Abstract
This paper addresses the control of chaos using a neural network for a continuous time dynamical system. The neural network is trained on both the Ott–Grebogi–Yorke (OGY) control algorithm and the Pyragas's delayed feedback control algorithm. The system considered for this study is a Bonhoeffer–van der Pol (BVP) oscillator. A feed-forward backpropagating neural network is used for the control application. It is found that the control effected by the neural network trained on the OGY control algorithm results in smaller control transients than when the control is effected directly by the OGY algorithm itself. The control transients are of the same order in the case of the Pyragas method.
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