文献类型：期刊文献

英文题名：An Integration-Implemented Newton-Raphson Iterated Algorithm With Noise Suppression for Finding the Solution of Dynamic Sylvester Equation

作者：Wang, Guancheng[1,2];Huang, Haoen[1,2];Yan, Jingkun[3];Cheng, Yihang[1,2];Fu, Dongyang[1,2]

机构：[1]Guangdong Ocean Univ, Sch Elect & Informat Engn, Zhanjiang 524025, Peoples R China;[2]Guangdong Ocean Univ, Shenzhen Inst, Shenzhen 518108, Peoples R China;[3]Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Peoples R China

年份：2020

卷号：8

起止页码：34492

外文期刊名：IEEE ACCESS

收录：SCI-EXPANDED(收录号：WOS:000567609700041)、、EI(收录号：20201008273964)、Scopus(收录号：2-s2.0-85080881131)、WOS

基金：This work was supported in part by the Fund of Southern Marine Science and Engineering Guangdong Laboratory, Zhanjiang, under Grant ZJW-2019-08, in part by the Project of Enhancing School with Innovation of Guangdong Ocean University under Grant GDOU2014050226, in part by the Project of Innovation Training Project of Guangdong Ocean University under Grant CXXL2019276, and in part by the Innovation and Strength Project of Guangdong Ocean University under Grant Q15090 and Grant 230419065.

语种：英文

外文关键词：Heuristic algorithms; Mathematical model; Newton method; Robustness; Perturbation methods; Oceans; Convergence; Dynamic Sylvester equation; integration-implemented; Newton-Raphson iterated algorithm; noise suppression

外文摘要：Solving dynamic Sylvester matrix equations is a prevalent research topic and many methods have been arisen to solve the dynamic Sylvester equation, but few of them consider the noise effect. To investigate the new approach which can suppress the noise effect, integration feedback is added in the conventional Newton-Raphson iterated (CNRI) algorithm to form the proposed integration-implemented Newton-Raphson iterated (IINRI) algorithm based on the control theorem. Besides, this paper transforms the dynamic Sylvester equation into a linear equation which turns into the zeroing finding problem in further by constructing the error function. According to the theoretical analyses and the simulation results, the IINRI algorithm has higher accuracy and strong robustness under different noises (e.g. the constant noise, the linear noise, and the bounded random noise) while the performance of the CNRI algorithm is seriously degraded by the noises, which reveals that the IINRI algorithm is an efficient and powerful approach to solve dynamic Sylvester equation under noise perturbations.