文献类型：期刊文献

英文题名：A Wave Peak Frequency Tracking Method Based on Two-Stage Recursive Extended Least Squares Identification Algorithm

作者：Yuan, Jianping[1,2];An, Shun[3];Pan, Xinxiang[1];Mao, Hongfei[1];Wang, Longjin[3]

机构：[1]Guangdong Ocean Univ, Coll Ocean Engn, Zhanjiang 524088, Peoples R China;[2]Harbin Engn Univ, Coll Ship Engn, Harbin 150001, Peoples R China;[3]Qingdao Univ Sci & Technol, Coll Electromech Engn, Qingdao 266061, Peoples R China

年份：2021

卷号：9

起止页码：86514

外文期刊名：IEEE ACCESS

收录：SCI-EXPANDED(收录号：WOS:000673113900001)、、EI(收录号：20210809935595)、Scopus(收录号：2-s2.0-85100857108)、WOS

基金：This work was supported by the State Administration of Science, Technology and Industry for National Defence under Grant JCKYS2019604SXJQR-02.

语种：英文

外文关键词：Marine vehicles; Signal processing algorithms; Frequency estimation; Computational modeling; Heuristic algorithms; Frequency control; Autoregressive processes; Wave frequency tracker; least squares; recursive identification; hierarchical identification

外文摘要：This paper proposes the wave peak frequency tracking methods based on the least squares identification algorithm. The wave disturbance model is transformed into an autoregressive moving average (ARMA) model and a recursive extended least squares (RELS) algorithm is derived to identify the model parameters by using the auxiliary model identification idea. Furthermore, a two-stage recursive extended least squares (2S-RELS) algorithm is presented to improve the convergence speed by using the hierarchical identification principle. A ship heading control system with the wave peak frequency tracker is built to evaluate the effectiveness of the proposed algorithms. Finally, simulation results show that the proposed algorithms can estimate the wave peak frequency accurately and the 2S-RELS algorithm can improve the convergence speed effectively.