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Directing orbits of chaotic systems by particle swarm optimization

Author

Listed:
  • Liu, Bo
  • Wang, Ling
  • Jin, Yi-Hui
  • Tang, Fang
  • Huang, De-Xian

Abstract

This paper applies a novel evolutionary computation algorithm named particle swarm optimization (PSO) to direct the orbits of discrete chaotic dynamical systems towards desired target region within a short time by adding only small bounded perturbations, which could be formulated as a multi-modal numerical optimization problem with high dimension. Moreover, the synchronization of chaotic systems is also studied, which can be dealt with as an online problem of directing orbits. Numerical simulations based on Hénon Map demonstrate the effectiveness and efficiency of PSO, and the effects of some parameters are also investigated.

Suggested Citation

  • Liu, Bo & Wang, Ling & Jin, Yi-Hui & Tang, Fang & Huang, De-Xian, 2006. "Directing orbits of chaotic systems by particle swarm optimization," Chaos, Solitons & Fractals, Elsevier, vol. 29(2), pages 454-461.
    • Handle: RePEc:eee:chsofr:v:29:y:2006:i:2:p:454-461
    DOI: 10.1016/j.chaos.2005.08.034
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    References listed on IDEAS

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    1. Liu, Bo & Wang, Ling & Jin, Yi-Hui & Tang, Fang & Huang, De-Xian, 2005. "Improved particle swarm optimization combined with chaos," Chaos, Solitons & Fractals, Elsevier, vol. 25(5), pages 1261-1271.
    2. Elabbasy, E.M. & Agiza, H.N. & El-Dessoky, M.M., 2005. "Global synchronization criterion and adaptive synchronization for new chaotic system," Chaos, Solitons & Fractals, Elsevier, vol. 23(4), pages 1299-1309.
    3. Ge, Z.-M. & Cheng, J.-W., 2005. "Chaos synchronization and parameter identification of three time scales brushless DC motor system," Chaos, Solitons & Fractals, Elsevier, vol. 24(2), pages 597-616.
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    Cited by:

    1. Matsushita, H. & Kurokawa, H. & Kousaka, T., 2019. "Saddle-node bifurcation parameter detection strategy with nested-layer particle swarm optimization," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 126-134.
    2. He, Qie & Wang, Ling & Liu, Bo, 2007. "Parameter estimation for chaotic systems by particle swarm optimization," Chaos, Solitons & Fractals, Elsevier, vol. 34(2), pages 654-661.
    3. He, Yao-Yao & Zhou, Jian-Zhong & Xiang, Xiu-Qiao & Chen, Heng & Qin, Hui, 2009. "Comparison of different chaotic maps in particle swarm optimization algorithm for long-term cascaded hydroelectric system scheduling," Chaos, Solitons & Fractals, Elsevier, vol. 42(5), pages 3169-3176.
    4. Wang, Yang & Pan, Binfeng & Zheng, Yue & Lu, Xiang, 2017. "ETLBO based optimal targeting to the moon in the PCR3BP chaotic system," Chaos, Solitons & Fractals, Elsevier, vol. 105(C), pages 21-28.
    5. Peng, Bo & Liu, Bo & Zhang, Fu-Yi & Wang, Ling, 2009. "Differential evolution algorithm-based parameter estimation for chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 39(5), pages 2110-2118.
    6. Coelho, Leandro dos Santos, 2008. "A quantum particle swarm optimizer with chaotic mutation operator," Chaos, Solitons & Fractals, Elsevier, vol. 37(5), pages 1409-1418.
    7. Coelho, Leandro dos Santos & Mariani, Viviana Cocco, 2009. "A novel chaotic particle swarm optimization approach using Hénon map and implicit filtering local search for economic load dispatch," Chaos, Solitons & Fractals, Elsevier, vol. 39(2), pages 510-518.
    8. Alatas, Bilal & Akin, Erhan, 2009. "Chaotically encoded particle swarm optimization algorithm and its applications," Chaos, Solitons & Fractals, Elsevier, vol. 41(2), pages 939-950.

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