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Chaos control using maximum Lyapunov number of universal learning network

Chaotic behaviors are characterized mainly by Lyapunov numbers of a dynamic system. In this paper, a new method is proposed, which can control the maximum Lyapunov number of dynamic system that can be represented by universal learning networks (ULNs). The maximum Lyapunov number of a dynamic system can be formulated by using higher order derivatives of ULNs and parameters of ULNs can be adjusted for the maximum Lyapunov number to approach the target value by the combined gradient and random search method. Based on simulation results, a fully connected ULN with three nodes is possible to display chaotic behaviors.