Gradient Approach to Curve Fitting with Incomplete Data

Karol Koniuszewski , Paweł Domański


The paper deals with the problem of nonlinear curve fitting in situation of incomplete data. Research was motivated by the industrial identification of Hammerstein models. It was noticed that for the model robustness and quality the fitness of the static nonlinear element is much more crucial then efficiency of dynamic operation of linear part. Industrial data are incomplete, i.e. they do not cover the whole process domain. It is due to the operation around selected steady states, close loop operation, extensive manual model use, etc. In case of multi-regional approach we often get regions with no data. Proposed methodology is addressing that issue. Included results are for both simulation and real industrial case.
Author Karol Koniuszewski (FEIT / AK)
Karol Koniuszewski,,
- The Institute of Control and Computation Engineering
, Paweł Domański (FEIT / AK)
Paweł Domański,,
- The Institute of Control and Computation Engineering
Publication size in sheets0.5
Book Szewczyk Roman, Kaliczyńska Małgorzata, Zieliński Cezary: Challenges in Automation, Robotics and Measurement Techniques. Proceedings of AUTOMATION-2016, March 2-4, 2016, Warsaw, Poland, Advances in Intelligent Systems and Computing, vol. 440, 2016, Springer International Publishing, ISBN 978-3-319-29356-1, [978-3-319-29357-8], 919 p., DOI:10.1007/978-3-319-29357-8
ProjectDevelopment of methodology of control, decision support and production management. Project leader: Zieliński Cezary, , Phone: 5102, start date 19-05-2015, end date 31-12-2016, 504/02233/1031, Completed
WEiTI Działalność statutowa
Languageen angielski
koniuszewski idoman Gradient autom2016.pdf 1.36 MB
Score (nominal)15
Score sourceconferenceIndex
ScoreMinisterial score = 15.0, 02-02-2020, BookChapterSeriesAndMatConfByConferenceseries
Ministerial score (2013-2016) = 15.0, 02-02-2020, BookChapterSeriesAndMatConfByConferenceseries
Publication indicators Scopus Citations = 1; WoS Citations = 1
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