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

Development of a Comprehensive Simulation and Experiment Platform for Dynamically Positioned
Vessels
Changjun Hu1,2, Quan Shi1,2, Xiaoxian Guo1,2, Xin Li1,2*

1.

State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University,Shanghai, China
2. SJTU Yazhou Bay Institute of Deepsea Technology,Sanya, China

enough. As Fossen (2011) emphasized clearly, the simulation model
should be able to reconstruct the motion response of the real physicalsystem, where including the convincing environmental loads and thefluid-memory effects caused by the hydrodynamic coefficients.
Therefore, it is necessary to develop a comfortable and scalable DP
simulation environment in combination with hydrodynamic software.

ABSTRACTThe harsh ocean environment and operation condition requirements
requires high dynamic positioning (DP) performance of oceanengineering vessel. In order to improve the dynamic positioning
performance of vessels, hydrodynamic simulation test and wave tanktest are carried out. This paper focuses on the building of the simulation
framework and DP vessel model, including the function andimplementation of the components, and control system required toachieve DP capability on the corresponding model ship. Finally, theeffectiveness of the control system is verified by numerical simulationand experimental comparison.

In addition, the model experiment is an effective means to study theKEY WORDS: Dynamic positioning, Hydrodynamic simulation,
Experiment, Robot operating system
INTRODUCTION
The DP control system can continuously activate the vessel’s propellers
to balance the external disturbances (wind, waves, currents, etc.), andautomatically control the position/heading of vessel (Peng et al., 2021).
Recently, As the importance of the ocean becomes more and more
apparent, the field of naval architecture and ocean engineering has beendeveloped (Sørensen, 2011). The DP technology been vigorously
promoted, because of its broad application prospects, such as, offshore
platforms for rocket launch and recovery, etc.
In the control community, numerous advanced control algorithms areapplied into DP control, such as neural network (NN) (Hu et al., 2018),
adaptive control, adaptive dynamic programming (ADP) (Gao et al.,2021), reinforcement learning (RL) (Wen et al., 2019), etc. However,researchers seem to focus solely on the sophistication of the control
strategies, often ignoring the importance of the validation platform. A
simple mathematical model, which only can describe the main motionof the vessel, was utilized to both control design and simulation
verification in (Gao et al., 2021; Wang et al., 2021; Wen et al., 2019). It
is unreliable to simulate the actual physical motion of real ships in thisway, which also creates a huge barrier between advanced control theory
and practical control engineering. Brink and Chung (1981) mentionedthat the control of the ocean mining ship should be based on thepremise that the response simulation of pipeline movement is accurate

motion response of DP control for vessels. Based on the similarity
theory, researchers have carried out a lot of research work on the scalemodel experiments of DP control. Tannuri et al. (2010) carried out theexperiment of sliding mode control for a 1:150 scaled off-loadingtanker. Hu et al. (2020) carried out a 1:37 scaled model DP experimentof a novel twin-lift decommissioning operation. It is worth noting thatthe experimental conditions and equipment are not so easy to constructand obtain, and the field debugging of experiments is also very
complicated and difficult. Therefore, it is very meaningful to develop acomprehensive simulation and experiment platform.
Robot Operating System (ROS) is widely used in robots, unmanned
aerial vehicles (UAVs), autonomous surface vehicles (ASVs) and otherfields, such as the bionic robot dog "CyberDog" developed by Xiaomi,
the unmanned vehicle "Apollo" developed by Baidu, and the urban
waterways autonomous boat developed by MIT (Wang et al., 2019),
due to its distributed communication mechanism, simple datatransmission format, high flexibility and scalability. ROS is theapplicable carrier to implement a comprehensive simulation andexperimentation platform.
Inspired by the above observations, the main contribution of this paper
is to develop a comprehensive simulation and experimental platform.
The simulation environment is constructed in combination with thehydrodynamic programs, corresponding to the establishment of thepanel model, calculation of hydrodynamic coefficients andenvironmental loads of wind, waves and currents. The experimentalenvironment is constructed by a hardware framework based on thescaled model of real vessel. The ROS based control framework,
equipped with complete closed-loop control solution (i.e., PID control,reference filter, QP-based thrust allocation algorithm), has beendeveloped to be compatible with both the simulation environment andthe experimental environment.

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