Department of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China; College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
Abstract:
A novel adaptive control for uncertain nonlinear chaotic system is presented. A dynamical neural networks is used to perform ‘black box' identification. Based on the identifier, the state feedback control is employed to drive the unknown chaotic system toward the desired target. Simulations show the derived control via the neuro-identifier turns out to be very effective.