State-Space Model and Kalman Filter Gain Identification by a Kalman Filter of a Kalman Filter-Reference-Cited by-同舟云学术

State-Space Model and Kalman Filter Gain Identification by a Kalman Filter of a Kalman Filter

Published:2017-11-08 Issue:3 Volume:140 Page:
ISSN:0022-0434
Container-title:Journal of Dynamic Systems, Measurement, and Control
language:en
Short-container-title:

Author:

Phan Minh Q.¹,Vicario Francesco²,Longman Richard W.³,Betti Raimondo⁴

Affiliation:

1. Thayer School of Engineering, Dartmouth College, Hanover, NH 03755 e-mail:

2. Department of Acute Care Solutions, Philips Research, Cambridge, MA 02141 e-mail:

3. Department of Mechanical Engineering, Columbia University, New York, NY 10027 e-mail:

4. Department of Civil Engineering and Engineering Mechanics, Columbia University, New York, NY 10027 e-mail:

Abstract

This paper describes an algorithm that identifies a state-space model and an associated steady-state Kalman filter gain from noise-corrupted input–output data. The model structure involves two Kalman filters where a second Kalman filter accounts for the error in the estimated residual of the first Kalman filter. Both Kalman filter gains and the system state-space model are identified simultaneously. Knowledge of the noise covariances is not required.

Publisher

ASME International

Subject

Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering

Link

http://asmedigitalcollection.asme.org/dynamicsystems/article-pdf/doi/10.1115/1.4037778/6125748/ds_140_03_030902.pdf

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