Identifying the structure of nonlinear dynamic systems using multiobjective genetic programming

Identifying the structure of nonlinear dynamic systems using multiobjective genetic programming

A method for identifying the structure of nonlinear polynomial dynamic models is presented. This approach uses an evolutionary algorithm, genetic programming, in a multiobjective fashion to generate global models which describe the dynamic behavior of the nonlinear system under investigation. The va...

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Veröffentlicht in:IEEE transactions on systems, man and cybernetics. Part A, Systems and humans man and cybernetics. Part A, Systems and humans, 2004-07, Vol.34 (4), p.531-545
Hauptverfasser: Rodriguez-Vazquez, K., Fonseca, C.M., Fleming, P.J.
Format: Artikel
Sprache:eng
Schlagworte:
Dynamic programming
Engines
Evolutionary computation
Genetic programming
Mathematical model
Nonlinear dynamical systems
Nonlinear systems
Polynomials
System identification
Turbines
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Zusammenfassung:A method for identifying the structure of nonlinear polynomial dynamic models is presented. This approach uses an evolutionary algorithm, genetic programming, in a multiobjective fashion to generate global models which describe the dynamic behavior of the nonlinear system under investigation. The validation stage of system identification is simultaneously evaluated using the multiobjective tool, in order to direct the identification process to a set of global models of the system.
ISSN:1083-4427
2168-2216
1558-2426
2168-2232
DOI:10.1109/TSMCA.2004.826299