A computationally efficient EIV models identification method using the v-gap metric
作者单位：Tianjin Key Laboratory of Information Sensing and Intelligent ControlSchool of Automation and Electrical EngineeringTianjin University of Technology and Education
会议名称：《第37届中国控制会议》
会议日期：2018年
学科分类：0711[理学-系统科学] 07[理学] 08[工学] 070105[理学-运筹学与控制论] 081101[工学-控制理论与控制工程] 0701[理学-数学] 071101[理学-系统理论] 0811[工学-控制科学与工程]
基 金：supported in part by the Tianjin Key Program of Natural Science Foundation of China under Grant No.14JCZDJC36300 the Tianjin University of Technology and Education Funded Projects under Grant Nos.RC14–48 and RC17–01
关 键 词：V-gap Metric Computational Efficiency Nyquist Winding Condition Interior-point Method
摘 要：A frequency-domain identification method with higher computational efficiency is proposed in this paper. The minimum v-gap metric between the disturbing model and the estimation model is used as an objective function. By change the constraints way for the Nyquist winding condition, the computational efficiency is much higher than the way of previous pointto-point constraint. The proposed method is applicable to not only the errors-in-variables models but also the conventional output noise corrupted models. Parameter optimization of the estimation model employs the interior-point method, and thus the computational efficiency is greatly improved in comparison with the linear matrix inequalities based identification method. The length of experimental data is typically larger than the order of the estimation model, so the calculational efficiency is improved ***, a simulation experiment is given to demonstrate that the proposed identification method is computationally efficient.