Paper
26 July 2004 Adaptive generalized predictive control combined with a least-squares lattice filter
Suk-Min Moon, Robert L. Clark, Daniel G. Cole
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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.
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Suk-Min Moon, Robert L. Clark, and Daniel G. Cole "Adaptive generalized predictive control combined with a least-squares lattice filter", Proc. SPIE 5383, Smart Structures and Materials 2004: Modeling, Signal Processing, and Control, (26 July 2004); https://doi.org/10.1117/12.538493
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KEYWORDS
Digital filtering

System identification

Acoustics

Filtering (signal processing)

Control systems

Adaptive control

Algorithm development

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