DocumentCode :
697320
Title :
Non-linear model reduction by genetic algorithms with using a system structure related fitness function
Author :
Buttelmann, Maik ; Lohmann, Boris
Author_Institution :
Inst. of Autom. (IAT), Univ. of Bremen, Bremen, Germany
fYear :
2001
fDate :
4-7 Sept. 2001
Firstpage :
1870
Lastpage :
1875
Abstract :
Based on a known order reduction method for non-linear systems a solution is proposed to reduce the high system complexity of the order-reduced system, too. For this, suitable secondary conditions for the order reduction method are defined with the help of a genetic algorithm (GA). For the use of GA it is essential that the fitness function fulfils some "smoothness" or "small causes, small effects" properties. This is investigated for a system structure related fitness function and an example with technical background is given.
Keywords :
genetic algorithms; nonlinear control systems; reduced order systems; GA; genetic algorithms; nonlinear model reduction; nonlinear systems; order reduction method; order-reduced system; system structure related fitness function; Europe; Fitness Landscape; Genetic Algorithm; Model Simplification; Order Reduction; Structure of Non-linear Systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (ECC), 2001 European
Conference_Location :
Porto
Print_ISBN :
978-3-9524173-6-2
Type :
conf
Filename :
7076194
Link To Document :
بازگشت