Identification of Wiener Model Based on Improved Differential Evolution (SADE) Algorithm

Authors

Xiaoping Xu, 1. School of sciences, Xi'an University of Technology, Xi'an 710054;;
Bai Bo, 1. School of sciences, Xi'an University of Technology, Xi'an 710054;;
Fucai Qian, 2. School of Automation and information Engineering, Xi'an University of Technology, Xi'an 710048;

Abstract

Abstract: To identify the parameters of nonlinear Wiener model, a new identification method was put forward based on a SADE algorithm. Its basic idea is as follows: the Sigmoid function and adaptive mutation operator were adopted to improve the mutation operation part of the basic differential evolution algorithm, accordingly, the disadvantages of the basic differential evolution algorithm, such as premature convergence, instability, etc, were effectively overcome. The proposed algorithm was used to parameter identification problem of Wiener model; moreover, the accuracy of identification was well improved. In the numerical simulation, compared with other relevant existing algorithms, simulation results show that the proposed method is rational and effective.

Recommended Citation

Xu, Xiaoping; Bo, Bai; and Qian, Fucai (2020) "Identification of Wiener Model Based on Improved Differential Evolution (SADE) Algorithm," Journal of System Simulation: Vol. 28: Iss. 1, Article 20.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss1/20

First Page

147

Revised Date

2015-01-27

DOI Link

https://doi.org/

Last Page

153

CLC

TP391.9

Recommended Citation

Xu Xiaoping, Bai Bo, Qian Fucai. Identification of Wiener Model Based on Improved Differential Evolution (SADE) Algorithm[J]. Journal of System Simulation, 2016, 28(1): 147-153.