Neural networks adaptive synchronization for four-dimension energy resource system with unknown dead zones

This article investigates the neural networks adaptive chaos synchronization problem using a four-dimensional energy resource demand supply system. The response system contains unknown uncertain nonlinearities and unknown dead zones. In the design, adaptive compensation technique is employed to solve the unknown information problems of the dead-zone slopes and breakpoints, and the neural networks are used to identify the unknown uncertain nonlinearities. Based on Lyapunov stability theory, a novel neural network adaptive synchronization method is proposed to make the states of two chaotic systems asymptotic synchronization. Numerical simulations are provided to further illustrate the effectiveness of the proposed approach.