Full-parameter constrained parsimonious subspace identification with steady-state information for DC-DC converters
Jie Hou1
Zhen Yang1
Taifu Li2
Huiming Wang1
Jincheng Jiang1
Xiaolei Chen1
1.College of Automation,Chongqing University of Posts and Telecommunications,Chongqing 400065,China2.School of Electrical and Information Engineering,Chongqing University of Science and Technology,Chongqing 401331,China
摘要：A full-parameter constrained parsimonious subspace identification method that incorporates the steady-state a priori infor-mation of the system is proposed to model the DC-DC converters.A parsimonious model with fewer parameters is used to represent the system,and then an optimal weighted methods is used to estimate the system parameters matrices by taking into account both dynamical data and steady-state data.Compared with traditional data-driven methods for DC-DC convert-ers,the subspace-based method can simultaneously estimate model structure and parameter with appropriate computational complexity.Moreover,compared with the traditional full-parameter constrained subspace approach,the proposed algorithm can accurately estimate the system parameters with a smaller variance.The experimental results on a DC-DC synchronous buck converter verify the effectiveness and superiority of the proposed method.
机标关键词：identificationinformationwithconstrainedconvertersfull-parameterparsimonioussteady-state
论文发表日期：2024-05-05
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：11( 173-183 )
英文信息