Synchronization Control Of Chaotic Financial Systems With Non-constant Demand Elasticity

There are many complex nonlinear phenomena in production,life,and social sciences,among which chaos is an important type.Chaotic systems have the characteristics of randomness,ergodicity,and initial value sensitivity,which are reflected in financial systems,where small changes in the system caused by internal factors and external disturbances can have significant economic impacts Therefore,the synchronization control of chaotic financial systems is particularly important,and its research has theoretical value and practical significance.This article mainly studies the synchronization control problem of chaotic financial systems with non constant demand elasticity Considering bounded the uncertainties of the system model and external disturbances,the sliding surface and Sliding mode control strategies based on Lyapunov stability theory are first proposed to verify that the synchronization error of the system converges to zero,and the effectiveness of the control method is verified by numerical simulation.Further,the radial basis function neural networks are introduced to realize the adaptive approximation of the unknown part of the model.Based on the finite time stability theory,the Sliding mode control law is designed to make the system converge to the sliding mode surface in limited time to achieve adaptive synchronization control.Finally,numerical simulation is used to verify the effectiveness of the control method.