Using genetic algorithms for naval subsystem damage assessment and design improvements

Authors:
Christopher McCubbin;David Scheidt;Oliver Bandte;Steven Marshall;Iavor Trifonov
Affiliations:
Johns Hopkins University;Johns Hopkins University;Icosystem Inc.;Johns Hopkins University;Icosystem Inc.
Venue:
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Year:
2007

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Abstract

Some auxiliary systems of next generation naval ships will utilize distributed automatic control. Such distributed control systems will use interconnected sensors, actuators, controllers and networking components to diagnose and reconfigure the auxiliary systems. Testing these systems will be difficult with traditional methods of fault analysis due to the interconnected and automatic nature of these subsystems. We have designed a suite of genetic algorithms to find interesting and hidden damage scenarios in a testbed of a naval subsystem. Given this knowledge, we use a genetic algorithm to improve upon the design of this subsystem.