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Fictitious Reference Iterative Tuning of Disturbance Observers for Attenuation of the Effect of Periodic Unknown Exogenous Signals

机译:虚拟参考迭代调整干扰观察者,用于衰减周期性未知外源信号的效果

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In this paper, we develop a data-driven controller tuning for the disturbance observers. Particularly, we focus on the disturbance attenuation problem for a periodic unknown disturbance. However, in the case where it is difficult to construct inverse mathematical model of a plant which is implemented in the disturbance observer, we have to tale much time and costs for identification. In order to overcome such a difficulty, we utilize fictitious reference iterative tuning (FRIT), which is data-driven controller tuning with only one-shot experimental data, for tuning of parameters of controllers to eliminate the effect of the disturbance.
机译:在本文中,我们开发了一种用于干扰观察者的数据驱动控制器调整。特别是,我们专注于周期性未知干扰的扰动衰减问题。然而,在难以构建在干扰观察者中实现的植物的逆数学模型的情况下,我们必须缩小很多时间和成本。为了克服这种困难,我们利用虚构参考迭代调谐(FRIT),该调整(FRIT)是仅具有单次实验数据的数据驱动控制器调整,用于调整控制器的参数,以消除干扰的效果。

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