Offshore platforms and windmills are constructed by assembling huge mechanical structures transported by heavy lift vessels. The construction process comprises two interconnected operations, the dynamic positioning (DP) of the vessel and the lifting of heavy loads. The DP system is commonly designed and tuned for the case that there is no load or for the case that the heavy load is free-hanging (mode 1). During the transition from the free-hanging to the case that the vessel is connected to a heavy load which is mounted to the platform (mode 2), the DP system may not be able to preserve the position stability of the vessel, jeopardizing human and system safety. The goal of this work is to design an intelligent monitoring system for the early detection of the transition between the two construction modes by adopting a nonlinear state estimation approach. Simulation results are used for illustrating the effectiveness of the proposed construction mode detection system.

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Position control for heavy-lift construction vessels is crucial for safe operation during offshore construction. During the various phases of a typical offshore construction assignment, considerable changes in the dynamics of the crane-vessel system occur. Operational hazard was reported if such interchanging dynamics are not properly handled. However, to date and the best of our knowledge, no systematic control solution is reported considering multiphase offshore construction scenarios. This article proposes a switched dynamical framework to model the interchanging phases and to formulate a comprehensive position control solution for heavy-lift vessels. Stability and robustness against modeling imperfections and environmental disturbances are analytically assessed. The effectiveness of the solution is verified on a realistic heavy-lift vessel simulation platform; it is shown that the proposed switched framework sensibly improves accuracy and reduces hazard compared with a nonswitched solution designed for only one phase of the construction scenario.

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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.

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Autonomous vessels have developed into a popular research area in both industry and academia. The application of autonomy in offshore and coastal engineering could offer a safe and efficient solution to offshore transportation and operation. However, the state of the art in research has focused on waterborne transportation. Very limited research activity has been in the field of autonomous heavy lift operations. Offshore heavy lift vessels are construction vessels with large scale hydraulic cranes. One challenge to achieve autonomous offshore heavy lifting is to make smart control systems for the subsystems involved in offshore construction work, and to integrate the systems in a coordinated framework. In this thesis, an smart control system consisting of three subsystems is proposed for safe smart offshore heavy lifting, which aims to replace or assist human operators during offshore heavy lift construction. To develop this smart system, a robust switching Dynamic Positioning (DP) controller to stabilize the position of the vessel, a nonlinear model-based mode detection system to detect the mode switching, and a backstepping crane tension controller to stabilize the load are designed.@en

Offshore structures with large mass are installed and removed by heavy lift vessels. During offshore constructions, two safety-critical interconnected operations take place, the dynamic positioning of the vessel and the lifting of the heavy structure by an immovable boom crane on the vessel. Existing studies on offshore boom crane control either neglect the structure (load) dynamics in sway and the vessel movement, or consider the boom angle of the crane controllable. In this paper, we present a control scheme for underactuated offshore structure, taking into consideration the impact of the dynamic positioning of the vessel on the physical load model. The proposed control scheme is designed following a backstepping control approach using command filtering to generate virtual control signals and their derivatives avoiding the analytic differentiation. Simulation results are obtained by applying the control scheme in a dynamic positioned vessel-load model showing that the controller is able to stablize the load position during the vessel dynamic positioning.

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With the growing demand of large-scale heavy lift vessels in the deep-sea offshore construction works, high performance of Dynamic positioning (DP) systems is becoming ever crucial. However, current DP systems on board of heavy lift vessels do not consider model uncertainty (typically arising from mooring forces). In this paper, an observer-based robust controller is designed that can tackle model uncertainty in hydrodynamic damping and mooring forces, environmental disturbances as well as can filter out the high-frequency vessel movement. Closed-loop system stability is analytically established in terms of uniformly ultimately boundedness. In addition, several key performance indicators are provided for tuning the performance of the controller. The effectiveness of the proposed control framework is studied in simulation with a crane-vessel system.@en

Offshore heavy lift vessels are designed for transporting, installing and removing offshore facilities. Previous studies have shown that the time-varying forces acting on the main crane may result in an unstable Dynamic Positioning (DP) control system, which adversely affects the safety of the heavy lifting operation. Solutions based on force feedforward control thus has been proposed, i.e., the low-frequency horizontal component of the crane force is forwarded to the DP controller or observer. Accurate estimation of the horizontal component of the crane force is essential for the feedforward solution, but it is extremely difficult to obtain it from a measurement due to its time-varying nature and the non-linear system dynamics stemming from the ship-environment interaction. Therefore, in this work, we focus on the estimation of the low-frequency crane force in the horizontal direction during loading and offloading stages of a heavy lift operation in various environmental conditions. To achieve this goal, a novel time-varying mooring stiffness term is introduced, which is included in the nonlinear passive observer of the vessel and used in a joint parameter-state estimator to estimate the horizontal crane force and vessel states. Afterward, simulations are performed to test the estimator in various environmental and loading conditions. The results indicate that an accurate estimation of the low-frequency horizontal component of the crane force can be achieved by measuring the position of the ship and the tension in the wires even in the presence of large parameter uncertainty.@en

Heavy lift crane vessels play an important role in offshore installations. Previous studies have shown that position control systems for these vessels can cause unstable positioning behavior during offshore construction assignments under specific conditions, e.g., change of environmental loads. Some control methods, such as crane force feedforward to the controller or the estimator, have been developed to improve the stability of the position control systems. However, these methods depend on the accurate estimation of the crane force and fast reaction of thrusters, which are difficult to obtain under working conditions. To make the positioning system stable, and compensate the controller for the changing crane stiffness and the systems onboard, two methods will be provided. One is to increase the flexibility of the system, while the other one is to increase the robustness. Two control methods, adaptive PID and H-infinity, are adopted and the results are compared. During simulations, the two controllers can dispose of crane modeling error and time delay of thrusters. Adaptive PID has a smaller variance under higher wind and wave load, while H-infinity controller has a larger clearance with the platform.

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