Tracking 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.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Title :

    Real Time Optima Tracking Using Harvesting Models of the Genetic Algorithm


    Contributors:

    Conference:

    Advanced Space Propulsion ; 1999 ; Huntsville, AL, United States


    Publication date :

    1999-01-01


    Type of media :

    Miscellaneous


    Type of material :

    No indication


    Language :

    English




    Tracking Moving Optima Using Kalman-Based Predictions

    Rossi, Claudio / Abderrahim Fichouche, Mohamed / Díaz Cabrera, Julio César | BASE | 2008

    Free access

    Optima Loesung - Test Kia Optima 1,7 CRDi

    Thomas,J. / Kia Motors,KR | Automotive engineering | 2012


    Fahrzeugtest: Kia Optima

    Kia Motors,KR | Automotive engineering | 2010


    Neu: Kia Optima

    Skarics,R. / Kia Motor,KR | Automotive engineering | 2012


    Kurztest Kia Optima PHEV

    Lingner,H. / Kia Motors,KR | Automotive engineering | 2016