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Proceedings Paper

Optimal sensing strategy for adaptive control of optical systems
Author(s): Suk-Min Moon; Leslie P. Fowler; Robert L. Clark
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Paper Abstract

Optical jitter degrades the pointing and imaging performance of precision optical systems. When a correlated measurement of the disturbance is available, improved control performance can be attained. In this research, an adaptive optimal sensing strategy for optical systems is proposed. An array of reference sensors makes it possible to estimate the disturbance and model the disturbance-to-reference paths. The least-square algorithm is applied for the disturbance model estimation. A sensor scoring algorithm is then used to select an optimal disturbance reference from the available reference signals. The optimal disturbance reference is comprised of sensors which are well correlated with the disturbance. This disturbance reference is then fed forward and used in an adaptive generalized predictive control design. This adaptive control approach is advantageous in the presence of time-varying or uncertain disturbances. The proposed technique is applied to an experimental test bed in which an array of accelerometer sensors measures the structural vibration of optical elements. Reduction of the structural vibration of optical components is attained using a fast steering mirror which results in a reduction of the corresponding jitter. Performance using optimally selected disturbance reference is shown to be better than for system in which a disturbance reference signal is chosen to be the sensor with the lowest score.

Paper Details

Date Published: 19 May 2005
PDF: 10 pages
Proc. SPIE 5757, Smart Structures and Materials 2005: Modeling, Signal Processing, and Control, (19 May 2005); doi: 10.1117/12.605544
Show Author Affiliations
Suk-Min Moon, Duke Univ. (United States)
Leslie P. Fowler, CSA Engineering, Inc. (United States)
Robert L. Clark, Duke Univ. (United States)


Published in SPIE Proceedings Vol. 5757:
Smart Structures and Materials 2005: Modeling, Signal Processing, and Control
Ralph C. Smith, Editor(s)

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