Abstract: An identification structure based on Wiener model is presented for chaotic system,and an extended kalman filter algorithm is used to quicken neural training.A novel nonlinear general predictive control paradigm is developed to control chaos,and a incremental gene is introduced to improve dynamic system performance.Simulation studies verify effectiveness of our proposed identification and control structure.