基于改进Kinky Inference的输出调节自适应无拖曳控制

孙笑云; 沈强; 吴树范

doi:10.13700/j.bh.1001-5965.2022.0504

基于改进Kinky Inference的输出调节自适应无拖曳控制

doi: 10.13700/j.bh.1001-5965.2022.0504

孙笑云^{1, 2},
沈强^{1, 2, ,},
吴树范^{1, 2}

1.
上海市引力波探测前沿科学研究基地，上海 200240
2.
上海交通大学航空航天学院，上海 200240

基金项目: 科技部重点研发计划“引力波探测”重点专项课题(2020YFC2200800)；国家自然科学基金(62103275)；上海市自然科学基金面上项目(20ZR1427000)

详细信息

通讯作者:
E-mail：qiangshen@sjtu.edu.cn

中图分类号: V448.22.3
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- 被引次数: 0
出版历程
- 收稿日期: 2022-06-20
- 录用日期: 2022-07-22
- 网络出版日期: 2023-01-04
- 整期出版日期: 2024-05-29

Output regulation adaptive drag-free control with enhanced Kinky Inference

SUN Xiaoyun^{1, 2},
SHEN Qiang^{1, 2
, ,},
WU Shufan^{1, 2}

1.
Shanghai Frontiers Science Center of Gravitational Wave Detection，Shanghai 200240，China
2.
School of Aeronautics and Astronautics，Shanghai Jiao Tong University，Shanghai 200240，China

Funds: The key special topic of the Ministry of Science and Technology’s major research and development plan “Gravitational Wave Detection” (2020YFC2200800); National Natural Science Foundation of China (62103275); General Project of Shanghai Natural Science Foundation (20ZR1427000)

More Information

Corresponding author: E-mail：qiangshen@sjtu.edu.cn

摘要

摘要:
在空间引力波探测任务中，航天器内部检验质量因存在载荷硬件噪声、环境噪声及微推力器耦合噪声等复杂干扰，影响其无拖曳控制精度，难以实现超净、超稳控制需求。提出一种基于惰性适配Lipschitz常数Kinky Inference (LACKI)的航天器自适应无拖曳控制方法，运用监督学习规则实现先验知识不足、样本数据存在损坏时外界干扰的逼近和抑制，及基于输出调节的模型参考自适应控制（MRAC）方法实现检验质量精确的无拖曳控制。数值仿真验证了无拖曳控制中敏感轴平动和转动自由度的状态响应性能及LACKI规则针对外界干扰的估计效果，通过与常规线性控制方法的对比，验证了所提方法对于提高无拖曳控制精度的有效性。
- 监督学习 /
- Lipschitz估计 /
- 模型参考自适应控制 /
- 无拖曳控制 /
- 输出调节 /
- Kinky Inference
Abstract:
Achieving ultra-precision and ultra-stable requirements is challenging in the space gravitational wave detection mission due to complex disturbances present in the spacecraft's internal test masses, including load hardware noise, environmental noise, and micro-thrust coupling noise.These disturbances impact the accuracy of drag-free control. In this paper, an adaptive drag-free control method is proposed for spacecraft based on the lazily adapted Lipschitz constant Kinky Inference (LACKI) scheme. When there is not enough empirical data, the LACKI scheme is used to approximate disturbances and suppress non-Lipschitz components. The model reference adaptive control (MRAC), which is based on output regulation, is then used to precise the drag-free control of test masses. Numerical simulation verifies the state response performance of the translational and rotational degrees of freedom of sensitive axes and the estimation effect of the LACKI rule for random discontinuous disturbances, and the accuracy conclusion of the drag-free control loop is obtained.
- supervised learning /
- Lipschitz estimation /
- model reference adaptive control /
- drag-free control /
- output regulation /
- Kinky Inference

HTML全文

图 1 LISA Pathfinder航天器构型^[10]

Figure 1. LISA Pathfinder spacecraft configuration^[10]

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图 2 控制结构

Figure 2. Control structure

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图 3 LACKI规则下各自由度输入噪声估计

Figure 3. Input noise observation for each degree of freedom under LACKI rule

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图 4 LACKI-MRAC方案下增量学习性能

Figure 4. Supervised learning performance under LACKI-MRAC scheme

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图 5 不同方案下噪声估计误差对比

Figure 5. Noise estimation error comparison of various schemes

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图 6 LACKI-MRAC方案与QFT方案位移响应对比

Figure 6. Displacement response comparison between LACKI-MRAC scheme and QFT scheme

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