Robustifying Dynamic Positioning of Crane Vessels for Heavy Lifting Operation

Jun Ye; Spandan Roy; Milinko Godjevac; Vasso Reppa; Simone Baldi

doi:10.1109/JAS.2021.1003913

Volume 8 Issue 4

Apr. 2021

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2021 > 8(4): 753-765

Jun Ye, Spandan Roy, Milinko Godjevac, Vasso Reppa, and Simone Baldi, "Robustifying Dynamic Positioning of Crane Vessels for Heavy Lifting Operation," IEEE/CAA J. Autom. Sinica, vol. 8, no. 4, pp. 753-765, Apr. 2021. doi: 10.1109/JAS.2021.1003913

Citation:

Jun Ye, Spandan Roy, Milinko Godjevac, Vasso Reppa, and Simone Baldi, "Robustifying Dynamic Positioning of Crane Vessels for Heavy Lifting Operation," IEEE/CAA J. Autom. Sinica, vol. 8, no. 4, pp. 753-765, Apr. 2021. doi: 10.1109/JAS.2021.1003913

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Robustifying Dynamic Positioning of Crane Vessels for Heavy Lifting Operation

doi: 10.1109/JAS.2021.1003913

Jun Ye^1
,,
Spandan Roy^2
,,
Milinko Godjevac^3
,,
Vasso Reppa^1
,,
Simone Baldi^{4, 5
,
,}

1.
Department of Maritime and Transport Technology, Delft University of Technology, Delft 2628 CD, The Netherlands
2.
Robotics Research Center, International Institute of Information Technology Hyderabad, Hyderabad-500032, India
3.
Future Proof Shipping, Delft 3013 AL, The Netherlands
4.
School of Mathematics and School of Cyber Science and Engineering, Southeast University, Nanjing 210096, China
5.
Delft Center for System and Control, Delft University of Technology, Delft 2600 AA, The Netherlands

Funds: This work was supported by the Program of China Scholarship Council (CSC) (20167720003), the Special Guiding Funds Double First-Class (3307012001A), and the Natural Science Foundation of China (62073074)

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Author Bio:
Jun Ye received the B.Sc. in marine engineering at Shanghai Jiao Tong University in China (2009–2013), and the M.Sc. in marine engineering at Delft University of Technology, The Netherlands (2014–2016). She recently received the Ph.D. in maritime and transport technology from Delft University of Technology in 2020. Her research focuses on modelling, dynamic positioning, and autonomy of heavy lift vessels

Spandan Roy received the B.Tech degree in electronics and communication engineering from Techno India (Salt Lake), West Bengal University of Technology, India in 2011, the M.Tech. degree in mechatronics from Academy of Scientific and Innovative Research (AcSIR), India in 2013 and Ph.D. degree in control and automation from Indian Institute of Technology Delhi (IITD), India in 2018. He is currently Assistant Professor with Robotics Research Center, International Institute of Information Technology Hyderabad, India. Previously, he was Postdoc with Delft Center for System and Control, TU Delft, The Netherlands. He is Subject Editor of Int. Journal of Adaptive Control and Signal Processing. His research interests include artificial delay based control, adaptive-robust control, switched systems and its applications in Euler–Lagrange systems

Milinko Godjevac works as a Senior R&D Engineer at Future Proof Shipping and previously at Allseas Engineering b.v. His field of expertise is system integration of dynamic positioning and ship propulsion systems. He graduated in Naval Architecture at Belgrade University and obtained the Ph.D. title in marine engineering from Delft University of Technology

Vasso Reppa (M’06) has been an Assistant Professor in the Department of Maritime and Transport Technology, Delft University of Technology since 2018. She obtained the doctorate (2010) in electrical and computer engineering from the University of Patras, Greece. From 2011 to 2017, she was a Research Associate (now Research Affiliate) with the KIOS Research and Innovation Center of Excellence in Cyprus. In 2013, Dr. Reppa was awarded the Marie Curie Intra European Fellowship and worked as a Research Fellow in CentraleSupélec of the University Paris-Saclay, France from 2014 to 2016. She was a Visiting Researcher at Imperial College, the UK and at University of Newcastle, Australia in 2015 and 2016, respectively. Her research interests include distributed fault diagnosis and fault tolerant control, adaptive learning, observer-based estimation, and applications of autonomous systems in transport, smart buildings, and robotics

Simone Baldi (M’14–SM’19) received the B.Sc. in electrical engineering, and the M.Sc. and Ph.D. in automatic control engineering from University of Florence, Italy, in 2005, 2007, and 2011, respectively. He is Professor at School of Mathematics and School of Cyber Science and Engineering, Southeast University, with guest position at Delft Center for Systems and Control, TU Delft, where he was Assistant Professor. He was awarded Outstanding Reviewer for Automatica (2017). He is Subject Editor of Int. Journal of Adaptive Control and Signal Processing and Associate Editor of IEEE Control Systems Letters. His research interests are adaptive and learning systems with applications in unmanned vehicle systems
Corresponding author: Simone Baldi, e-mail: s.baldi@tudelft.nl
Received Date: 2020-10-07
Revised Date: 2020-11-15
Accepted Date: 2020-12-16

Available Online: 2020-12-21

Abstract

Abstract

Construction crane vessels make use of dynamic positioning (DP) systems during the installation and removal of offshore structures to maintain the vessel’s position. Studies have reported cases of instability of DP systems during offshore operation caused by uncertainties, such as mooring forces. DP “robustification” for heavy lift operations, i.e., handling such uncertainties systematically and with stability guarantees, is a long-standing challenge in DP design. A new DP method, composed by an observer and a controller, is proposed to address this challenge, with stability guarantees in the presence of uncertainties. We test the proposed method on an integrated cranevessel simulation environment, where the integration of several subsystems (winch dynamics, crane forces, thruster dynamics, fuel injection system etc.) allow a realistic validation under a wide set of uncertainties.
- Construction crane vessels,
- dynamic positioning system,
- offshore,
- robust control,
- uncertainty

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References(41)

References

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We solve the challenge of “robustification” of dynamic positioning (DP) for heavy lift operations
A new observer + controller DP method is given with stability guarantees
An integrated crane-vessel simulation environment is used for a realistic validation

Robustifying Dynamic Positioning of Crane Vessels for Heavy Lifting Operation

doi: 10.1109/JAS.2021.1003913

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