of delay is effectively weakened, and the tracking accuracy of PTP is significantly improved. © 2021 IEEE. |
产权排序 | 1 |
会议录 | Proceedings - 2021 International Conference on Machine Learning and Intelligent Systems Engineering, MLISE 2021 |
会议录出版者 | Institute of Electrical and Electronics Engineers Inc. |
语种 | 英语 |
ISBN号 | 9781665417365 |
内容类型 | 会议论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/95686] |
专题 | 西安光学精密机械研究所_光电测量技术实验室 |
作者单位 | Xi'an Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Xi'an; 710119, China |
推荐引用方式 GB/T 7714 | Wang, Fan,Wang, Ranjun,Xie, Meilin,et al. Tracking control Scheme for photoelectric tracking platform with predictor-structure ESO[C]. 见:. Virtual, Chongqing, China. 2021-07-09. |
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