Abstract
This paper presents a neural network controller for synchronization of two Duffing-Holmes oscillators. A Duffing-Holmes oscillator is a chaotic system describing a dynamics of the forced vibration of a buckled elastic beam. The controller is a feedforward neural network trained to drive the first Duffing-Holmes oscillator so that its states converge to those of the other Duffing-Holmes. The training scheme is based on a model reference strategy with imposing stability conditions on the controller’s parameters. The stability condition guarantees the convergence of the synchronization errors. Numerical simulations are conducted to illustrate the feasibility and effectiveness of the stable neural network controller.
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Kuntanapreeda, S. (2010). Synchronization of Duffing-Holmes Oscillators Using Stable Neural Network Controller. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6423. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16696-9_27
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DOI: https://doi.org/10.1007/978-3-642-16696-9_27
Publisher Name: Springer, Berlin, Heidelberg
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