Robust Adaptive Fuzzy Fractional Control for Nonlinear Chaotic Systems with Uncertainties

The control of nonlinear chaotic systems with uncertainties is a challenging problem that has attracted the attention of researchers in recent years. In this paper, we propose a robust adaptive fuzzy fractional control strategy for stabilizing nonlinear chaotic systems with uncertainties. The proposed strategy combined a fuzzy logic controller with fractional-order calculus to accurately model the system's behavior and adapt to uncertainties in real-time. The proposed controller was based on a supervised sliding mode controller and an optimal robust adaptive fractional PID controller subjected to fuzzy rules. The stability of the closed-loop system was guaranteed using Lyapunov theory. To evaluate the performance of the proposed controller, we applied it to the Duffing-Holmes oscillator. Simulation results demonstrated that the proposed control method outperformed a recently introduced controller in the literature. The response of the system was significantly improved, highlighting the effectiveness and robustness of the proposed approach. The presented results provide strong evidence of the potential of the proposed strategy in a range of applications involving nonlinear chaotic systems with uncertainties.

Automated summary

In this paper, a robust adaptive fuzzy fractional control strategy is proposed for stabilizing nonlinear chaotic systems with uncertainties. The strategy combines a fuzzy logic controller with fractional-order calculus to accurately model the system's behavior and adapt to uncertainties in real-time. The proposed controller based on a supervised sliding mode controller and an optimal robust adaptive fractional PID controller proved to outperform a recently introduced controller in the literature, improving the response of the system and demonstrating the effectiveness and robustness of the approach. The presented results provide strong evidence of the potential of the proposed strategy in a range of applications involving nonlinear chaotic systems with uncertainties.