This paper considers the problem of state estimation for discrete-time systems whose dynamics switches within a finite set of linear stochastic behaviors. The solution of the filtering problem depends on the a priori informations available on the switching process. In most papers the switching process is modeled by a finite-state Markov chain, with a known transition matrix. In this case the computation of the optimal filter is cumbersome and most papers deal with approximate filters. This paper considers systems in which the switching process is not statistically characterized. Such systems can be regarded as uncertain regular systems and can be transformed into singular systems with uncertainties only on the second order noise statistics. This allows to develop minimax linear filters, i.e. filters that give the minimum error variance in the worst case of noise statistics.

Germani, A., Manes, C., Palumbo, P. (2002). Filtering of switching systems via a singular minimax approach. In Proceedings of the IEEE Conference on Decision and Control (pp.2600-2605). IEEE Institute of Electrical and Electronics Engineers [10.1109/CDC.2002.1184230].

Filtering of switching systems via a singular minimax approach

Palumbo, P
2002

Abstract

This paper considers the problem of state estimation for discrete-time systems whose dynamics switches within a finite set of linear stochastic behaviors. The solution of the filtering problem depends on the a priori informations available on the switching process. In most papers the switching process is modeled by a finite-state Markov chain, with a known transition matrix. In this case the computation of the optimal filter is cumbersome and most papers deal with approximate filters. This paper considers systems in which the switching process is not statistically characterized. Such systems can be regarded as uncertain regular systems and can be transformed into singular systems with uncertainties only on the second order noise statistics. This allows to develop minimax linear filters, i.e. filters that give the minimum error variance in the worst case of noise statistics.
paper
Markov Linear-Systems; State Estimation; Unknown Inputs
English
41st IEEE Conference on Decision and Control - 10 December 2002 through 13 December 2002
2002
Proceedings of the IEEE Conference on Decision and Control
0-7803-7516-5
2002
3
2600
2605
reserved
Germani, A., Manes, C., Palumbo, P. (2002). Filtering of switching systems via a singular minimax approach. In Proceedings of the IEEE Conference on Decision and Control (pp.2600-2605). IEEE Institute of Electrical and Electronics Engineers [10.1109/CDC.2002.1184230].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/246658
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