Design of adaptive controller for the chaotic neural network model reference

The design of adaptive controller for the chaotic neural network model reference is studied. Chaotic mechanism is introduced to normal BP algorithm, and the problem of local limit value for network is solved using global moving characteristic of chaotic mechanism is weight optimization. By training the adaptive controller and identifier for neural network model reference the control problem of complex nonlinear discrete system is completed. The steps of the algorithm are given. The simulation results show that the chaotic BP algorithm is more effective than the normal BP algorithm. The control precision and instantaneity are improved effectively.