Fuzzy Feedback Control of Chaotic Systems via Lyapunov Exponents Placement

This work presents a nonlinear fuzzy feedback control approach for stabilizing the unknown chaotic systems via 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 fuzzy control law is designed to place the Lyapunov exponents of the system in the desired location to remove chaotic conduct. The proposed fuzzy Lyapunov exponents placement approach is robust to external uncertainties and provides a higher performance than the state of the art for stabilizing a Duffing oscillator circuit.