Conference Paper

Maximum entropy adaptive control of chaotic systems

Dept. of Electr. & Comput. Eng., Syracuse Univ., NY
DOI: 10.1109/ISIC.1998.713668 Conference: Intelligent Control (ISIC), 1998. Held jointly with IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA), Intelligent Systems and Semiotics (ISAS), Proceedings
Source: IEEE Xplore

ABSTRACT We present an adaptive control strategy for controlling chaos in
nonlinear dynamical systems. The proposed method is a neuro-fuzzy model
as a globally coupled map based on entropy optimization, which combines
an identified system fuzzy model and a control input update rule. The
stability analysis of the resulting control scheme is shown by a
property of contraction mappings. Numerical examples are given to
illustrate the transition between chaotic states and stable equilibrium
states

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