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Multi‐rate observer design for process monitoring using asynchronous inter‐sample output predictions
Author(s) -
Ling Chen,
Kravaris Costas
Publication year - 2017
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.15707
Subject(s) - observer (physics) , control theory (sociology) , asynchronous communication , state observer , rate of convergence , sampling (signal processing) , convergence (economics) , mathematics , computer science , sample (material) , stability (learning theory) , mathematical optimization , chemistry , detector , artificial intelligence , nonlinear system , chromatography , physics , computer network , telecommunications , channel (broadcasting) , control (management) , quantum mechanics , economics , economic growth , machine learning
In this article, the problem of observer design in linear multi‐output systems with asynchronous sampling is addressed. The proposed multi‐rate observer is based on a continuous‐time Luenberger observer design coupled with an inter‐sample predictor for each sampled measurement, which generates an estimate of the output in between consecutive measurements. The sampling times are not necessarily uniformly spaced, but there exists a maximum sampling period among all the sensors. Sufficient and explicit conditions are derived to guarantee exponential stability of the multi‐rate observer. The proposed framework of multi‐rate observer design is examined through a mathematical example and a gas‐phase polyethylene reactor. In the latter case, the amount of active catalyst sites is estimated, with a convergence rate that is comparable to the case of continuous measurements. © 2017 American Institute of Chemical Engineers AIChE J , 63: 3384–3394, 2017