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Repetitive Learning Control Based on Terminal Sliding Mode of Space Manipulator System with Elastic Base and Two Flexible Joints

机译:具有弹性基座的空间机械系统终端滑动的重复学习控制和两个柔性接头

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In this paper, based on the system linear momentum conversation and the Lagrange equation of second kind, the dynamic equation of the space manipulator system with elastic base and two flexible joints is established. According to the singular perturbation theory, the model is decomposed into a rigid subsystem and a flexible subsystem. A repetitive learning control based on terminal sliding mode is proposed for the rigid subsystem to tracking periodic reference signals in limited time. The repetitive learning control is the feed-forward compensation section, which is designed to track the periodic reference signal. Terminal sliding mode control is a feedback part, which is designed to suppress periodic or non-periodic interference. The combination of the two control methods allows the closed-loop system to achieve better trajectory tracking accuracy. Compared with traditional controllers, this method deals with highly uncertain controlled systems with less prior knowledge. The implementation of this scheme does not require dynamic model information of the system, can track periodic signals accurately and suppress periodic or aperiodic disturbances. For the elastic vibration of the flexible subsystem, a linear quadratic optimal control scheme is adopted to suppress the vibration. Finally, Lyapunov theory is used to prove the global asymptotic stability of the closed-loop system. Through the simulation calculation, the validity of repetitive learning control based on terminal sliding mode is verified.
机译:本文基于系统线性动量对话和第二种的拉格朗日方程,建立了具有弹性基座的空间机械手系统的动态方程和两个柔性接头。根据奇异扰动理论,该模型被分解成刚性子系统和柔性子系统。基于终端滑动模式的重复学习控制被提出用于刚性子系统,以在有限的时间内跟踪周期性参考信号。重复学习控制是前馈补偿部分,其旨在跟踪周期性参考信号。终端滑模控制是反馈部分,其旨在抑制周期性或非周期性干扰。两种控制方法的组合允许闭环系统实现更好的轨迹跟踪精度。与传统控制器相比,该方法处理高度不确定的受控系统,具有较少的先验知识。该方案的实现不需要系统的动态模型信息,可以准确地跟踪周期性信号并抑制周期性或非周期性干扰。对于柔性子系统的弹性振动,采用线性二次最佳控制方案来抑制振动。最后,Lyapunov理论用于证明闭环系统的全球渐近稳定性。通过仿真计算,验证了基于终端滑动模式的重复学习控制的有效性。

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