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Genetic Algorithms for Minimal Fuel Consumption of Electric Propulsion Space Vehicles

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3 Author(s)
Reddy, B.B.K. ; Dept. of Electr. & Comput. Eng., North Carolina A&T State Univ., Greensboro, NC ; Homaifar, A. ; Esterline, A.C.

This paper demonstrates the utility of genetic algorithms (GAs) to determine a near optimal control strategy for electric propulsion systems. The various strategies implemented are simple GA, simple GA with elitism and micro GA. The accuracy and performance of the control strategy obtained using these methods are discussed along with their detailed description. This work inherently validates the use of ionic thrust for deep space missions

Published in:

Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on  (Volume:2 )

Date of Conference:

28-30 Nov. 2005

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