Data underlying the PhD thesis: Smart Offshore Heavy Lift Operations

Datacite citation style:
Ye, Jun (2020): Data underlying the PhD thesis: Smart Offshore Heavy Lift Operations. Version 1. 4TU.ResearchData. dataset.
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by Jun Ye orcid logo
This dissertation seeks to increase the intelligence of the offshore heavy lift operations and takes the first step towards autonomous heavy lift vessels. A smart system is designed to assist or replace human operators for both crane control and DP control during offshore construction. The proposed smart system is a high level controller which consists of three parts: the nonlinear observer-based robust switching DP controller that can maintain the vessel's position during offshore operation, which also takes the uncertainty into consideration during design process; the model-based mode detection system that can detect the switch of the construction modes and activate the switching of controllers; the nonlinear backstepping crane controller with command filtering controls the underactuated load position under the impact of the DP system. The three subsystems are integrated into one system with the detection system provides mode signal, the DP controller and the crane controller switch according to the mode signal.
  • 2020-06-19 first online, published, posted
4TU.Centre for Research Data
media types: application/octet-stream, application/x-matlab-data, application/zip, text/plain
  • CSC, 201607720003
TU Delft Faculty of Mechanical, Maritime and Materials Engineering, Department of Maritime and Transport Technology


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