A framework for state-space estimation with uncertain models

@article{Sayed2001AFF,
  title={A framework for state-space estimation with uncertain models},
  author={Ali H. Sayed},
  journal={IEEE Trans. Automat. Contr.},
  year={2001},
  volume={46},
  pages={998-1013}
}
This paper develops a framework for state-space estimation when the parameters of the underlying linear model are subject to uncertainties. Compared with existing robust filters, the proposed filters perform regularization rather than deregularization. It is shown that, under certain stabilizability and detectability conditions, the steady-state filters are stable and that, for quadratically-stable models, the filters guarantee a bounded error variance. Moreover, the resulting filter structures… CONTINUE READING
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T. Kailath, A. H. Sayed, B. Hassibi
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Indefinite Quadratic Estimation and Control: A Unified Approach to H andH Theories

B. Hassibi, A. H. Sayed, T. Kailath
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