Dual closed loop AUV trajectory tracking control based on finite time and state observer.

Area of Science:

• Robotics and Control Systems
• Ocean Engineering

Background:

• Autonomous Underwater Vehicles (AUVs) require precise three-dimensional trajectory tracking for mission completion.
• External disturbances (wind, waves, currents) and internal model uncertainties negatively impact AUV control performance, leading to slow convergence and output saturation.

Purpose of the Study:

• To develop an advanced control strategy for robust and accurate 3D trajectory tracking in AUVs.
• To address limitations of existing controllers, including slow convergence, output saturation, and model uncertainties.

Main Methods:

• Implemented a finite-time control method to accelerate controller convergence speed.
• Designed an auxiliary dynamic system to compensate for controller output saturation.
• Utilized a reduced-order extended observer to estimate and compensate for AUV model uncertainties and external disturbances in real-time.

Main Results:

• Simulations demonstrated superior convergence speed, control accuracy, robustness, and tracking performance compared to conventional methods.
• Experimental validation on the "sea exploration II" AUV in Suzhou Lake confirmed the algorithm's effectiveness.
• Achieved mean pitch and heading angle errors below 8 degrees, and mean depth error below 0.1 meters.

Conclusions:

• The proposed control strategy significantly enhances AUV trajectory tracking capabilities.
• The method effectively mitigates issues related to slow convergence, output saturation, and model uncertainties.
• The validated algorithm meets practical AUV navigation and task requirements.