Proceedings of the Thirty-second (2022) International Ocean and Polar Engineering Conference
Shanghai, China, June 5–10, 2022
Copyright © 2022 by the International Society of Offshore and Polar Engineers (ISOPE)
ISBN 978-1-880653-81-4; ISSN 1098-6189

www.isope.org

Dynamic Positioning Control of Unmanned Surface Vehicle for Core Sampling:
Correction Input Using Neural Network
Shun Fujii1, Junichiro Tahara1, Shoichiro Baba2, Yukihisa Sanada3
1Tokyo University of Marine Science and Technology, Tokyo, Japan
2Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan
3Japan Atomic Energy Agency, Fukushima, Japan

respectively (Fig. 3). Using these thrusters, we were able to move to atarget position and maintain the heading angle and position within acircle of radius 6 [m] by sliding mode control (Fujii et al., 2021).

ABSTRACT
We have been studying an USV for measuring radiation in the sea near
the Fukushima Daiichi Nuclear Power Plant. The USV is equipped witha core sampler and a sensor to measure radiation on the seafloor, and itis necessary to maintain the position of the USV when using thesedevices. In the sea area where the USV is used, there are disturbancessuch as wind, current, waves, which make it difficult to maintain theposition. To solve this problem, we devised a position control methodthat dynamically adds correction inputs using a neural network.

However, in the future, we plan to use the USV not only in the harbors
where we have conducted experiments so far, but also in the open ocean
where disturbances such as winds, currents, and waves are more severe.
In such a case, the conventional method will be able to move the target
position and maintain the angle without any problem, but it is highly
possible that it will not be able to maintain the position, which is the mostsensitive to disturbance.

KEY WORDS:

unmanned surface vehicle; dynamic positioningcontrol; neural network

In order to solve the above problem, we decided to add a correction input
to the conventional method to counter the large disturbance. The
correction input needs to be changed dynamically depending on the sizeand direction of the disturbance at that time. Therefore, we thought ofusing a neural network to calculate the correction input in real time, sothat it would be added according to the error in the switching line of thesliding mode control. Using a neural network, the correction input canbe calculated automatically using the measured values at that time. In
this study, we devise a control method to add the correction input by theneural network and verify the control method.

INTRODUCTION
We have been studying an unmanned surface vehicle (USV, Fig. 1) tomeasure radiation contained in mud on the seafloor (Sanada et al., 2021;
Kato et al., 2021). The location where the USV will be used is
Matsukawaura, Soma City, Fukushima Prefecture, where radioactive
materials were discharged and deposited due to the accident at theFukushima Daiichi Nuclear Power Plant in 2011. The measurement ofradiation at this location is an important mission to investigate the effectsof the nuclear accident.

The structure of this paper is as follows. In section 2, the USV to becontrolled is described. In section 3, the mathematical model used forcontrol design and simulation is described. In section 4, the proposed
control method is described. In section 5, the simulation results of thecomparison between the conventional and proposed control methods arepresented. In section 6, the result of the sea trial is described. In section
7, the conclusion is present.

The USV is 6 meters long, weighs 4 tons in the air, and is equipped witha core sampler to collect mud from the seafloor and a sensor to measureradiation. The core sampler and sensor can be lowered from the moonpool in the center of the hull to the seafloor using a winch (Fig. 2). The
wire also serves as a communication cable. If the USV rotates or moves
when these devices are lowered to the seafloor, these devices may not
operate properly because the core sampler may fall over on the seafloor
or communication failure may occur due to the load on the wire.
Therefore, it is necessary to maintain the heading angle and position ofthe USV after lowering these devices to the seafloor.

USV
The specifications of the USV are shown in Table 1. The USV isequipped with GPS and IMU as sensors. GPS measures the position andIMU measures the angle, and the measured values are used for feedback
control. The USV has a rudder in addition to the thruster as an actuator,
but we do not use the rudder in this study because we only consider theposition-maintaining motion.

The USV has two main thrusters in the center that provide propulsion in
the forward and backward directions, and four sub-thrusters in the bow
and stern that provide propulsion in the left and right directions,1014