Parameters concurrent learning and reactionless control in post-capture of unknown targets by space manipulators

Parameters concurrent learning and reactionless control in post-capture of unknown targets by space manipulators
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空间操纵器捕获未知目标后的参数并发学习和无反应控制

DOI:
10.1007/s11071-019-04798-w
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发表时间:
2019-04
期刊:
影响因子:
5.6
通讯作者:
Yuan Jianping
Yuan Jianping
中科院分区:
工程技术2区
文献类型:
--
作者:
Zong Lijun;Luo Jianjun;Wang Mingming;Yuan Jianping

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研究空间机械臂捕获未知目标后的参数辨识和基座扰动最小化问题。提出了一种同时利用系统过去运动数据点和瞬时运动数据点进行参数辨识的并行学习算法。给定一个用于选择所使用的过去数据点的条件以及一个缩放技术,使参数具有相同的幅度,并行学习算法保证参数识别误差可以全局收敛到零,以指数速率,而不需要满足持续激励(PE)条件。基于无源性原理和任务优先法,提出了一种自适应无反应控制方法,在系统产生激励运动进行参数辨识的过程中,保证基座姿态平稳,关节运动满足极限。仿真结果验证了该方法的有效性。
This paper studies parameters identification and minimizing base disturbances problems after the space manipulator capturing an unknown target. A concurrent learning algorithm that concurrently uses past motion data points and instantaneous motion data of the system is proposed for the parameters identification. Given a condition for selecting the used past data points as well as a scaling technique to make the parameters have the same magnitude, the concurrent learning algorithm guarantees that parameters identification errors can globally converge to zero at an exponential rate and without the need for satisfying the persistent excitation (PE) condition. An adaptive reactionless control method is proposed based on the passivity theorem and Task-priority method, which ensures that the base attitude is stationary and joint motions satisfy the limits during the system generating excitation motions for the parameters identification. Simulation results verify the effectiveness of the proposed method.
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发表时间: 2015
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