| Autor: |
Jian Cao, Yang Zhang, Chuanyu Ju, Xinyi Xue, Jiyuan Zhang |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Aerospace, Vol 10, Iss 6, p 520 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2226-4310 |
| DOI: |
10.3390/aerospace10060520 |
| Popis: |
With the continuous development of the space industry, the demand for low-gravity simulation experiments on the ground for spacecraft is increasing, to overcome the gravity compensation of spacecraft on the ground tests. This paper presents a new low-gravity simulation system based on the suspension method. We used a traditional PID control method with Radial Basis Function (RBF) neural network to solve its constant-tension control problem. The ant colony algorithm was used to find the initial parameters of the neural network in the solution space. A self-adjusting control strategy of PID controller parameters was realized. The results show that the tension control error of the low-gravity simulation system is as small as 0.2%, which fully meets the requirements of the system’s technical indicators. This work provides auspicious theoretical and technical support for developing a low-gravity simulation system. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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