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Discrete-time repetitive control with model-less FIR filter inversion for high performance nanopositioning

机译:具有无模型FIR滤波器反演的离散时间重复控制可实现高性能纳米定位

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Repetitive control (RC) is used to track and reject periodic exogenous signals. RC achieves tracking by incorporating a model of a periodic signal in the feedback path, which provides infinite loop-gain at the harmonic frequencies of the periodic signal. To improve robustness, the periodic signal model is bandwidth limited, and to improve the performance, an inverse plant response filter is used. This filter can either be an infinite impulse response (IIR) filter or a finite impulse response (FIR) filter. The accuracy of the filter typically determines the allowable bandwidth of the periodic signal model, and it is therefore desirable to obtain the most accurate inverse possible. In this paper a model-less method for synthesizing an FIR filter for the inverse response is presented, and it is compared to the common approach of using an inverse model-based IIR filter. An experimental comparison of the two approaches is presented, and it is demonstrated that the two methods produce identical results, but where the model-less FIR filter approach has the added benefit of avoiding the modeling effort needed to obtain the IIR filter.
机译:重复控制(RC)用于跟踪和拒绝周期性外源信号。 RC通过在反馈路径中结合定期信号的模型来实现跟踪,该模型在周期信号的谐波频率下提供无限的环增益。为了提高鲁棒性,定期信号模型是带宽限制,并使用逆植物响应滤波器来改善性能。该过滤器可以是无限脉冲响应(IIR)滤波器或有限脉冲响应(FIR)滤波器。滤波器的精度通常确定周期性信号模型的允许带宽,因此希望获得最准确的逆可能。在本文中,提出了一种用于合成用于逆响应的FIR滤波器的模型方法,并将其与使用逆模型的IIR滤波器进行比较。提出了两种方法的实验比较,并证明这两种方法产生相同的结果,但是在较少的FIR滤波器方法具有避免获得IIR滤波器所需的建模工作的增加的益处。

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