Antidisturbance Control for AUV Trajectory Tracking Based on Fuzzy Adaptive Extended State Observer

Area of Science:

• Robotics
• Control Systems Engineering
• Artificial Intelligence

Background:

• Autonomous Underwater Vehicles (AUVs) face significant challenges including external disturbances, parameter uncertainties, measurement noise, and actuator faults.
• Existing control strategies often struggle to maintain performance under these complex and uncertain operating conditions.

Purpose of the Study:

• To propose an output-feedback fuzzy adaptive dynamic surface controller (FADSC) integrated with a fuzzy adaptive extended state observer (FAESO) for AUV systems.
• To enhance the adaptability, robustness, and tracking accuracy of AUVs in challenging environments.

Main Methods:

• Development of a dynamic model for AUV systems incorporating disturbances and uncertainties.
• Design of a Fuzzy Adaptive Extended State Observer (FAESO) to estimate system states and lumped disturbances, while mitigating measurement noise.
• Implementation of a Fuzzy Adaptive Dynamic Surface Controller (FADSC) using FAESO estimations, with fuzzy logic tuning observer bandwidth and controller time constants.
• Analysis of asymptotic stability using Lyapunov's direct method.

Main Results:

• The proposed FAESO effectively estimates system states and disturbances while reducing the impact of measurement noise.
• The FADSC demonstrates superior performance in tracking accuracy, robustness against external disturbances, parameter uncertainties, and even unmodeled actuator faults.
• Comparative simulations confirm the advantages of the proposed method over existing approaches in terms of performance and energy consumption.

Conclusions:

• The integration of fuzzy adaptive observers and controllers provides a robust and adaptive solution for AUV control.
• The proposed FADSC-FAESO framework significantly improves AUV performance and reliability in complex operational scenarios.
• This approach offers a promising direction for advanced autonomous underwater vehicle control systems.