Chaos prediction and inverse system control based on fuzzy-neural network

The Sugeno fuzzy-neuron network (FNN) is employed to establish the inverse system model of chaotic systems, and the inverse system method is used to control chaos. The characteristics of this method is learning the motion principles of the chaotic system by FNN and controlling chaos effectively with learned principles instead of establishing the exact analytical model of the chaotic system. Moreover, this method does not require the control objective to be a stationary point or a periodic trajectory. Theoretical analysis and simulations with Logistic and Henon mappings prove that this method is effective.