AUTOMATION OF OPTIMAL IDENTIFICATION OF DYNAMIC ELEMENT TRANSFER FUNCTIONS IN COMPLEX TECHNICAL OBJECTS BASED ON ACCELERATION CURVES

Abstract

Objectives. The aim of present paper is to minimise the errors in the approximation of experimentally obtained acceleration curves.Methods. Based on the features and disadvantages of the well-known Simoyu method for calculating transfer functions on the basis of acceleration curves, a modified version of the method is developed using the MathLab and MathCad software. This is based on minimising the sum of the squares of the experimental point deviations from the solution of the differential equation at the same points.Results. Methods for the implementation of parametric identification are analysed and the Simoyu method is chosen as the most effective. On the basis of the analysis of its advantages and disadvantages, a modified method is proposed that allows the structure and parameters of the transfer function to be identified according to the experimental acceleration curve, as well as the choice of optimal numerical values of those parameters obtained for minimising errors in the approximation of the experimentally obtained acceleration curves.Conclusion. The problem of optimal control over a complex technical facility was solved. On the basis of the modified Simoyu method, an algorithm for the automated selection of the optimal shape and calculation of transfer function parameters of dynamic elements of complex technical objects according to the acceleration curves in the impact channels was developed. This has allowed the calculation efficiency of the dynamic characteristics of control objects to be increased by minimising the approximation errors. The efficiency of the proposed calculation method is shown. Its simplicity makes it possible to apply to practical calculations, especially for use in the design of complex technical objects within the framework of the computer aided design system. The proposed method makes it possible to increase the accuracy of the approximation by at least 20%, which is an important advantage for its practical use.

Keywords

• transfer function
• mathematical model
• approximation
• optimisation
• identification