Open AccessSIMULATION OF DC-DC CONVERTER SYMBOLIC DYNAMICS: DETECTION AND IDENTIFICATION OF BIFURCATION TYPES
Author(s) -
Abdelaziz Hamzaoui,
Pavel Ustinov,
A.P. Sholonik,
Yury Kolokolov
Publication year - 2014
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.3.2.297
Subject(s) - symbolic dynamics , bifurcation , identification (biology) , transformation (genetics) , computer science , process (computing) , symbolic data analysis , the symbolic , dynamics (music) , type (biology) , control theory (sociology) , mathematics , theoretical computer science , artificial intelligence , nonlinear system , physics , pure mathematics , psychoanalysis , ecology , chemistry , acoustics , biology , operating system , psychology , biochemistry , control (management) , quantum mechanics , botany , gene
In this paper continuous-time model to discrete-time symbolic model transformation for an algorithmization of the DC-DC buck converter dynamics investigation process is derived. The proposed concept of symbolic index allows evaluate quantitatively the symbolic model change and makes possible the “nonsmooth” bifurcations revealing. The numerical simulation that had been carried out verifies utilizing efficiency of symbolic modeling both as for possible bifurcation pattern forecasting, as for bifurcation type identification.