Real-time HILS-validated model-free control for AUVs using time-delay adaptive fuzzy nonsingular fast terminal...

Area of Science:

• Robotics
• Control Systems Engineering
• Marine Technology

Background:

• Autonomous Underwater Vehicles (AUVs) require robust control for navigation and task execution in dynamic environments.
• Traditional sliding mode control methods often suffer from chattering and model dependency.
• Time Delay Control (TDC) offers model-free disturbance rejection, while nonsingular fast terminal sliding mode control (NFTSMC) provides fast convergence and singularity avoidance.

Purpose of the Study:

• To develop a novel adaptive fuzzy nonsingular fast terminal sliding mode control (AFNFTSMC) integrated with time delay control (TDC) for AUVs.
• To enhance the robustness and tracking performance of AUVs against nonlinear dynamics and external disturbances.
• To ensure global stability and finite-time convergence of the control system.

Main Methods:

• Integration of Time Delay Control (TDC) for real-time estimation and compensation of system uncertainties and disturbances without requiring an accurate model.
• Implementation of an adaptive fuzzy logic system to mitigate the chattering phenomenon common in sliding mode control, ensuring smooth control inputs.
• Application of Lyapunov stability theory to rigorously prove the global stability and finite-time convergence properties of the proposed AFNFTSMC-TDC scheme.

Main Results:

• The proposed AFNFTSMC-TDC controller demonstrates enhanced robustness and superior tracking performance compared to conventional methods.
• The integrated fuzzy logic system effectively suppresses control signal chattering, leading to smoother AUV motion.
• Numerical simulations using the Delphin2 AUV model confirm the controller's effectiveness in handling external disturbances and achieving finite-time convergence.

Conclusions:

• The novel AFNFTSMC-TDC scheme provides an effective solution for robust and precise control of AUVs.
• The controller's model-free nature and adaptive capabilities make it suitable for real-world AUV applications with unpredictable environmental conditions.
• The validated stability and performance highlight the potential of this control strategy for advancing AUV autonomy.