Abstract
This paper presents a novel chaos stabilization method using fuzzy Lyapunov exponents placement. An adaptive neuro-fuzzy inference system (ANFIS) learning method is used to estimate the unknown parameters of the chaotic system, and a nonlinear fuzzy feedback controller is designed to place the Lyapunov exponents of the system in the desired location to remove chaotic conduct. The proposed approach is robust to external disturbances and provides a higher performance than the current chaos stabilization methods, as demonstrated by numerical examples.
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