STUDY OF CHAOS IDENTIFICATION AND CONTROL BASED ON WIENER MODEL
Chen Zeng · Information and Computation · 2001
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.