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

Jianping Yuan,Shun An,Hongfei Mao,Longjin Wang,Xinxiang Pan

doi:10.1109/access.2021.3057454

Abstract

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.

Highlights

When a ship is sailing in a sea way, the manoeuvring characteristics are influenced by external forces and moments caused by waves [1]
As the sea state and navigation state vary constantly, the peak frequency of the wave spectrum is modified by the wave encounter frequency which varies with the wave state, the total speed of the ship and the angle between the heading and the direction of the wave, which leads to the difficulty of wave filter design [5]
In order to verify the performance of the proposed algorithms, a ship heading control system is constructed using the wave peak frequency tracker

Summary

Introduction

When a ship is sailing in a sea way, the manoeuvring characteristics are influenced by external forces and moments caused by waves [1]. In order to increase the safety and performance of the ship control system, a filter based on the wave peak frequency tracker is necessary to eliminate the effect of the wave disturbances. To describe the wave spectrum in different sea state accurately, both linear and nonlinear models were proposed [2], [3]. Among the proposed descriptions of the wave spectrum, the 2nd-order linear wave disturbance model which is applied to fit the shape of the PM spectrum is widely used for filter design [4]. Belleter et al proposed a signal based nonlinear wave encounter frequency estimator which

Objectives

Results

Conclusion