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Log-concave Observers

In English

Författare

Summary, in English

The Kalman filter is the optimal state

observer in the case of linear dynamics and Gaussian noise.

In this paper, the observer problem

is studied when process noise and measurements

are generalized from Gaussian to log-concave. This

generalization is of interest for example in the case

where observations only give information that the

signal is in a given range. It turns out that the optimal

observer preserves log-concavity. The concept

of strong log-concavity is introduced and two new

theorems are derived to compute upper bounds on

optimal observer covariance in the log-concave case.

The theory is applied to a system with threshold

based measurements, which are log-concave but far

from Gaussian.

Publiceringsår

2006

Språk

Engelska

Publikation/Tidskrift/Serie

17th International Symposium on Mathematical Theory of Networks and Systems, 2006

Dokumenttyp

Konferensbidrag

Ämne

  • Control Engineering

Nyckelord

  • Event based control
  • Observers
  • Log-concave functions

Conference name

17th International Symposium on Mathematical Theory of Networks and Systems, 2006

Conference date

2006-07-24 - 2006-07-28

Conference place

Kyoto, Japan

Status

Published