Accelerated Co-evolutionary Algorithms

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A new co-evolutionary algorithm, of which the convergence speed is accelerated by neural networks, is proposed and verified in this paper. To reduce computational load required for co-evolutionary optimization processes, the cost function and constraint information is stored in the neural networks, and the extra offspring group, whose cost is computed by the neural networks, is generated. It increases the offspring population size without overloading computational effort; therefore, the convergence speed is accelerated. The proposed algorithm is applied to attitude control design of flexible satellites, and it is verified by computer simulations and experiments using a torque-free air bearing system.
Publisher
한국항공우주학회
Issue Date
2002-05
Language
English
Citation

INTERNATIONAL JOURNAL OF AERONAUTICAL AND SPACE SCIENCES , v.3, no.1, pp.50 - 60

ISSN
2093-274X
URI
http://hdl.handle.net/10203/81650
Appears in Collection
AE-Journal Papers(저널논문)
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