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
         
        
        
        
        
        
            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;
         
        
        
        
            Conference_Titel : 
Control Conference (ECC), 2001 European
         
        
            Conference_Location : 
Porto
         
        
            Print_ISBN : 
978-3-9524173-6-2