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http://dx.doi.org/10.5302/J.ICROS.2011.17.12.1183

An Optimal FIR Filter for Discrete Time-varying State Space Models  

Kwon, Bo-Kyu (Kangwon National University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.17, no.12, 2011 , pp. 1183-1187 More about this Journal
Abstract
In this paper, an optimal FIR (Finite-Impulse-Response) filter is proposed for discrete time-varying state-space models. The proposed filter estimates the current state using measured output samples on the recent time horizon so that the variance of the estimation error is minimized. It is designed to be linear, unbiased, with an FIR structure, and is independent of any state information. Due to its FIR structure, the proposed filter is believed to be robust for modeling uncertainty or numerical errors than other IIR filters, such as the Kalman filter. For a general system with system and measurement noise, the proposed filter is derived without any artificial assumptions such as the nonsingular assumption of the system matrix A and any infinite covariance of the initial state. A numerical example show that the proposed FIR filter has better performance than the Kalman filter based on the IIR (Infinite- Impulse-Response) structure when modeling uncertainties exist.
Keywords
optimal state estimation; FIR (Finite Impulse Response); time-varying system; Kalman filter; receding horizon;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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