不确定数据的状态空间估计:有限和无限视界结果

Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187) Pub Date : 2000-12-12 DOI:10.1109/CDC.2001.914664

A. H. Sayed

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引用次数: 0

摘要

为具有参数不确定性的状态空间模型开发了一种鲁棒估计程序。与现有的鲁棒滤波器相比，该滤波器对数据进行正则化而不是反正则化。结果表明，在一定的稳定性和可检测性条件下，稳态滤波器是稳定的，对于二次稳定模型，它保证误差方差有界。

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State-space estimation with uncertain data: finite and infinite-horizon results

Develops a robust estimation procedure for state-space models with parametric uncertainties. Compared with existing robust filters, the proposed filter performs data regularization rather than de-regularization. It is shown that, under certain stabilizability and detectability conditions, the steady-state filter is stable and that, for quadratically-stable models, it guarantees a bounded error variance.

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Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187)

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