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Algorithms for robust identification in H-infinity with nonuniformly spaced frequency response data

机译:具有不均匀间隔的频率响应数据的H无穷大鲁棒识别算法

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In this paper, first a two-stage robustly convergent identification algorithm in H-infinity for nonuniformly spaced data is proposed. The worst-case error of the algorithm converges to zero faster than polynomial rates in the noise-free case when the identified system is an exponentially stable discrete-time system. The algorithm is characterized by a rational interpolation step with fixed poles at zero and infinity. Next, a minimax algorithm with better convergence properties is introduced. Sensitivity of the algorithms to small variations in the frequency values is also studied. [References: 28]
机译:在本文中,首先提出了一种用于H-无穷大的两阶段非均匀间隔数据的鲁棒收敛收敛两阶段辨识算法。当所识别的系统是指数稳定的离散时间系统时,在无噪声情况下,算法的最坏情况误差收敛到零,比多项式速率快。该算法的特征在于在零和无穷大处有固定极点的有理插值步骤。接下来,介绍具有更好收敛性的minimax算法。还研究了算法对频率值的微小变化的敏感性。 [参考:28]

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