Stablity, convergence of balloon Particle Swarm Optimizer and its application on vechile modelling

Feng Pan; Jie Chen; Ming Gang Gan; Tao Cai; Xu Yan Tu

doi:10.3182/20050703-6-cz-1902.00933

Stablity, convergence of balloon Particle Swarm Optimizer and its application on vechile modelling

Feng Pan^*, Jie Chen, Ming Gang Gan, Tao Cai, Xu Yan Tu

^*Corresponding author for this work

School of Automation

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Particle Swarm Optimizer, PSO, exhibits good performance for optimization problem, although, PSO can not guarantee convergence of a global minimum, even a local minimum. However, there are some adjustable parameters and restrictive conditions which can affect performance of the algorithm. in this paper, a new adaptive PSO algorithm-Balloon PSO (BPSO) is proposed. The sufficient conditions for asymptotic stability of acceleration factor and inertia weight are deduced. Furthermore it is proved that BPSO is a global research algorithm. Simulation results of power spectral density (PSD) of vehicle vibratory signal estimation show the good performance of BPSO.

Original language	English
Title of host publication	Proceedings of the 16th IFAC World Congress, IFAC 2005
Publisher	IFAC Secretariat
Pages	431-434
Number of pages	4
ISBN (Print)	008045108X, 9780080451084
DOIs	https://doi.org/10.3182/20050703-6-cz-1902.00933
Publication status	Published - 2005

Publication series

Name	IFAC Proceedings Volumes (IFAC-PapersOnline)
Volume	16
ISSN (Print)	1474-6670

Keywords

Asymptotic stability
Balloon PSO (BPSO)
Global convergence
Particle swarm optimizer (PSO)

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10.3182/20050703-6-cz-1902.00933

Cite this

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title = "Stablity, convergence of balloon Particle Swarm Optimizer and its application on vechile modelling",

abstract = "Particle Swarm Optimizer, PSO, exhibits good performance for optimization problem, although, PSO can not guarantee convergence of a global minimum, even a local minimum. However, there are some adjustable parameters and restrictive conditions which can affect performance of the algorithm. in this paper, a new adaptive PSO algorithm-Balloon PSO (BPSO) is proposed. The sufficient conditions for asymptotic stability of acceleration factor and inertia weight are deduced. Furthermore it is proved that BPSO is a global research algorithm. Simulation results of power spectral density (PSD) of vehicle vibratory signal estimation show the good performance of BPSO.",

keywords = "Asymptotic stability, Balloon PSO (BPSO), Global convergence, Particle swarm optimizer (PSO)",

author = "Feng Pan and Jie Chen and Gan, {Ming Gang} and Tao Cai and Tu, {Xu Yan}",

year = "2005",

doi = "10.3182/20050703-6-cz-1902.00933",

language = "English",

isbn = "008045108X",

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publisher = "IFAC Secretariat",

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booktitle = "Proceedings of the 16th IFAC World Congress, IFAC 2005",

}

Stablity, convergence of balloon Particle Swarm Optimizer and its application on vechile modelling. / Pan, Feng; Chen, Jie; Gan, Ming Gang et al.
Proceedings of the 16th IFAC World Congress, IFAC 2005. IFAC Secretariat, 2005. p. 431-434 (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 16).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Stablity, convergence of balloon Particle Swarm Optimizer and its application on vechile modelling

AU - Pan, Feng

AU - Chen, Jie

AU - Gan, Ming Gang

AU - Cai, Tao

AU - Tu, Xu Yan

PY - 2005

Y1 - 2005

N2 - Particle Swarm Optimizer, PSO, exhibits good performance for optimization problem, although, PSO can not guarantee convergence of a global minimum, even a local minimum. However, there are some adjustable parameters and restrictive conditions which can affect performance of the algorithm. in this paper, a new adaptive PSO algorithm-Balloon PSO (BPSO) is proposed. The sufficient conditions for asymptotic stability of acceleration factor and inertia weight are deduced. Furthermore it is proved that BPSO is a global research algorithm. Simulation results of power spectral density (PSD) of vehicle vibratory signal estimation show the good performance of BPSO.

AB - Particle Swarm Optimizer, PSO, exhibits good performance for optimization problem, although, PSO can not guarantee convergence of a global minimum, even a local minimum. However, there are some adjustable parameters and restrictive conditions which can affect performance of the algorithm. in this paper, a new adaptive PSO algorithm-Balloon PSO (BPSO) is proposed. The sufficient conditions for asymptotic stability of acceleration factor and inertia weight are deduced. Furthermore it is proved that BPSO is a global research algorithm. Simulation results of power spectral density (PSD) of vehicle vibratory signal estimation show the good performance of BPSO.

KW - Asymptotic stability

KW - Balloon PSO (BPSO)

KW - Global convergence

KW - Particle swarm optimizer (PSO)

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SN - 008045108X

SN - 9780080451084

T3 - IFAC Proceedings Volumes (IFAC-PapersOnline)

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BT - Proceedings of the 16th IFAC World Congress, IFAC 2005

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Stablity, convergence of balloon Particle Swarm Optimizer and its application on vechile modelling

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Keywords

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