A receding horizon Kalman FIR filter for discrete time-invariant systems

A receding horizon Kalman FIR filter is presented that combines the Kalman filter and the receding horizon strategy when the horizon initial state is assumed to be unknown. The suggested filter is a FIR filter form which has many good inherent properties. It can always be defined irrespective of sin...

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Bibliographic Details
Published in:IEEE transactions on automatic control 1999-09, Vol.44 (9), p.1787-1791
Main Authors: Kwon, Wook H, Kim, Pyung S, Park, Poo Gyeon
Format: Article
Language:English
Subjects:
Automatic control
Control systems
Feedback control
Finite impulse response filter
FIR filters
Horizon
IIR filters
Initial conditions
Integral equations
Iterative methods
Kalman filters
Robustness
Singularities
State estimation
Stochastic systems
Strategy
Time measurement
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Summary:A receding horizon Kalman FIR filter is presented that combines the Kalman filter and the receding horizon strategy when the horizon initial state is assumed to be unknown. The suggested filter is a FIR filter form which has many good inherent properties. It can always be defined irrespective of singularity problems caused by unknown information about the horizon initial state. The suggested filter can be represented in either an iterative form or a standard FIR form. It is also shown that the suggested filter possesses the unbiasedness property and the remarkable deadbeat property irrespective of any horizon initial condition. The validity of the suggested filter is illustrated by numerical examples.
ISSN:0018-9286
1558-2523
DOI:10.1109/9.788554