| Author Name | Affiliation | | Xiaoning Shi | School of Electronic Information, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, China
Fujian Quanzhou-HIT Research Institute of Engineering and Technology, Quanzhou 362000, Fujian, China | | Di Zhou | School of Astronautics, Harbin Institute of Technology, Harbin 150001, China | | Zhigang Zhou | School of Electronic Information, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, China
Fujian Quanzhou-HIT Research Institute of Engineering and Technology, Quanzhou 362000, Fujian, China |
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| Abstract: |
| This paper addresses a geometric control algorithm for the attitude tracking problem of the rigid spacecraft modeled on SO(3). Considering the topological and geometric properties of SO(3), we introduced a smooth positive attitude error function to convert the attitude tracking issue on SO(3) into the stabilization counterpart on its Lie algebra. The error transformation technique was further utilized to ensure the assigned transient and steady state performance of the attitude tracking error with the aid of a well- designed assigned-time performance function. Then, using the actor-critic (AC) neural architecture, an adaptive reinforcement learning approximator was constructed, in which the actor neural network (NN) was utilized to approximate the unknown nonlinearity online. A critic function was introduced to tune the next phase of the actor neural network operation for performance improvement via supervising the system performance. A rigorous stability analysis was presented to show that the assigned system performance can be achieved. Finally, the effectiveness and feasibility of the constructed control strategy was verified by the numerical simulation. |
| Key words: spacecraft attitude tracking appointed-time control performance constraints actor-critic NNs |
| DOI：10.11916/j.issn.1005-9113.2021135 |
| Clc Number:TP301.1 |
| Fund: |
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| Descriptions in Chinese: |
| 基于强化学习的刚性航天器指定时间预设性能姿态控制方法 史晓宁1,2, 周荻3, 周智刚1,2 (1.江苏科技大学 电子信息学院, 江苏 镇江212000; 2. 福建（泉州）哈工大工程技术研究院, 福建 泉州 362000；3. 哈尔滨工业大学, 航天学院, 哈尔滨150000) 摘要：本文针对SO(3)群上描述的刚性航天器姿态跟踪控制问题提出一种几何控制算法。考虑到SO(3)群的拓扑和几何特性，通过引入一个光滑正定的姿态误差函数，将SO(3)群上的姿态跟踪问题转化为相应李代数上的镇定问题。借助设计良好的指定时间性能函数，本文利用误差变换技术确保姿态跟踪误差的瞬态和稳态性能。另外本文在行动器-评判器神经框架下构造一个自适应强化学习估计器，其中行动神经网络用来在线估计未知的非线性项。通过引入评价函数来监督系统的性能从而改善下一阶段行动神经网络的估计性能。此外给出了严格的稳定性分析，并证明了系统能够达到指定的性能指标。最后，通过数值仿真验证了所构造控制算法的有效性和可行性。 关键词：航天器姿态跟踪；指定时间控制；性能约束；AC神经网络 |
