DocumentCode
1726461
Title
Chaotic system identification via genetic algorithm
Author
Caponetto, R.C. ; Fortuna, L. ; Manganaro, G. ; Xibilia, M.G.
Author_Institution
Catania Univ., Italy
fYear
1995
Firstpage
170
Lastpage
174
Abstract
In this paper a novel approach for identifying the asymptotic behaviour of non-linear chaotic dynamic systems is proposed. The problem has been faced like an optimisation procedure and it has been solved by using the genetic algorithm approach. Given the asymptotic time evolution of the state variables of the non-linear system that has to be identified, they are used to synchronise another system with the same mathematical model. The difference between the given time evolution and the derived trajectories is used in order to define the functional to be minimised
Keywords
chaos; genetic algorithms; identification; nonlinear dynamical systems; asymptotic behaviour; asymptotic time evolution; chaotic dynamic systems; derived trajectories; functional; genetic algorithm; state variables; time evolution;
fLanguage
English
Publisher
iet
Conference_Titel
Genetic Algorithms in Engineering Systems: Innovations and Applications, 1995. GALESIA. First International Conference on (Conf. Publ. No. 414)
Conference_Location
Sheffield
Print_ISBN
0-85296-650-4
Type
conf
DOI
10.1049/cp:19951044
Filename
501667
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