Finite-Time Tracking Control of Autonomous Underwater Vehicle Without Velocity Measurements

Human-on-the-loop (HOTL) system is regarded as a promising technology to allow autonomous underwater vehicle (AUV) to track the most adequate target point as soon as possible. However, the unique characteristics of the underwater environment make it challenging to perform the tracking task. This article is concerned with a finite-time tracking control issue for AUV, subjected to unavailable velocity signals in the measurement side and uncertain model parameters in physical side. A HOTL system, including operator, buoys, AUV and sensors, is first provided to construct a cooperative tracking network. For such system, operator in surface control center decides the tracking mission based on all available data. Then, a buoy-assisted localization estimator is utilized by AUV to acquire its position, through which a fast terminal sliding mode observer is developed to estimate the velocity of AUV in finite time. With the estimated velocity information, an adaptive-nonsingular fast terminal sliding mode tracking controller is designed to drive AUV to the target point in finite time. For the proposed velocity observer and tracking controller, the signum and differential functions are employed together to improve the convergence speed and reduce the chattering. Besides that, the proposed solution can not only guarantee finite-time velocity observation, but also achieve finite-time tracking control. Finally, simulation and experimental results are both presented to verify the effectiveness.

Automated summary

This article focuses on the finite-time tracking control issue for AUV in a HOTL system, utilizing a cooperative tracking network with operator, buoys, AUV, and sensors. It includes a buoy-assisted localization estimator and a fast terminal sliding mode observer for finite-time velocity estimation, along with an adaptive-nonsingular fast terminal sliding mode tracking controller for driving AUV to the target point in finite time. The proposed solution improves convergence speed and reduces chattering by using signum and differential functions together.