Open Access
Translator Disclaimer
2013 A Multilayer Feed Forward Small-World Neural Network Controller and Its Application on Electrohydraulic Actuation System
Xiaohu Li, Feng Xu, Jinhua Zhang, Sunan Wang
J. Appl. Math. 2013(SI16): 1-8 (2013). DOI: 10.1155/2013/872790

Abstract

Being difficult to attain the precise mathematical models, traditional control methods such as proportional integral (PI) and proportional integral differentiation (PID) cannot meet the demands for real time and robustness when applied in some nonlinear systems. The neural network controller is a good replacement to overcome these shortcomings. However, the performance of neural network controller is directly determined by neural network model. In this paper, a new neural network model is constructed with a structure topology between the regular and random connection modes based on complex network, which simulates the brain neural network as far as possible, to design a better neural network controller. Then, a new controller is designed under small-world neural network model and is investigated in both linear and nonlinear systems control. The simulation results show that the new controller basing on small-world network model can improve the control precision by 30% in the case of system with random disturbance. Besides the good performance of the new controller in tracking square wave signals, which is demonstrated by the experiment results of direct drive electro-hydraulic actuation position control system, it works well on anti-interference performance.

Citation

Download Citation

Xiaohu Li. Feng Xu. Jinhua Zhang. Sunan Wang. "A Multilayer Feed Forward Small-World Neural Network Controller and Its Application on Electrohydraulic Actuation System." J. Appl. Math. 2013 (SI16) 1 - 8, 2013. https://doi.org/10.1155/2013/872790

Information

Published: 2013
First available in Project Euclid: 14 March 2014

zbMATH: 1271.92004
Digital Object Identifier: 10.1155/2013/872790

Rights: Copyright © 2013 Hindawi

JOURNAL ARTICLE
8 PAGES


SHARE
Vol.2013 • No. SI16 • 2013
Back to Top