文献类型：期刊文献

英文题名：Noise-Suppressing Newton Algorithm for Kinematic Control of Robots

作者：Xiao, Xiuchun[1];Wei, Lin[2];Fu, Dongyang[1];Yan, Jingwen[3];Wang, Huan[1]

机构：[1]Guangdong Ocean Univ, Coll Elect & Informat Engn, Zhanjiang 524088, Peoples R China;[2]Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Peoples R China;[3]Shantou Univ, Coll Elect Engn, Shantou 515000, Peoples R China

年份：2025

卷号：13

起止页码：124295

外文期刊名：IEEE ACCESS

收录：SCI-EXPANDED(收录号：WOS:001534522000008)、、EI(收录号：20240915653737)、Scopus(收录号：2-s2.0-85082242214)、WOS

基金：This work was supported in part by the National Natural Science Foundation of China under Grant 61703189, in part by the International Science and Technology Cooperation Program of China under Grant 2017YFE0118900, in part by the Key Laboratory of Digital Signal and Image Processing of Guangdong Province under Grant 2016GDDSIPL-02, in part by the Doctoral Initiating Project of Guangdong Ocean University under Grant E13428, in part by the Innovation and Strength Project of Guangdong Ocean University under Grant Q15090 and Grant 230419065, in part by the Natural Science Foundation of Gansu Province, China, under Grant 18JR3RA264, in part by the Sichuan Science and Technology Program under Grant 19YYJC1656, in part by the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, under Grant 20190112, and in part by the Fundamental Research Funds for the Central Universities under Grant lzujbky-2019-89.

语种：英文

外文关键词：Redundancy; Kinematics; Signal processing algorithms; Heuristic algorithms; End effectors; Noise-suppressing Newton algorithm; redundancy resolution; serial redundant robot manipulators; parallel redundant robot manipulators

外文摘要：In this paper, armed with the integral control method, a new noise-suppressing Newton (NSN) algorithm is proposed for the redundancy resolution of redundant robot manipulators efficiently. For practical hardware implementation, the discrete-time noise-suppressing Newton (abbreviated as DTNSN) algorithm is discretized from the continues NSN algorithm. Specifically, the distinguishing feature of the proposed DTNSN algorithm is that it can rigorously converge with inherent tolerance to noises induced by communication jamming and computational systematical errors. In contrast, considerable traditional algorithms often dispose of noises with the high-degree filter from the viewpoint of signal processing, which requires a complex system structure and further results in a heavy computational burden. Note that theoretical analyses are provided to elaborate the convergent property of the DTNSN algorithm polluted with constant bias, time-dependent linear noises and bounded random noises. Besides, by the proposed DTNSN algorithm, the end effector of both serial and parallel redundant robot manipulators complete the allocated motion planning and are impervious to the noisy simulated environment.