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Optimization in Control and Learning in Coupled Map Lattice Systems

Author

Listed:
  • S. P. Nair

    (University of Florida)

  • P. M. Pardalos

    (University of Florida)

  • V. A. Yatsenko

    (Institute of Space Research)

Abstract

In this paper, we analyze various control algorithms that have been proposed for controlling spatiotemporal chaos in a globally coupled map lattice (CML) system. We reformulate the choice of feedback parameters in such systems as a constrained optimization problem and provide numerical and experimental results on the choice of optimal parameters for controlling the mean global Lyapunov exponent of a lattice. Finally, we propose a scheme to use this optimization technique to solve a learning problem in which such a CML system can be used to emulate the dynamics of an epileptic brain.

Suggested Citation

  • S. P. Nair & P. M. Pardalos & V. A. Yatsenko, 2007. "Optimization in Control and Learning in Coupled Map Lattice Systems," Journal of Optimization Theory and Applications, Springer, vol. 134(3), pages 533-547, September.
    • Handle: RePEc:spr:joptap:v:134:y:2007:i:3:d:10.1007_s10957-007-9257-2
    DOI: 10.1007/s10957-007-9257-2
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    References listed on IDEAS

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    1. Shibata, Hiroshi, 2001. "KS entropy and mean Lyapunov exponent for coupled map lattices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 292(1), pages 182-192.
    2. P. M. Pardalos & V. A. Yatsenko, 2006. "Optimization Approach to the Estimation and Control of Lyapunov Exponents," Journal of Optimization Theory and Applications, Springer, vol. 128(1), pages 29-48, January.
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