Share Email Print
cover

Proceedings Paper

Adaptive generalized predictive control combined with a least-squares lattice filter
Author(s): Suk-Min Moon; Robert L. Clark; Daniel G. Cole
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

The generalized predictive control (GPC) concept is extended to an adaptive control algorithm by combining with a least-squares lattice filter. A least-squares lattice (LSL) filter, another class of exact least-squares filters, has a modular structure that is advantageous in the application of on-line system identification. The modular structure passes system information from lower order to higher order in a wave motion. The adaptive GPC algorithm combined with a LSL filter is implemented for a real-time computer algorithm and its performance is experimentally demonstrated to a structural system and an acoustic enclosure. In addition, the adaptive GPC algorithm with a LSL filter is compared with the adaptive GPC algorithm combined with a classical recursive least-squares (RLS) filter in terms of complexity, computational cost and other on-line application concerns. The average task execution time (TET) --- the measured processing time to run the algorithm during each sample interval --- is reduced by over 35 \% by using the adaptive GPC algorithm with a LSL filter.

Paper Details

Date Published: 26 July 2004
PDF: 11 pages
Proc. SPIE 5383, Smart Structures and Materials 2004: Modeling, Signal Processing, and Control, (26 July 2004); doi: 10.1117/12.538493
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)

© SPIE. Terms of Use
Back to Top