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Real Time Optima Tracking Using Harvesting Models of the Genetic AlgorithmTracking optima in real time propulsion control, particularly for non-stationary optimization problems is a challenging task. Several approaches have been put forward for such a study including the numerical method called the genetic algorithm. In brief, this approach is built upon Darwinian-style competition between numerical alternatives displayed in the form of binary strings, or by analogy to 'pseudogenes'. Breeding of improved solution is an often cited parallel to natural selection in.evolutionary or soft computing. In this report we present our results of applying a novel model of a genetic algorithm for tracking optima in propulsion engineering and in real time control. We specialize the algorithm to mission profiling and planning optimizations, both to select reduced propulsion needs through trajectory planning and to explore time or fuel conservation strategies.
Document ID
Document Type
Reprint (Version printed in journal)
Baskaran, Subbiah
(Raytheon Co. Huntsville, AL United States)
Noever, D.
(NASA Marshall Space Flight Center Huntsville, AL United States)
Date Acquired
August 19, 2013
Publication Date
January 1, 1999
Subject Category
Spacecraft Propulsion And Power
Meeting Information
Advanced Space Propulsion(Huntsville, AL)
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