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Proceedings Paper

Recursive generalized predictive control for systems with disturbance measurements
Author(s): Suk-Min Moon; Robert L. Clark; Daniel G. Cole
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Paper Abstract

The recursive generalized predictive control (RGPC), which combines the process of system identification using recursive least-squares (RLS) algorithm and the process of generalized predictive feedback control design, has been presented and successfully implemented on testbeds. In this research, the RGPC algorithm is extended when the disturbance measurement signal is available for feedforward control. First, the feedback and feedforward RGPC design algorithm is presented when the disturbance is stochastic or random, and is applied to an optical jitter suppression testbed. Second, the feedback and feedforward algorithm is further extended when the disturbance is deterministic or periodic. The deterministic disturbance measurement is used to estimate the future disturbance values that are then used in the control design to enhance the performance. The RGPC with future disturbance estimation algorithm is applied to a structural system and an acoustic system.

Paper Details

Date Published: 26 July 2004
PDF: 12 pages
Proc. SPIE 5383, Smart Structures and Materials 2004: Modeling, Signal Processing, and Control, (26 July 2004); doi: 10.1117/12.538095
Show Author Affiliations
Suk-Min Moon, Duke Univ. (United States)
Robert L. Clark, Duke Univ. (United States)
Daniel G. Cole, Duke Univ. (United States)


Published in SPIE Proceedings Vol. 5383:
Smart Structures and Materials 2004: Modeling, Signal Processing, and Control
Ralph C. Smith, Editor(s)

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