Tracking control for uncertain chaotic systems using dynamic neural networks
Tan Woan Wen, Wang Yao-nan · Kongzhi yu juece · 2004
An adaptive tracking controller based on dynamical neural network identifier for uncertain nonlinear chaos systems is presented. The weights of the dynamic neural networks used as neuro-identifier can be on-line (adjusted) through the usage of the sliding mode technique. An optimal controller via dynamic neural network model is (presented) to perform reference trajectory following control for chaotic system.The identification error and the (trajectory) tracking error are analyzed and guaranteed to be bounded. The experiment results of the chaotic system given by Lorenz equation show the effectiveness of the method.