H∞ control for chaotic system with cooperative weights neural network

In the paper, a novel type of neural network, referred to as neural network with cooperative weights is proposed to achieve H_∞ tracking performances for a class of unknown nonlinear dynamic system with external disturbance. By Lyapunov method, the overall closed-loop system is shown to be stable. In the article, the effect of both approximate error and external disturbance on the tracking error is attenuated to a prescribed lever ρ by adequately selecting the weight factor r ; the changes of weights are consistent by on-line adjusting the cooperative factor. Thus, the realization is easy. The simulation results of the Duffing chaotic system are given to confirm the control algorithm is feasible for practical application.