Flight management of multiple aerial vehicles using genetic algorithms

S. KANURY; Y. D. SONG

doi:10.1109/SSST.2006.1619100

Flight management of multiple aerial vehicles using genetic algorithms

S. KANURY^*
, Y. D. SONG

^*Corresponding author for this work

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

13 Citations (Scopus)

Abstract

Flight Management System (FMS) plays an important role in automatic and fuel-efficient flight from take-off to landing and reducing the pilot's workload. Path planning and tracking are two major functions of FMS. Most flight control algorithms assume that reference trajectory is available, which is not the case in real world. In this paper we introduce a new FMS that not only generates the optimal trajectory but also produces smooth control action for path tracking. Genetic Algorithms (GAs) is used to generate the optimal flight path when the target positions are given. Unknown obstacles also are considered. A memory based control strategy is developed to steer the vehicle along the generated trajectory, which can be dynamically adjusted according to the varying flight conditions. Simulation is conducted for verification. © 2006 IEEE.

Original language	English
Title of host publication	Proceedings of the 38th Southeastern Symposium on System Theory
Publisher	IEEE
Pages	33-37
Number of pages	5
ISBN (Print)	0780394577
DOIs	https://doi.org/10.1109/SSST.2006.1619100
Publication status	Published - 17 Oct 2006
Externally published	Yes
Event	The Thirty-Eighth Southeastern Symposium on System Theory 2006 - Cookeville, United States Duration: 5 Mar 2006 → 7 Mar 2006

Symposium

Symposium	The Thirty-Eighth Southeastern Symposium on System Theory 2006
Country/Territory	United States
City	Cookeville
Period	5/03/06 → 7/03/06

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10.1109/SSST.2006.1619100

Cite this

@inproceedings{78492753c7204678b4df302cdcb1456e,

title = "Flight management of multiple aerial vehicles using genetic algorithms",

abstract = "Flight Management System (FMS) plays an important role in automatic and fuel-efficient flight from take-off to landing and reducing the pilot's workload. Path planning and tracking are two major functions of FMS. Most flight control algorithms assume that reference trajectory is available, which is not the case in real world. In this paper we introduce a new FMS that not only generates the optimal trajectory but also produces smooth control action for path tracking. Genetic Algorithms (GAs) is used to generate the optimal flight path when the target positions are given. Unknown obstacles also are considered. A memory based control strategy is developed to steer the vehicle along the generated trajectory, which can be dynamically adjusted according to the varying flight conditions. Simulation is conducted for verification. {\textcopyright} 2006 IEEE.",

author = "S. KANURY and SONG, \{Y. D.\}",

year = "2006",

month = oct,

day = "17",

doi = "10.1109/SSST.2006.1619100",

language = "English",

isbn = "0780394577",

pages = "33--37",

booktitle = "Proceedings of the 38th Southeastern Symposium on System Theory",

publisher = "IEEE",

note = "The Thirty-Eighth Southeastern Symposium on System Theory 2006 ; Conference date: 05-03-2006 Through 07-03-2006",

}

TY - GEN

T1 - Flight management of multiple aerial vehicles using genetic algorithms

AU - KANURY, S.

AU - SONG, Y. D.

PY - 2006/10/17

Y1 - 2006/10/17

N2 - Flight Management System (FMS) plays an important role in automatic and fuel-efficient flight from take-off to landing and reducing the pilot's workload. Path planning and tracking are two major functions of FMS. Most flight control algorithms assume that reference trajectory is available, which is not the case in real world. In this paper we introduce a new FMS that not only generates the optimal trajectory but also produces smooth control action for path tracking. Genetic Algorithms (GAs) is used to generate the optimal flight path when the target positions are given. Unknown obstacles also are considered. A memory based control strategy is developed to steer the vehicle along the generated trajectory, which can be dynamically adjusted according to the varying flight conditions. Simulation is conducted for verification. © 2006 IEEE.

AB - Flight Management System (FMS) plays an important role in automatic and fuel-efficient flight from take-off to landing and reducing the pilot's workload. Path planning and tracking are two major functions of FMS. Most flight control algorithms assume that reference trajectory is available, which is not the case in real world. In this paper we introduce a new FMS that not only generates the optimal trajectory but also produces smooth control action for path tracking. Genetic Algorithms (GAs) is used to generate the optimal flight path when the target positions are given. Unknown obstacles also are considered. A memory based control strategy is developed to steer the vehicle along the generated trajectory, which can be dynamically adjusted according to the varying flight conditions. Simulation is conducted for verification. © 2006 IEEE.

UR - https://www.scopus.com/pages/publications/33749646134

U2 - 10.1109/SSST.2006.1619100

DO - 10.1109/SSST.2006.1619100

M3 - Conference paper (refereed)

AN - SCOPUS:33749646134

SN - 0780394577

SP - 33

EP - 37

BT - Proceedings of the 38th Southeastern Symposium on System Theory

PB - IEEE

T2 - The Thirty-Eighth Southeastern Symposium on System Theory 2006

Y2 - 5 March 2006 through 7 March 2006

ER -

Flight management of multiple aerial vehicles using genetic algorithms

Abstract

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