文献类型：期刊文献

英文题名：A noise-suppressing Newton-Raphson iteration algorithm for solving the time-varying Lyapunov equation and robotic tracking problems

作者：Wang, Guancheng[1,2];Huang, Haoen[1,2];Shi, Limei[1];Wang, Chuhong[1];Fu, Dongyang[1,2];Jin, Long[3];Xiao Xiuchun[1,2]

机构：[1]Guangdong Ocean Univ, Coll Elect & Informat Engn, Zhanjiang 524088, Peoples R China;[2]Guangdong Ocean Univ, Shenzhen Inst, Shenzhen 518108, Peoples R China;[3]Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China

年份：2021

卷号：550

起止页码：239

外文期刊名：INFORMATION SCIENCES

收录：SCI-EXPANDED(收录号：WOS:000605760900015)、、EI(收录号：20204609491061)、Scopus(收录号：2-s2.0-85095950551)、WOS

基金：This work was supported in part by the Innovation and Strength Project in Guangdong Province (Natural Science) (No. 230419065), in part by the Key Lab of Digital Signal and Image Processing of Guangdong Province (No. 2019GDDSIPL-01), in part by the Industry-University-Research Cooperation Education Project of Ministry of Education (No. 201801328005), in part by the Guangdong Graduate Education Innovation Project, Graduate Summer School (No. 2020SQXX19), in part by the Special Project in Key Fields of Universities in Department of Education of Guangdong Province (No. 2019KZDZX1036), in part by the Guangdong Graduate Education Innovation Project, Graduate Academic Forum (No. 2020XSLT27), in part by the Doctoral Initiating Project of Guangdong Ocean University (No. E13428), in part by the Youth Innovation Project of the Department of Education of Guangdong Province (No. 2020KQNCX026), in part by the National Natural Science Foundation of China (No. 61703189), in part by the Natural Science Foundation of Chongqing (China) under grant (No. Cstc2020jcyjzdxmX0028), in part by the Key projects of the Guangdong Education Department (2019KZDXM019), in part by the Fund of Southern Marine Science and Engineering Guangdong Laboratory (Zhanjiang)(ZJW-2019-08), in part by the High-level marine discipline team project of Guangdong Ocean University(002026002009), in part by the Guangdong graduate academic forum project(230420003), in part by the "first class" discipline construction platform project in 2019 of Guangdong Ocean University (231419026).

语种：英文

外文关键词：Time-varying Lyapunov equation; Newton-Raphson iteration; Noise suppressing; Robotic tracking problems

外文摘要：The Newton-Raphson iteration (NRI) algorithm is a prevalent computational methodology in many fields and can be used to solve the time-varying Lyapunov equation. However, the performance of the traditional NRI (TNRI) algorithm is severely degraded under noisy conditions. To overcome this weakness, a noise-suppressing NRI (NSNRI) algorithm is proposed in this paper. By utilizing the Kronecker product theorem, the time-varying Lyapunov equation can be transformed into a linear matrix equation. Based on that linear matrix equation, the related theoretical analyses of the convergence and the noisesuppressing property of the NSNRI algorithm under various noise conditions are provided. To verify the theoretical analyses, numerical simulations for solving the time-varying Lyapunov equation and an application to manipulator motion tracking are presented. For comparison purpose, the TNRI and two zeroing neural network (ZNN) algorithms are also introduced in these simulations. As indicated by the simulation results, the NSNRI algorithm is superior in terms of the convergence accuracy and the robustness to noise. (C) 2020 Elsevier Inc. All rights reserved.