Chaos control using second order derivatives of universal learning network

Abstract

A method is proposed for controlling chaotic phenomena on a universal learning network (ULN). The chaos control method proposed here is a novel one. Generation and die-out of chaotic phenomena are controlled by changing the Lyapunov number of the ULN, which is accomplished by adjusting ULN parameters so as to minimize a criterion function that is the difference between the desired Lyapunov number and its actual value. Both a gradient method utilizing second order derivatives of the ULN and a random search method are adopted to optimize the parameters. Control of generation and die-out of chaotic phenomena are easily realized in simulations.