A Method of Reducing Invalid Steering for AUVs Based on a Wave Peak Frequency Tracker

Jianping Yuan, Jin Li (), Zhihui Dong, Qinglong Chen and Hanbing Sun
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Jianping Yuan: College of Ocean Engineering, Guangdong Ocean University, Zhanjiang 524088, China
Jin Li: College of Science, Jiujiang University, Jiujiang 332005, China
Zhihui Dong: College of Ocean Engineering, Guangdong Ocean University, Zhanjiang 524088, China
Qinglong Chen: College of Ocean Engineering, Guangdong Ocean University, Zhanjiang 524088, China
Hanbing Sun: Jiujiang Branch of the 707th Research Institute of China State Shipbuilding Corporation, Jiujiang 332005, China

Sustainability, 2022, vol. 14, issue 22, 1-14

Abstract: The motion control of autonomous underwater vehicles (AUVs) is affected by waves near the ocean surface or in shallow-water areas. Therefore, to counteract the influence of waves, we need to remove them by designing a filter. The wave peak frequency is important in wave filter design. This paper focuses on the identification of the wave peak frequency using the least-squares parameter estimation algorithm. The input–output expression of the wave disturbance model is derived by eliminating the intermediate variable. Based on the obtained identification model, an auxiliary model-based recursive extended least-squares identification algorithm is developed to estimate the model parameters. The effectiveness of the proposed method is verified with simulated tests of the heading control system of an AUV. The simulation results demonstrate that the proposed method is effective for the identification of the wave peak frequency, and an observer with a wave peak frequency tracker can significantly reduce invalid steering.

Keywords: least squares; wave frequency tracker; recursive identification; parameter estimation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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