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Alternative TitleResearch on Gravity Balance Control of Suspended Space Manipulator
Thesis Advisor徐永利
Keyword空间机械臂 微重力模拟 模糊PID控制 力/位混合控制 RBF神经网络PID控制
Degree Discipline控制工程
Degree Name专业学位硕士
Degree Grantor中国科学院沈阳自动化研究所
Place of Conferral沈阳
Abstract随着航天技术的发展,越来越多的空间机械臂被应用到在轨服务中。为了保证空间机械臂在太空中稳定运行,就需要在升空之前对其进行大量的地面微重力环境下的仿真实验验证其各种性能指标。为了实现空间机械臂的地面微重力环境,同时保证高精度的微重力环境模拟效果,本文设计了一种三维主动悬吊式微重力模拟系统。该系统设有3个吊点机构,每个吊点实现微重力模拟的机构主要包括恒张力吊挂单元和二维水平直线运动单元。恒张力吊挂单元通过力传感器的反馈采用主动控制的方式实现空间机械臂竖直方向上的运动跟随和重力补偿。该单元的控制精度的高低直接影响到重力补偿精度的高低。二维水平直线运动单元通过角度传感器的反馈采用主动控制的方式实现空间机械臂水平方向上的运动跟随。该单元的运动跟随精度决定了是否会引入水平分力从而影响重力补偿精度。本文主要研究如何提高悬吊式微重力模拟系统的重力补偿精度。首先针对恒张力吊挂单元建立了数学模型,采用恒张力的控制思想提出一种基于模糊PID参数整定的力/位混合控制算法。该算法采用位置控制回路与力控制回路并联控制的结构,在力控制回路中通过模糊控制实现PID控制器参数的在线调整,实现高精度的重力补偿。并针对该单元的卷扬电机与电动缸的复合运动提出一种复合控制策略,实现卷扬电机对电动缸位移量程的扩展。然后针对于二维水平直线运动单元,设计了一种3-8-1网络结构的基于RBF神经网络系统辨识的增量式PID控制算法。通过RBF神经网络实现PID控制器参数的自适应调整,用以提高水平方向上的跟随运动的控制精度,从而避免引入水平分力对重力补偿精度造成影响。此外,本文还给出了控制系统的硬件组成及选型以及软件功能的设计流程。并在MATLAB/Simulink环境中搭建了仿真模型,仿真实验结果表明基于模糊PID 参数整定的力/位混合控制算法能够将重力补偿精度控制在0.3%F.S(全量程)之内,基于RBF神经网络系统辨识的PID控制算法能够将吊索的偏角控制在0.4°之内,并且整个重力平衡系统具有较强的抗干扰能力和良好的动态响应性能。再加之现场实际实验得到的数据可知,本文设计的控制算法满足悬吊式微重力模拟系统的项目指标要求。
Other AbstractWith the development of aerospace technology, more and more space manipulators are being applied to orbit services. In order to ensure the stable operation of the space manipulator in space, it is necessary to perform a large number of simulation experiments on the ground microgravity environment to verify its various performance indicators before launching. In order to realize the ground microgravity environment of the space manipulator, and at the same time ensure the high-precision microgravity environment simulation effect, a three-dimensional active suspension microgravity simulation system is designed in this paper. The system is provided with 3 lifting point mechanisms, and the mechanism for microgravity simulation of each hanging point mainly includes a constant tension hanging unit and a 2-dimensional horizontal linear motion unit. The constant tension suspension unit adopts the active control mode to realize the motion following and vertical gravity compensation of the space manipulator through the feedback of the force sensor. The control accuracy of this unit directly affects the accuracy of gravity compensation. The 2-dimensional horizontal linear motion unit uses the feedback of the angle sensor to actively follow the movement of the space manipulator in the horizontal direction through active control. The motion following accuracy of this unit determines whether horizontal component force will be introduced and affect the accuracy of gravity compensation. This article mainly studies how to improve the accuracy of gravity compensation of suspended microgravity simulation system. First, a mathematical model is established for the constant tension hanging unit, and a constant force / position hybrid control algorithm based on fuzzy PID parameter tuning is proposed using the constant tension control idea. The algorithm adopts a structure in which the position control loop and the force control loop are controlled in parallel. In the force control loop, the PID controller parameters are adjusted online through fuzzy control to achieve high-precision gravity compensation. A composite control strategy for the combined motion of the hoisting motor and electric cylinder of the unit is proposed to realize the extension of the displacement range of the electric cylinder by the hoisting motor. Aiming at the 2D horizontal linear motion unit, an incremental PID control algorithm based on RBF neural network system identification based on 3-8-1 network structure is designed. The adaptive adjustment of the PID controller parameters is realized through the RBF neural network to improve the control accuracy of the following motion in the horizontal direction, so as to avoid the influence of the introduction of horizontal component force on the accuracy of gravity compensation. In addition, this paper also gives the hardware composition and selection of the control system and the design flow of the software functions. A simulation model is built in the MATLAB / Simulink environment. Simulation results show that the hybrid force / position control algorithm based on fuzzy PID parameter tuning can control the accuracy of gravity compensation within 0.3% F.S (full range). The PID control algorithm based on RBF neural network system identification can control the deflection angle of the sling within 0.4 °. And the entire gravity balance system has strong anti-interference ability and good dynamic response performance. Coupled with the data obtained from the actual field experiments, it can be seen that the control algorithm designed in this paper meets the project index requirements of the suspended microgravity simulation system.
Contribution Rank1
Document Type学位论文
Recommended Citation
GB/T 7714
李潇男. 悬吊式空间机械臂重力平衡控制研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2020.
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