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
Link To Document :
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