模式识别与人工智能
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  2019, Vol. 32 Issue (6): 524-530    DOI: 10.16451/j.cnki.issn1003-6059.201906005
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Identification of Low-Order System with Time Delay Based on Particle Swarm Optimization
LI Minhua1, BAI Meng1, LÜ Yingjun1
1.Department of Electrical Engineering and Information Technology, Shandong University of Science and Technology, Jinan 250031

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Abstract  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.
Key wordsLow-Order System with Time Delay      Parameter Estimation      Step Response      Integral Equation      Particle Swarm Optimization     
Received: 05 March 2019     
ZTFLH: TP 271  
  TP 391  
About author:: (LI Minhua(Corresponding author), Ph.D., associate professor. Her research interests include image processing, intelligent computing and pattern recognition.)(BAI Meng, Ph.D., associate professor. His research interests include system identification, image processing and intelligent computing.)(LÜ Yingjun, master, associate professor. His research interests include design of embedded control systems.)
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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201906005      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2019/V32/I6/524
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