Thruster-assisted Position Mooring System Research Articles

A survey on modeling and control of thruster-assisted position mooring systems

This review presents a systematic summary of the state-of-the-art development of technological solutions, modeling, and control strategies of thruster-assisted position mooring (TAPM) systems. The survey serves as a starting point for exploring automatic control and real-time monitoring solutions proposed for TAPM systems. A brief historical background of the mooring systems is given. The kinematics and a simplified kinetic control-design model of a TAPM system are derived in accordance with established control methods, including a quasistatic linearized model for the restoring and damping forces based on low-frequency horizontal motions of the vessel. In addition, another two mooring line models, i.e., the catenary equation and the finite element method model, are presented for the purpose of higher-fidelity simulations. The basic TAPM control strategies are reviewed, including heading control, surge-sway damping, roll–pitch damping (for semisubmersibles), and line break detection and compensation. Details on the concepts of setpoint chasing for optimal positioning of a vessel at the equilibrium position are discussed based on balancing the mooring forces with the environmental loads and avoiding mooring line failure modes. One method for setpoint chasing is the use of a structural reliability index, accounting for both mean mooring line tensions and dynamic effects. Another method is the use of a lowpass filter on the position of the vessel itself, to provide a reference position. The most advanced method seems to be the use of a fault-tolerant control framework that, in addition to direct fault detection and isolation in the mooring system, incorporates minimization of either the low-frequency tensions in the mooring lines or minimization of the reliability indices for the mooring lines to select the optimal directions for the setpoint to move. A hybrid (or supervisory switching) control method is also presented, where a best-fit control law and observer law are automatically selected among a bank of control and observer algorithms based on the supervision of the sea-state and automatic switching logic.

Energy-efficient control of a thruster-assisted position mooring system using neural Q-learning techniques

ABSTRACT Thruster-assisted position mooring (PM) systems use both mooring lines and thrusters to maintain the position and heading of marine structures in ocean environments. In order to operate in an energy-efficient manner in moderate sea conditions, appropriate setpoints need to be found for the feedback controller, where the mooring system counteracts the main environmental loads and the thrusters reduce the oscillatory motion of the marine structure. The theory of reinforcement learning (RL) provides powerful and effective tools for designing decision making agents, which can optimise their behaviours based on the interactions with the environment. We propose several designs of decision making agent based on state-of-art neural Q-learning techniques. The simulation results show that the RL agents can successfully identify the optimal setpoints through the interaction with an unknown and stochastic environment, and double Q-learning and prioritised replay techniques prove to be fairly effective in shortening the learning time of the agent.

Optimal setpoint learning of a thruster-assisted position mooring system using a deep deterministic policy gradient approach

Thruster-assisted position mooring (PM) systems use both mooring lines and thrusters for station keeping of marine structures in ocean environments. To operate in an energy-efficient manner in moderate sea conditions, setpoints need to be appropriately chosen for the setpoint controller, so that the mooring system counteracts main environmental loads, while the thrusters reduce oscillatory motions of the marine structure. In this paper, reinforcement learning is used to design a decision-making agent for setpoint selection. In particular, a deep deterministic policy gradient (DDPG) approach is adopted with the powerful actor–critic architecture to continuously modify the setpoint setting at an optimal position. Extensive numerical experiments demonstrated that with the DDPG-based PM system, the intelligent agent is able to successfully identify the optimal positioning region in an unknown and stochastic environment, and the power consumption of the thrusters is maintained at a considerably low level.

Detection of mooring line failures using Dynamic Hypothesis Testing

This article proposes a novel methodology for the detection of mooring line breakage in thruster assisted position mooring (PM) systems, when no measurements of the tensions on the mooring lines are available. For dynamic positioning (DP) of marine vessels moored to the seabed via a turret-based spread mooring system, thrusters provide only complementary assistance to the mooring system, which is responsible for generating a large part of the forces and moments required for station keeping. However, in extreme weather conditions thruster assistance is essential to avoid mooring line failure. Once a mooring line is parted, the remaining lines must withstand an increase in the tension forces required to compensate for the lost tension in the ruptured line. This in turn may lead to a cascade breakage of the mooring lines. Hence, it is of paramount importance to detect any line breakage as soon as it occurs to compensate for the lost tension by proper use of DP thruster assistance. As a contribution to solving this problem, in this paper we propose a methodology that builds on Dynamic Hypothesis Testing (DHT) whereby a set of hypotheses are assessed, at each sampling time, using the measured inputs and outputs of the thruster assisted position mooring system. While the first hypothesis corresponds to the assumption that all mooring lines are intact, the remaining hypotheses are built assuming that a single, or multiple line breakage events have taken place. At each sampling time, the inputs and outputs to the system are used to generate the conditional probability of each hypothesis being true. The conditional probabilities are then used to evaluate which hypothesis is more probable to be compatible with the collected measurements. In addition, we find conditions for any pair of hypothesis to be distinguishable. Numerical simulations, carried out using a high fidelity nonlinear PM simulator, illustrate the efficiency of the proposed methodology.

Numerical and Experimental Study on the Influence of the Set Point on the Operation of a Thruster-Assisted Position Mooring System

Numerical and Experimental Study on the Influence of the Set Point on the Operation of a Thruster-Assisted Position Mooring System

Supervisory Control of Line Breakage for Thruster-Assisted Position Mooring System

Thruster-assisted position mooring (TAPM) is an energy-efficient and reliable stationkeeping method for deep water structures. Mooring line breakage can significantly influence the control system, and ultimately reduce the reliability and safety during operation and production. Therefore, line break detection is a crucial issue for TAPM systems. Tension measurement units are useful tools to detect line failures. However, these units increase the building cost of the system, and in a large portion of existing units in operation line tension sensors are not installed. This paper presents a fault-tolerant control scheme based on estimator-based supervisory control methodology to detect and isolate a line failure with only position measurements. After detecting a line break, a supervisor switches automatically a new controller into the feedback loop to keep the vessel within the safety region. Numerical simulations are conducted to verify the performance of the proposed technique, for a turret-based mooring system.

Robust adaptive control of a thruster assisted position mooring system

In this paper, robust adaptive control is developed for a thruster assisted position mooring system in the transverse direction. To provide an accurate and concise representation for the dynamic behavior of the mooring system, the flexible mooring lines are modeled as a distributed parameter system of partial differential equations (PDEs). The proposed control is applied at the top boundary of the mooring lines for station keeping via Lyapunov’s direct method. Adaptive control is designed to handle the system parametric uncertainties. With the proposed robust adaptive control, uniform boundedness of the system under the ocean current disturbance is achieved. The proposed control is implementable with actual instrumentations since all the signals in the control can be measured by sensors or calculated by using a backward difference algorithm. The effectiveness of the proposed control is verified by numerical simulations.

Modelling and Control of Thruster Assisted Position Mooring Systems for Ships

This paper adresses the mathematical modelling and control design of an automatic thruster assisted position mooring (POSMOOR) system. Such control systems are applied to anchored floating production offloading and storage vessels (FPSO's) and semi-subs. The POSMOOR controller is designed using model based control with a LQG feedback controller in conjunction with a Kalman filter. The controller design is in addition to the environmental loads accounting for the mooring forces acting on the vessel. This is reflected in the model structure and in the inclusion of new functionality.