中国科技核心期刊

中文核心期刊

CSCD来源期刊

空间控制技术与应用 ›› 2023, Vol. 49 ›› Issue (3): 18-27.doi: 10.3969/j.issn.1674 1579.2023.03.003

• 论文与报告 • 上一篇    下一篇

基于Bi-LSTM网络的自由漂浮空间机械臂控制

  

  1. 北京邮电大学自动化学院
  • 出版日期:2023-06-26 发布日期:2023-07-11
  • 基金资助:
    国家自然科学基金资助项目(62103058)和“十四五”民用航天技术预先研究项目(D010301)

Free Floating Space Manipulator Control Based on Bi-LSTM Networks

  • Online:2023-06-26 Published:2023-07-11

摘要: 自由漂浮空间机械臂轨迹跟踪控制受模型不确定性和外部扰动影响。针对该问题, 提出了基于神经网络估计的自适应滑模控制策略. 对模型不确定问题, 采用双向长短期记忆神经网络 (Bi-LSTM) 对空间机械臂模型不确定性进行估计, 其中神经网络的估计方式为离线学习方式. 采用自适应滑模控制解决网络估计中的误差和外部扰动影响. 通过Lyapunov方法证明系统的稳定性, 数值仿真验证控制策略的有效性. 结果表明所提出的新型控制器能够实现低增益下控制性能的有效提升.

关键词: 自由漂浮, 空间机械臂, 模型不确定性, 神经网络, 自适应滑模控制, 外部扰动

Abstract: To solve the problem of trajectory tracking control for free floating space manipulator with model uncertainties and external disturbances, a neural network based adaptive sliding mode controller is proposed. To address the model uncertainty, the bidirectional long short term memory neural network (Bi-LSTM) is employed to estimate the uncertainty of the space manipulator model through offline learning. The adaptive sliding mode control is adopted to handle the estimation errors of neural network and external disturbances. The stability of the proposed controller is analyzed via Lyapunov theory. Numerical simulations verify the effectiveness of the proposed control strategy. The results show that the proposed novel controller can effectively improve the control performance at low gains.

Key words: free floating, space manipulator, model uncertainties, neural network, adaptive sliding mode control, external distarbances

中图分类号: 

  • V19