A dynamic genetic algorithm based on particle filter for UCAV formation control

Xingguang Peng; Demin Xu; Xiaoguang Gao

A dynamic genetic algorithm based on particle filter for UCAV formation control

Xingguang Peng
, Demin Xu
, Xiaoguang Gao

School of Electronics and Information

Northwestern Polytechnical University Xian

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

1 Scopus citations

Abstract

Formation control problem is an important issue in formation flying of unmanned combat aerial vehicles (UCAVs). A dynamic genetic algorithm based on particle filter (PFDGA) was proposed to solve this dynamic optimal control problem. Within this algorithm, the genetic algorithm (GA) and the particle filter (PF) are properly combined together. The GA provides observation of global optimum for the PF and the PF guide the search of the GA. Experimental results show PFDGA performs better in compare with random immigration GA (RIGA) and the formation control problem is effectively solved by PFDGA.

Original language	English
Title of host publication	Proceedings of the 29th Chinese Control Conference, CCC'10
Pages	5238-5241
Number of pages	4
State	Published - 2010
Event	29th Chinese Control Conference, CCC'10 - Beijing, China Duration: 29 Jul 2010 → 31 Jul 2010

Publication series

Name	Proceedings of the 29th Chinese Control Conference, CCC'10

Conference

Conference	29th Chinese Control Conference, CCC'10
Country/Territory	China
City	Beijing
Period	29/07/10 → 31/07/10

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 10 Reduced Inequalities

Keywords

Dynamic genetic algorithm
Formation control
Particle filter
UCAV

Cite this

@inproceedings{7c7516d0fcb14c24817504afc082d7d8,

title = "A dynamic genetic algorithm based on particle filter for UCAV formation control",

abstract = "Formation control problem is an important issue in formation flying of unmanned combat aerial vehicles (UCAVs). A dynamic genetic algorithm based on particle filter (PFDGA) was proposed to solve this dynamic optimal control problem. Within this algorithm, the genetic algorithm (GA) and the particle filter (PF) are properly combined together. The GA provides observation of global optimum for the PF and the PF guide the search of the GA. Experimental results show PFDGA performs better in compare with random immigration GA (RIGA) and the formation control problem is effectively solved by PFDGA.",

keywords = "Dynamic genetic algorithm, Formation control, Particle filter, UCAV",

author = "Xingguang Peng and Demin Xu and Xiaoguang Gao",

year = "2010",

language = "英语",

isbn = "9787894631046",

series = "Proceedings of the 29th Chinese Control Conference, CCC'10",

pages = "5238--5241",

booktitle = "Proceedings of the 29th Chinese Control Conference, CCC'10",

note = "29th Chinese Control Conference, CCC'10 ; Conference date: 29-07-2010 Through 31-07-2010",

}

A dynamic genetic algorithm based on particle filter for UCAV formation control. / Peng, Xingguang; Xu, Demin; Gao, Xiaoguang.
Proceedings of the 29th Chinese Control Conference, CCC'10. 2010. p. 5238-5241 5573402 (Proceedings of the 29th Chinese Control Conference, CCC'10).

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

TY - GEN

T1 - A dynamic genetic algorithm based on particle filter for UCAV formation control

AU - Peng, Xingguang

AU - Xu, Demin

AU - Gao, Xiaoguang

PY - 2010

Y1 - 2010

N2 - Formation control problem is an important issue in formation flying of unmanned combat aerial vehicles (UCAVs). A dynamic genetic algorithm based on particle filter (PFDGA) was proposed to solve this dynamic optimal control problem. Within this algorithm, the genetic algorithm (GA) and the particle filter (PF) are properly combined together. The GA provides observation of global optimum for the PF and the PF guide the search of the GA. Experimental results show PFDGA performs better in compare with random immigration GA (RIGA) and the formation control problem is effectively solved by PFDGA.

AB - Formation control problem is an important issue in formation flying of unmanned combat aerial vehicles (UCAVs). A dynamic genetic algorithm based on particle filter (PFDGA) was proposed to solve this dynamic optimal control problem. Within this algorithm, the genetic algorithm (GA) and the particle filter (PF) are properly combined together. The GA provides observation of global optimum for the PF and the PF guide the search of the GA. Experimental results show PFDGA performs better in compare with random immigration GA (RIGA) and the formation control problem is effectively solved by PFDGA.

KW - Dynamic genetic algorithm

KW - Formation control

KW - Particle filter

KW - UCAV

UR - https://www.scopus.com/pages/publications/78650244121

M3 - 会议稿件

AN - SCOPUS:78650244121

SN - 9787894631046

T3 - Proceedings of the 29th Chinese Control Conference, CCC'10

SP - 5238

EP - 5241

BT - Proceedings of the 29th Chinese Control Conference, CCC'10

T2 - 29th Chinese Control Conference, CCC'10

Y2 - 29 July 2010 through 31 July 2010

ER -

A dynamic genetic algorithm based on particle filter for UCAV formation control

Abstract

Publication series

Conference

UN SDGs

Keywords

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