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Estimation of ship oscillation subject to ship speed variation using an algorithm combining H#x221E; and Kalman Filters

机译:结合H 和卡尔曼滤波器的算法估计船舶速度变化下的船舶振动

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This paper presents an estimation method of ship oscillation subject to ship speed variation, which leads to oscillation frequency variation. Such variation will deteriorate the estimation performance particularly when relying on a model-based estimation algorithm such as the Kalman filter. To overcome the problem, we propose an estimation method of ship oscillation with a low-cost gyro rate sensor, which incorporates periodic updates of fast Fourier transform (FFT)-based model and a method of selectively combining multiple H∞ and Kalman filters according to an innovation-based criterion. The latter algorithm is the heart of our estimation method, which aims at utilizing the advantage of each filter. Some simulation results show that the proposed method is more effective than the conventional H∞ and Kalman filters.
机译:本文提出了一种基于船舶速度变化的船舶振动估计方法,该方法导致了船舶振动频率的变化。这种变化将特别是在依赖基于模型的估计算法(例如卡尔曼滤波器)时降低估计性能。为解决该问题,我们提出了一种低成本陀螺率传感器的船舶振动估计方法,该方法结合了基于快速傅里叶变换(FFT)的模型的周期性更新以及根据以下特征有选择地组合多个H∞和卡尔曼滤波器的方法:基于创新的标准。后一种算法是我们估算方法的核心,该方法旨在利用每个滤波器的优势。仿真结果表明,该方法比传统的H∞和卡尔曼滤波器更有效。

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