Robust numerical approach to steady-state calibration of mean-value models

A numerically robust approach to steady-state calibration of nonlinear dynamic models is presented. The approach is based on explicit formulation of the constraints on validity of internal model signals by set of inequalities. The constrained optimization with feasible iterates guarantees that the m...

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Bibliographic Details
Published inControl engineering practice Vol. 61; pp. 186 - 197
Main Authors Beňo, Radek, Pachner, Daniel, Havlena, Vladimír
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.04.2017
Subjects
Engine modeling
Internal combustion engines
Nonlinear systems
Parameter identification
System identification
System identification
Engine modeling
Parameter identification
Nonlinear systems
Internal combustion engines
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Summary:A numerically robust approach to steady-state calibration of nonlinear dynamic models is presented. The approach is based on explicit formulation of the constraints on validity of internal model signals by set of inequalities. The constrained optimization with feasible iterates guarantees that the model will never be evaluated with invalid internal signals. This overcomes numerical difficulties often encountered when dealing with highly nonlinear models. Because the approach uses a large number of slack variables, distributed least squares algorithm is proposed. The robustness of this approach is demonstrated on a steady-state calibration of turbocharged diesel engine model starting from grossly inaccurate initial estimates.
ISSN:0967-0661
1873-6939
DOI:10.1016/j.conengprac.2016.04.009