Application Research on Developed Chaos-Wasp Colony Algorithm Used in Suspension-Parameter Optimization

Haitao Zhang, Hong Gao, Xinlin Hun, Aiguo Wang

2018

Abstract

Aimed at parameters matching of automobile suspension system, this paper was presented an approach to optimize suspension system parameters based on developed chaos-wasp colony algorithm . Firstly, chaos factors were initialized through cube map; Balance of local and global searching of artificial wasp colony algorithm was realized on the basis of inertia weight of exponential decline; Early maturing was judged by fitness variance values. Secondly, dynamic models of quarter suspension were established and Matlab/Simulink software was employed to conduct the simulation experiments by taking integral white noise as road surface input. Results of simulation experiments indicated that developed chaos-wasp colony algorithm was better than tradition algorithms and normal artificial wasp colony algorithm.

Paper Citation

in Harvard Style

Zhang H., Gao H., Hun X. and Wang A. (2018). Application Research on Developed Chaos-Wasp Colony Algorithm Used in Suspension-Parameter Optimization .In 3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT, ISBN 978-989-758-312-4, pages 150-155. DOI: 10.5220/0006966701500155

in Bibtex Style

@conference{icectt18,
author={Haitao Zhang and Hong Gao and Xinlin Hun and Aiguo Wang},
title={Application Research on Developed Chaos-Wasp Colony Algorithm Used in Suspension-Parameter Optimization },
booktitle={3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT,},
year={2018},
pages={150-155},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006966701500155},
isbn={978-989-758-312-4},
}

in EndNote Style

TY - CONF

JO - 3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT,
TI - Application Research on Developed Chaos-Wasp Colony Algorithm Used in Suspension-Parameter Optimization
SN - 978-989-758-312-4
AU - Zhang H.
AU - Gao H.
AU - Hun X.
AU - Wang A.
PY - 2018
SP - 150
EP - 155
DO - 10.5220/0006966701500155