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 ›› 2022, Vol. 48 ›› Issue (6): 12-21.doi: 10.3969/j.issn.1674 1579.2022.06.002

• 论文与报告 • 上一篇    下一篇

空间机械臂基于速度观测器的神经网络控制

  

  1. 南京晓庄学院电子工程学院
  • 出版日期:2022-12-26 发布日期:2023-01-16
  • 基金资助:
    国家自然科学基金资助项目(61772247)、浙江省自然科学基金重点项目(LZ21F020003)、浙江省自然科学基金资助项目(LY20E050002,LY18F030001)和南京晓庄学院高层次培育项目(2020NXY14)

Neural Network Control of Space Manipulator Based on Velocity Observer


  • Online:2022-12-26 Published:2023-01-16

摘要: 针对无速度反馈的柔性关节空间机器人控制问题,提出了一种基于速度观测器的自适应神经网络的控制方法.基于奇异摄动理论将柔性关节空间机械臂动力学模型分解为快慢变2个子系统;利用神经网络逼近控制器和观测器中的未知非线性,设计基于自适应神经网络的速度观测器和控制器,动态抵消模型不确定性对系统的影响;利用泰勒线性化方法,设计了权值、基函数中心和宽度参数在内的自适应学习律,提高了控制精度,且不需要离线学习;设计了基于速度差值的控制器来抑制快变子系统模型中的弹性振动;基于Lyapunov稳定性理论证明了闭环系统的一致最终有界.仿真实验证明了所提控制策略的有效性.

关键词: 空间机械臂, 柔性关节, 速度观测器, 神经网络, 振动抑制

Abstract: An adaptive neural network control method based on speed observer is proposed for the control of flexible joint space robot without speed feedback. Based on singular perturbation theory, the dynamic model of space manipulator with flexible joints is decomposed into two subsystems,fast and slow subsystems; Using neural network to approximate the unknown nonlinearity in the controller and observer, a speed observer and a controller based on adaptive neural network are designed to dynamically counteract the influence of model uncertainty on the system. Using Taylor linearization method, an on line adaptive learning law of weight, basis function center and width is designed, which improves the control accuracy and does not need the off line learning stage. A controller based on velocity difference is designed to suppress the elastic vibration in the model of the rapidly varying subsystem. Based on Lyapunov stability theory, the uniform ultimate boundedness of the closed loop system is proved. Simulation results show the effectiveness of the proposed control strategy.

Key words: space manipulator, flexible joints, speed observer, neural network, vibration suppression

中图分类号: 

  • TP241