Identification of Nonlinear Dynamic Systems Structured by Expanded Wiener Model

被引:0
作者
Shanshiashvili, Besarion [1 ]
Avazneli, Beka [1 ]
机构
[1] Georgian Tech Univ, GE-0160 Tbilisi, Georgia
来源
ADVANCES IN PRODUCTION MANAGEMENT SYSTEMS: ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE AND RESILIENT PRODUCTION SYSTEMS, APMS 2021, PT I | 2021年 / 630卷
关键词
Identification; Nonlinear system; Model; Parameter; Dynamic;
D O I
10.1007/978-3-030-85874-2_58
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A problem of parameter identification of nonlinear manufacturing systems represented by expanded Wiener model, linear elements of which are described by the ordinary differential equation, in the frequency domain is considered. Method of parameter identification in steady state based on the observation of the system's input and output variables at the input harmonic influences is proposed. The solution of the problem of parameter identification is reduced to the solution of the systems of algebraic equations by using the Fourier approximation. The parameters estimations are received by the least squares method. Reliability of the received results, at the identification of the nonlinear systems in industrial conditions at the presence of noise, depends on the accuracy of the measurement of system input and output signals and mathematical processing of the experimental data at the approximation. The parameter identification method is investigated by means of both the theoretical analysis and the computer modelling.
引用
收藏
页码:546 / 554
页数:9
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