Chaotic Gravitational Search Iterative Identification for Wiener Systems

Authors

Shanling Xu, Nantong University, Nantong 226019, China;
Junhong Li, Nantong University, Nantong 226019, China;
Mengru Liu, Nantong University, Nantong 226019, China;
Hua Liang, Nantong University, Nantong 226019, China;

Abstract

Abstract: The Wiener nonlinear system is composed of a dynamic linear subsystem and a series of nonlinear static subsystems, which is widely used in the fields of automatic control, chemical engineering, electrical and other fields. Considering the identification of the Wiener Output Error Autoregressive (Wiener OEAR) system, a chaotic gravitational search iterative identification algorithm is proposed, in which the chaotic optimization mechanism is introduced into the gravitational search algorithm to estimate the unknown parameters of the Wiener OEAR system and the convergence is proved. In order to show the effectiveness of the proposed identification algorithm, the gravitational search algorithm and gradient iterative algorithm are used to identify the same system, and a simulation example and an application example are given. The simulation results show that the three algorithms can effectively identify the Wiener OEAR system, and the chaotic gravitational search iterative identification is better than the gravitational search algorithm and gradient iterative algorithm in the accuracy of parameter estimation.

Recommended Citation

Xu, Shanling; Li, Junhong; Liu, Mengru; and Liang, Hua (2021) "Chaotic Gravitational Search Iterative Identification for Wiener Systems," Journal of System Simulation: Vol. 33: Iss. 9, Article 15.
DOI: 10.16182/j.issn1004731x.joss.20-0352
Available at: https://dc-china-simulation.researchcommons.org/journal/vol33/iss9/15

First Page

2138

Revised Date

2020-09-12

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.20-0352

Last Page

2146

CLC

TP273

Recommended Citation

Xu Shanling, Li Junhong, Liu Mengru, Hua Liang. Chaotic Gravitational Search Iterative Identification for Wiener Systems[J]. Journal of System Simulation, 2021, 33(9): 2138-2146.

Corresponding Author

Junhong Li,

DOI

10.16182/j.issn1004731x.joss.20-0352