A simple Adaptive Neural Fuzzy Design for Hyper-Chaos Control under External Disturbance

In this paper, an adaptive neural fuzzy control methodis proposed to control hyper-chaotic dynamic systems. Due to theinherent complexity of hyper-chaotic systems, the neural fuzzynetwork training architecture is described, which includes the typeand number of training inputs. The training data for the adaptiveneural fuzzy network is based on nonlinear control. In otherwords, the data of a nonlinear controller, which includes errorvectors and control input vectors, is used for neural fuzzy training.The numerical simulation results show that the proposed methodis suitable for controlling hyper-chaotic systems. After thecontroller design, an external disturbance is added to the model toevaluate the performance of the ANFIS controller. The time toreach zero error and the behavior of the control signal arediscussed, this can be an important issue in real-worldimplementation and manufacturing