上海交通大学学报

上海交通大学学报 >

2022 , Vol. 56 >Issue 7: 868 - 876

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2021.186

电子信息与电气工程

基于扰动块的柔性臂分布式滚动时域估计

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  • 浙江工业大学 信息工程学院, 杭州 310023
徐晨辉(1996-),男,浙江省宁波市人,博士生,研究方向为鲁棒滚动时域估计.

收稿日期: 2021-06-02

  网络出版日期: 2022-08-16

基金资助

国家自然科学基金(61773345);浙江省高校基本科研业务费项目(RF-C2020003)

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Disturbance-Blocking-Based Distributed Receding Horizon Estimation of Flexible Joint Robots

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  • College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China

Received date: 2021-06-02

  Online published: 2022-08-16

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摘要

针对柔性机械臂因在实际运动过程中易发生变形而需进行状态监测的问题,提出一种基于扰动块的分布式滚动时域估计算法.在分布式一致性滚动时域估计的基础上,通过设计扰动块并将其应用于估计窗口内的过程扰动序列,减少了与优化相关的变量,从而降低了算法的计算量,实现快速性.通过分析算法在最大分块长度下的可行性与收敛性,建立了保证算法的优化问题存在等价解的假设条件,并将结果推广到了过程扰动任意分块的情况.仿真结果表明:与不加扰动块的算法相比,所提算法能在不影响估计误差的前提下有效缩短计算时间.

关键词： 柔性机械臂; 状态估计; 滚动时域估计; 分布式估计; 扰动块

本文引用格式

徐晨辉, 俞芳慧, 何德峰 . 基于扰动块的柔性臂分布式滚动时域估计[J]. 上海交通大学学报, 2022 , 56(7) : 868 -876 . DOI: 10.16183/j.cnki.jsjtu.2021.186

Abstract

Considering the state monitoring problem of flexible joint robots (FJRs) caused by the easy deformation in practice, a distributed receding horizon estimation algorithm based on disturbance blocks is proposed. Based on distributed consistent receding horizon estimation, the proposed algorithm reduces the computational amount and achieves rapidity by designing the disturbance block and applying it to the process disturbance sequence in the estimation window to reduce the variables related to optimization. By analyzing the feasibility and convergence of the proposed algorithm based on the maximum block length, the assumptions are made under which the existence of equivalent solution to the optimization problem of the algorithm is guaranteed, and the results are extended to the case that the process disturbance can be divided into arbitrary blocks. The simulation results show that the proposed algorithm can effectively shorten the computation time without affecting the estimation error compared with the algorithm without disturbance blocks.

Key words： flexible joint robots (FJRs); state estimation; receding horizon estimation; distributed estimation; disturbance blocks

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