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A noise-suppressing Newton-Raphson iteration algorithm for solving the time-varying Lyapunov equation and robotic tracking problems
Wang, Guancheng1,2; Huang, Haoen1,2; Shi, Limei1; Wang, Chuhong1; Fu, Dongyang1,2; Jin, Long3; Xiao Xiuchun1,2
2021-03-01
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.
关键词Time-varying Lyapunov equation Newton-Raphson iteration Noise suppressing Robotic tracking problems
DOI10.1016/j.ins.2020.10.032
发表期刊INFORMATION SCIENCES
ISSN0020-0255
卷号550页码:239-251
通讯作者Jin, Long(jinlongsysu@foxmail.com)
收录类别SCI
WOS记录号WOS:000605760900015
语种英语