Detail publikace

Stabilization of Higher Periodic Orbits of the Chaotic Logistic and Henon Maps using Meta-evolutionary Approaches

MATOUŠEK, R. HŮLKA, T.

Anglický název

Stabilization of Higher Periodic Orbits of the Chaotic Logistic and Henon Maps using Meta-evolutionary Approaches

Typ

Stať ve sborníku v databázi WoS či Scopus

Jazyk

en

Originální abstrakt

This paper deals with an advanced adjustment of stabilization sequences for selected discrete chaotic systems by means of meta-evolutionary approaches. As the representative models of deterministic chaotic systems, one dimensional Logistic equation and two dimensional H ' enon map were used. The stability of the chaotic systems has been studied by computer simulations. The novelty of the approach is in an effective design of a new type of objective function, which is very important for the whole optimization process of higher periodic orbits. Furthermore, modern meta-heuristics were used for own design of proper stabilizing sequences. The used optimization methods are a grid-based Nelder-Mead Algorithm (NMA), Genetic Algorithm (GA) as well as Genetic Programming (GP). GP results show good capability of control law synthesis in case of higher periodic orbits. A connection of GP and second level optimization using GA or NMA displays better results than stand alone meta-heuristic techniques. Although the task of stabilizing the presented chaotic systems is known, its solution presented for periodic orbits two and four is not trivial.

Klíčová slova anglicky

Orbits; Mathematical model; Logistics; Linear programming; Chaos; Sociology; Statistics

Vydáno

2019-08-08

Nakladatel

IEEE

Místo

NEW YORK

ISBN

978-1-7281-2153-6

Kniha

2019 IEEE Congress on Evolutionary Computation, CEC 2019 – Proceedings

Strany od–do

1758–1765

Počet stran

8

BIBTEX


@inproceedings{BUT162169,
  author="Radomil {Matoušek} and Tomáš {Hůlka}",
  title="Stabilization of Higher Periodic Orbits of the Chaotic Logistic and Henon Maps using Meta-evolutionary Approaches",
  booktitle="2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings 
",
  year="2019",
  pages="1758--1765",
  publisher="IEEE",
  address="NEW YORK",
  doi="10.1109/CEC.2019.8790075",
  isbn="978-1-7281-2153-6"
}