%0 Journal Article
%T Adjustment method of parameters intended for first-principle models
%A P. Czop
%A G. Kost
%A D. SŁżawik
%A G. WszoŁżek
%J Journal of Achievements in Materials and Manufacturing Engineering
%D 2012
%I World Academy of Materials and Manufacturing Engineering
%X Purpose: This paper demonstrates a process of estimation phenomenological parameters of a first-principle nonlinear model based on the hydraulic damper system.Design/methodology/approach: First-principle (FP) models are formulated using a system of continuous ordinary differential equations capturing usually nonlinear relations among variables of the model. The considering model applies three categories of parameters: geometrical, physical and phenomenological. Geometrical and physical parameters are deduced from construction or operational documentation. The phenomenological parameters are the adjustable ones, which are estimated or adjusted based on their roughly known values, e.g. friction/damping coefficients. Findings: A phenomenological parameter, friction coefficient, was successfully estimated based on the experimental data. The error between the model response and experimental data is not greater than 10%.Research limitations/implications: Adjusting a model to data is, in most cases, a non-convex optimization problem and the criterion function may have several local minima. This is a case when multiple parameters are simultaneously estimated. Practical implications: First-principle models are fundamental tools for understanding, optimizing, designing, and diagnosing technical systems since they are updatable using operational measurements.Originality/value: First-principle models are frequently adjusted by trial-and-error, which can lead to nonoptimal results. In order to avoid deficiencies of the trial-and-error approach, a formalized mathematical method using optimization techniques to minimize the error criterion, and find optimal values of tunable model parameters, was proposed and demonstrated in this work.
%K First principle model
%K Data driven model
%K Hydraulic damper
%U http://journalamme.org/papers_vol55_2/58234.pdf