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

Author

Peng Xingguang ; Xu Demin ; Gao Xiaoguang

Author_Institution

Coll. of Marine Eng., Northwestern Polytech. Univ., Xi´an, China

fYear

2010

fDate

29-31 July 2010

Firstpage

5238

Lastpage

5241

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

aircraft control; genetic algorithms; military aircraft; optimal control; particle filtering (numerical methods); remotely operated vehicles; PFDGA; RIGA; UCAV formation control; dynamic genetic algorithm; dynamic optimal control problem; formation flying; particle filter; random immigration GA; unmanned combat aerial vehicles; Electronic mail; Evolutionary computation; Genetic algorithms; Heuristic algorithms; Optimized production technology; Particle filters; Vehicle dynamics; Dynamic Genetic Algorithm; Formation Control; Particle Filter; UCAV;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (CCC), 2010 29th Chinese

Conference_Location

Beijing

Print_ISBN

978-1-4244-6263-6

Type

conf

Filename

5573402