文献类型：期刊文献

英文题名：Modified Newton Integration Algorithm With Noise Tolerance Applied to Robotics

作者：Fu, Dongyang[1,2,3];Huang, Haoen[1,2,3];Wei, Lin[4,5];Xiao, Xiuchun[1,2,3];Jin, Long[4,5];Liao, Shan[6];Fan, Jialiang[4,5];Xie, Zhengtai[4,5]

机构：[1]Guangdong Ocean Univ, Sch Elect & Informat Engn, Zhanjiang 524088, Peoples R China;[2]Guangdong Ocean Univ, Guangdong Prov Engn & Technol Res Ctr Marine Remo, Zhanjiang 524088, Guangdong, Peoples R China;[3]Guangdong Ocean Univ, Shenzhen Inst, Shenzhen 518108, Peoples R China;[4]Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Beijing 100049, Peoples R China;[5]Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Peoples R China;[6]Sichuan Univ, Sch Cybersecur, Chengdu 610000, Peoples R China

年份：2022

卷号：52

期号：4

起止页码：2134

外文期刊名：IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS

收录：SCI-EXPANDED(收录号：WOS:000732097300001)、、EI(收录号：20210609899477)、Scopus(收录号：2-s2.0-85100503935)、WOS

基金：This work was supported in part by the Fund of Southern Marine Science and Engineering Guangdong Laboratory of Zhanjiang, China, under Grant ZJW-2019-08; in part by the Key Projects of the Guangdong Education Department under Grant 2019KZDXM019; in part by the High-Level Marine Discipline Team Project of Guangdong Ocean University under Grant 002026002009; in part by the Guangdong Graduate Academic Forum Project under Grant 230420003; in part by the First Class Discipline Construction Platform Project in 2019 of Guangdong Ocean University under Grant 231419026; in part by the CAAI-Huawei MindSpore Open Fund under Grant CAAIXSJLJJ-2020-009A; in part by the CAS "Light of West China" Program; in part by the Innovation and Strength Project in Guangdong Province, China (Natural Science) under Grant 230419065; in part by the Key Lab of Digital Signal and Image Processing of Guangdong Province, China, under Grant 2019GDDSIPL-01; in part by the IndustryUniversity-Research Cooperation Education Project of Ministry of Education under Grant 201801328005; in part by the Guangdong Graduate Education Innovation Project, Graduate Summer School under Grant 2020SQXX19; in part by the Special Project in Key Fields of Universities in Department of Education of Guangdong Province under Grant 2019KZDZX1036; in part by the Guangdong Graduate Education Innovation Project, Graduate Academic Forum under Grant 2020XSLT27; in part by the Doctoral Initiating Project of Guangdong Ocean University under Grant E13428; in part by the Special Project in Key Fields of Universities in Department of Education of Guangdong Province, China, under Grant 2019033; and in part by the Natural Science Foundation of Chongqing, China, under Grant cstc2020jcyjzdxmX0028. This article was recommended by Associate Editor M. Zhou.

语种：英文

外文关键词：Mathematical model; Heuristic algorithms; Oceans; Noise measurement; Iterative algorithms; Education; Technological innovation; Dynamic system of linear equations; modified Newton integration (MNI) algorithm; noise tolerance; steady-state error

外文摘要：Currently, the Newton-Raphson iterative algorithm has been extensively employed in the fields of basic research and engineering. However, when noise components exist in a system, its performance is largely affected. To remedy shortcomings that the conventional computing methods have encountered in a noisy workspace, a novel modified Newton integration (MNI) algorithm is proposed in this article. In addition, the steady-state error of the proposed MNI algorithm is smaller than that of the Newton-Raphson algorithm under a noise-free or noisy workspace. To lay the foundations for the corresponding theoretical analyses, the proposed MNI algorithm is first converted into a homogeneous linear equation with a residual term. Then, the related theoretical analyses are carried out, which indicate that the MNI algorithm possesses noise-tolerance ability under various noisy environments. Finally, multiple computer simulations and physical experiments on robot control applications are performed to verify the feasibility and advantage of the proposed MNI algorithm.