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

机译:使用算法H &#X221E的算法估计船舶振荡对船舶速度变化进行船舶速度变化; 和卡尔曼过滤器

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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:本文介绍了船舶振荡的估计方法,以送货速度变化,导致振荡频率变化。在依赖于基于模型的估计算法之类的基于模型的估计算法之类的基于模型的估计算法之类的诸如卡尔曼滤波器的情况下,这种变化将劣化。为了克服这个问题,我们提出了一种利用低成本陀螺速率传感器的船舶振荡的估计方法,其包括基于快速傅里叶变换(FFT)的模型的周期性更新,以及根据诸如此选择性地组合多个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计方法的核心,其旨在利用每个过滤器的优点。一些仿真结果表明,该方法比传统的H∞和卡尔曼过滤器更有效。

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