Identification of low-order system with time delay based on particle swarm optimization

被引：0
|
作者：
Li M. [1 ]
Bai M. [1 ]
Lü Y. [1 ]
机构：
[1] Department of Electrical Engineering and Information Technology, Shandong University of Science and Technology, Jinan
来源：
Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence | 2019年 / 32卷 / 06期
关键词：
Integral Equation; Low-Order System with Time Delay; Parameter Estimation; Particle Swarm Optimization; Step Response;
D O I：
10.16451/j.cnki.issn1003-6059.201906005
中图分类号：
学科分类号：
摘要：
To solve the problem of step response identification of low-order system with time delay, a parameter estimation method based on particle swarm optimization is proposed. The method consists of the calculation of initial parameters and the parameter estimation. Firstly, an integral equation approach is utilized to estimate the initial parameters of the system with time delay. By setting an initial parameter estimation error, the parameter range of the time-delay system can be determined. Next, the particle swarm optimization algorithm is employed to reduce the influence of the measurement noise on parameter estimation. Simulation experiments are conducted to verify the performance of the proposed method in identifying the parameters of low-order system with time delay under different noisy conditions. Experimental results demonstrate that the proposed method possesses good parameter estimation precision and strong anti-noise ability and it effectively solves the step response identification problem of low-order system with time delay. © 2019, Science Press. All right reserved.
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页码：524 / 530
页数：6
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