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Proceedings Paper

Adaptive state estimation for control of flexible structures
Author(s): Chung-Wen Chen; Jen-Kuang Huang
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Paper Abstract

This paper proposes a new approach of obtaining adaptive state estimation of a system in the presence of unknown system disturbances and measurement noise. In the beginning, a non-optimal Kalman filter with arbitrary initial guess for the process and measurement noises is implemented. At the same time, an adaptive transversal predictor (ATP) based on the recursive least-squares (ilLS) algorithm is used to yield optimal one- to p- stepahead output predictions using the previous input/output data. Referring to these optimal predictions the Kalman filter gain is updated and the performance of the state estimation is thus improved. If forgetting factor is implemented in the recursive least-squares algorithm, this method is also capable of dealing with the situation when the noise statistics are slowly time-varying. This feature makes this new approach especially suitable for the control of flexible structures. A numerical example demonstrates the feasibility of this real time adaptive state estimation method.

Paper Details

Date Published: 1 October 1990
PDF: 11 pages
Proc. SPIE 1303, Advances in Optical Structure Systems, (1 October 1990); doi: 10.1117/12.21508
Show Author Affiliations
Chung-Wen Chen, Old Dominion Univ. (United States)
Jen-Kuang Huang, Old Dominion Univ. (United States)

Published in SPIE Proceedings Vol. 1303:
Advances in Optical Structure Systems
John A. Breakwell; Victor L. Genberg; Gary C. Krumweide, Editor(s)

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