Closed-loop parametric identification of DC-DC converter

Author:

Padhee Subhransu1ORCID,Pati Umesh Chandra1,Mahapatra Kamalakanta1

Affiliation:

1. Department of Electronics and Communication Engineering, National Institute of Technology, Rourkela, India

Abstract

This study provides a step-by-step analysis of closed-loop parametric system identification for DC-DC buck converter. In closed-loop parametric identification, input–output experimental data are used to estimate the transfer function coefficients of DC-DC buck converter. For system identification purpose, a high-frequency perturbation signal is injected in to the closed-loop system which acts as an input signal for identification experiment. Different input–output models such as Auto-Regressive eXogenous, Auto-Regressive Moving Average with eXogenous, output error, and Box–Jenkins are used to model the converter structure and prediction error method is used to estimate the parameters. Model validation schemes are used to validate the estimated model. Simulation and experimental analysis have been provided to validate the results obtained.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Control and Systems Engineering

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Data‐driven Buck converter model identification method with missing outputs;IET Control Theory & Applications;2024-08-13

2. Implementation of unidirectional control mechanism for DC-DC converters;Journal of Information and Optimization Sciences;2024

3. Full-parameter constrained parsimonious subspace identification with steady-state information for DC–DC converters;Control Theory and Technology;2023-07-10

4. LPV Modeling of Boost Converter and Gain Scheduling MPC Control;2019 IEEE 15th Brazilian Power Electronics Conference and 5th IEEE Southern Power Electronics Conference (COBEP/SPEC);2019-12

5. Blackbox Polytopic Model With Dynamic Weighting Functions for DC-DC Converters;IEEE Access;2019

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