电工技术学报2017，Vol.32Issue(3)：56-64,9.
一种多时间尺度线性系统模型降阶的误差预测方法
An Error Prediction Method of Model Order Reduction for Multi-Time Scale Linear System
摘要
Abstract
The conventional methods of order reduction model for linear system cannot predict the time domain error of dynamic behaviors of state variables between the original and reduced models,so the reduced models derived by conventional methods maybe not suitable for analyzing the system performances because of the large variation between the reduction model and origin model.To solve this problem,this paper has proposed a L2 norm-based error prediction method for error prediction which is based on the conventional singular perturbation model order reduction method.The relative error calculation formula of the dynamic characteristic of the system state variable is deduced which ignore the variation caused by fast dynamic and fixed slow dynamic reduction.Then,the multi-time scale mathematical models of an AC system powered by one generator and a model of a DC system powered by three generators are built.They are reduced and the consequent errors are predicted.The simulation results demonstrate the effectiveness and accuracy of the proposed method.关键词
线性系统/多时间尺度/模型降阶/误差预测/奇异摄动理论Key words
Linear system/multi-time scale/model order reduction/error prediction/singular perturbation theory分类
信息技术与安全科学引用本文复制引用
康军,马凡,胡健,孙文,熊又星..一种多时间尺度线性系统模型降阶的误差预测方法[J].电工技术学报,2017,32(3):56-64,9.基金项目
国家自然科学基金项目(51377167)和国家重点基础研究发展计划(973计划)(2012CB215103)资助. （51377167）
