Optimizing evader's trajectory in 6-DOF pursuit-evasion problem using parallel evolutionary programming

Abstract. The optimisation of air combat manoeuvre using standard evolutionary programming (EP) algorithm is discussed. The objective is to increase the level of realism in the simulation. This is achieved via employing the nonlinear six degree-of-freedom equations of motion to represent the vehicle...

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Main Authors: Nusyirwan, Istas F., Bil, Cees
Format: Conference or Workshop Item
Published: 2007
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Online Access:http://eprints.utm.my/id/eprint/14264/
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Institution: Universiti Teknologi Malaysia
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spelling my.utm.142642012-11-30T03:01:17Z http://eprints.utm.my/id/eprint/14264/ Optimizing evader's trajectory in 6-DOF pursuit-evasion problem using parallel evolutionary programming Nusyirwan, Istas F. Bil, Cees TJ Mechanical engineering and machinery Abstract. The optimisation of air combat manoeuvre using standard evolutionary programming (EP) algorithm is discussed. The objective is to increase the level of realism in the simulation. This is achieved via employing the nonlinear six degree-of-freedom equations of motion to represent the vehicle. The evader is modelled as a six degree of freedom generic jet fighter aircraft. The aileron, elevator, rudder and throttle setting of the aircraft are set as control variables. The pursuer is a medium range generic air-to-air missile and modelled as a point-mass. The air combat is played in three dimensions. The pursuer seeks to intercept the evader and the evader seeks to avoid interception. The search for optimal evasion solution is conducted utilising evolutionary programming (EP). The optimisation algorithm developed aims to maximise the objective function. The objective function is a self-play simulation between the players. The value of the game is demonstrated as the outcome of the game. The solution that produces the maximum value of fitness is considered to be the best. The optimal solution found is found to be highly dependent on the initial condition. A slight change of the initial condition will result a completely different set of optimal solutions. The computing time is further improved through parallel computing. This is achieved via dividing the solutions into smaller groups and sending each group to different processors for evaluation. As the numbers of processors increase, the time taken to search for optimal solution was found to decrease. 2007 Conference or Workshop Item PeerReviewed Nusyirwan, Istas F. and Bil, Cees (2007) Optimizing evader's trajectory in 6-DOF pursuit-evasion problem using parallel evolutionary programming. In: Simulation Conference and Exhibition (SimTecT 2007), 2007, Brisbane Convention Centre.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Nusyirwan, Istas F.
Bil, Cees
Optimizing evader's trajectory in 6-DOF pursuit-evasion problem using parallel evolutionary programming
description Abstract. The optimisation of air combat manoeuvre using standard evolutionary programming (EP) algorithm is discussed. The objective is to increase the level of realism in the simulation. This is achieved via employing the nonlinear six degree-of-freedom equations of motion to represent the vehicle. The evader is modelled as a six degree of freedom generic jet fighter aircraft. The aileron, elevator, rudder and throttle setting of the aircraft are set as control variables. The pursuer is a medium range generic air-to-air missile and modelled as a point-mass. The air combat is played in three dimensions. The pursuer seeks to intercept the evader and the evader seeks to avoid interception. The search for optimal evasion solution is conducted utilising evolutionary programming (EP). The optimisation algorithm developed aims to maximise the objective function. The objective function is a self-play simulation between the players. The value of the game is demonstrated as the outcome of the game. The solution that produces the maximum value of fitness is considered to be the best. The optimal solution found is found to be highly dependent on the initial condition. A slight change of the initial condition will result a completely different set of optimal solutions. The computing time is further improved through parallel computing. This is achieved via dividing the solutions into smaller groups and sending each group to different processors for evaluation. As the numbers of processors increase, the time taken to search for optimal solution was found to decrease.
format Conference or Workshop Item
author Nusyirwan, Istas F.
Bil, Cees
author_facet Nusyirwan, Istas F.
Bil, Cees
author_sort Nusyirwan, Istas F.
title Optimizing evader's trajectory in 6-DOF pursuit-evasion problem using parallel evolutionary programming
title_short Optimizing evader's trajectory in 6-DOF pursuit-evasion problem using parallel evolutionary programming
title_full Optimizing evader's trajectory in 6-DOF pursuit-evasion problem using parallel evolutionary programming
title_fullStr Optimizing evader's trajectory in 6-DOF pursuit-evasion problem using parallel evolutionary programming
title_full_unstemmed Optimizing evader's trajectory in 6-DOF pursuit-evasion problem using parallel evolutionary programming
title_sort optimizing evader's trajectory in 6-dof pursuit-evasion problem using parallel evolutionary programming
publishDate 2007
url http://eprints.utm.my/id/eprint/14264/
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