Input design for on-line system identification of a human respiratory system

An efficient implementation of input design for on-line system identification is presented. The optimal input is calculated recursively based on the imminent available information content in the inverse correlation matrix of the data. The new input is computed one step ahead of time with a predictiv...

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Bibliographic Details
Main Author: Schoen, M.P.
Format: Conference Proceeding
Language:English
Subjects:
Applied sciences
Computer science
control theory
systems
Control system synthesis
Control theory. Systems
Correlation methods
Exact sciences and technology
Gaussian noise
Humans
Information filtering
Information filters
Mathematical model
Mathematical models
Matrix algebra
Online systems
Parameter estimation
Recursive estimation
Respiratory system
Signal to noise ratio
System identification
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Description
Summary:An efficient implementation of input design for on-line system identification is presented. The optimal input is calculated recursively based on the imminent available information content in the inverse correlation matrix of the data. The new input is computed one step ahead of time with a predictive filter so that it will increase the information content in the inverse correlation matrix. A numerical example is provided which is based on a human respiratory system.
ISSN:0743-1619
2378-5861
DOI:10.1109/ACC.2002.1024496