Abstract
System identification is one of the necessary tasks in controller design and its adaptation. Many identification methods are known, and new ones are still being developed in order to find a better solution for huge scale of cases. In the paper identification of system of 2nd order systems using genetic algorithms is demonstrated. In presented case genetic algorithms are used for finding parameters of difference equation of the controlled system and it substitutes classic, conventional optimization methods. Proposed method can be used for continuous identification or it can be activated in defined time points on stored data. And on the other hand, presented task is also a case of a specific usage of genetic algorithms and it can serve as a proof of efficiency of this non-conventional optimization method (simulated in the Matlab&Simulink software environment).
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© 2014 Springer International Publishing Switzerland
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Nowaková, J., Pokorný, M. (2014). System Identification Using Genetic Algorithms. In: Kömer, P., Abraham, A., Snášel, V. (eds) Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014. Advances in Intelligent Systems and Computing, vol 303. Springer, Cham. https://doi.org/10.1007/978-3-319-08156-4_41
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DOI: https://doi.org/10.1007/978-3-319-08156-4_41
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08155-7
Online ISBN: 978-3-319-08156-4
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