Robust Receding Horizon Control of Dynamic Positioning Ship

This study is concerned with the robust H ∞ control problem for dynamic positioning (DP) ships based on sampled-data. Input delay approach is used to convert the sampled-data DP ship system to a system with time-varying delay. Adequate condition is derived to determine the system's asymptotical stability and establish H ∞ performance. Then sampled-data controller is obtained by means of linear matrix inequalities. Simulation results show that the proposed method and the designed controller for DP ships are effective in the existence of varying environment disturbance.

Following an investigation undertaken by the publisher, we have determined that this paper was accepted on the basis of a compromised peer review process. We hereby retract the paper. The corresponding author has been notified of the retraction. The retraction statement can be found here: https://doi.org/10.1520/JTE20269996. Aiming at the difficulty of the dynamic positioning process and trajectory control under the influence of complex disturbance, ship dynamic positioning control based on the nonlinear fuzzy algorithm is studied. By analyzing the composition and task of the ship dynamic positioning system, the nonlinear characteristics of the ship dynamic positioning system are obtained, and the ship dynamic pose is described by the combined coordinate system of the geodetic coordinate system, ship hull coordinate system, and multi-degree-of-freedom coordinate system. The dual fuzzy proportional, integral, derivative (PID) algorithm is applied to the point control and surface control and an approximate algorithm is adopted to calculate the target control parameters, so as to enhance the comprehensive effectiveness of ship hull nonlinear control results. The experimental results show that the control effect of this method is better and the heading angle control error is smaller. Meet the dynamic positioning ship control needs.

Performances of a set of control schemes for dynamic positioning (DP) are studied in this work; DP performance is essential for future developments of autonomous shipping technology. The linear and non-linear model predictive control (MPC and NMPC), the non-linear proportional integral and derivative (NPID) control, the sliding mode control (SMC), as well as the multi-resolution PID (MRPID) control schemes, are evaluated under two different sea conditions, namely, moderate and extreme seas. Matlab/Simulink models of a full-scale ship and its corresponding scaled model are used to benchmark the efficacy of the controllers. An unscented Kalman filter (UKF) is used to estimate vessel motions and to control low frequency (LF) motions while filtering out wave frequency (WF) motions. The tuning of the controllers is also taken into consideration. Of the five controller schemes, the NMPC shows the best ability to deal with extreme disturbances efficiently. Although all of the controllers were able to maintain the ship position under moderate conditions, only the NMPC and the MRPID controllers were able to stabilize the ship under extreme sea states. Findings from this research are expected to help operators of DP systems in choosing the most effective control scheme for different sea conditions. In addition, the results are supportive of further control system development for dynamic positioning and autonomous operations of ships and offshore platforms.

This paper presents a novel Lyapunov-based model predictive control (LMPC) framework for the dynamic positioning (DP) control of autonomous underwater vehicles (AUVs). Due to the optimization essential, LMPC can explicitly consider the practical constraints on the real system and generate the best possible DP control. Meanwhile, taking advantage of the existing Lyapunov-based DP controller, a contraction constraint can be imposed to the formulated optimal control problem, which guarantees the closed-loop stability. In addition, the thrust allocation (TA) subproblem can be solved simultaneously with LMPC-based DP control. The most widely used proportional-integral-derivative (PID) type DP controller is investigated for the construction of the contraction constraint. Sufficient conditions that ensure the recursive feasibility hence closed-loop stability of the LMPC are derived. An arbitrarily large region of attraction can be claimed. The proposed LMPC framework serves as a bridge connecting modern optimization technique and the conventional control theory, which enables a direct integration of online optimization into control system design to improve the control performance. Simulation results on the Saab SeaEye Falcon open-frame ROV/AUV reveal the effectiveness of the proposed method.

Event-triggered neuroadaptive predefined practical finite-time control for dynamic positioning vessels: A time-based generator approach

Among most of industrial control system, the time delay generally exists due to the actuator's own mechanical properties, which will produce the problem of force response delayed. And actuators are the main elements in Dynamic Positioning (DP) ships, thus it is necessary to solve the problem about time delay. Considering of the environmental disturbances, output response could be delayed and the environmental disturbances can't be compensated in time, it will cause the bad control effect, even oscillation. This paper proposed the adaptive fuzzy control, and it is a kind of adaptive active control. This control method can solve the time delay of passive control well. Combined with the fuzzy control, the adaptive control law is designed based on the backstepping method. Thus the adaptive fuzzy control for time-delay is verified by MATLAB simulating results.

This paper presents a globally contracting controller for regulation and dynamic positioning of ships, using only position measurements. For this purpose a globally contracting observer which reconstructs the unmeasured states is constructed. The observer produces accurate estimates of position, slowly varying environmental disturbances (bias terms) and velocity. The estimates are automatically adjusted to the present sea state by gain-scheduling the wave model parameters in the observer. Finally, the estimates are used in a nonlinear PID control law and the stability proof of the observer-controller is based on a separation principle for contracting systems in cascade.

The drilling of the Mohole, a hole through the crust of the earth, will be undertaken from a drilling ship operating in true oceanic depths. Because anchoring at these depths is infeasible, the position of the drilling ship above the hole in the ocean floor must be controlled by surface propulsion units. This concept is called "dynamic positioning." An experimental drilling program was undertaken in 1961 to determine, among other engineering factors, whether dynamic positioning was feasible. A special integrated control system was developed for four steering propellers which permitted a single operator to control the position of the experimental drilling ship, CUSS I. The system operated successfully for a month at sea and proved that dynamic positioning was not only feasible but entirely practical. This system is expected to form the basis for the control of future waterborne vehicles for geophysical and oceanographic research.

Oil drilling and extraction platforms are currently being used in many offshore areas around the world. Whilst those operating in shallow seas are secured to the seabed, for deeper water operations, Dynamic Positioning (DP) is essential for the platforms to maintain their position within a safe zone. Operating DP requires intelligent and reliable control systems. Nearly all DP accidents have been caused by a combination of technical and human failures; however, according to the International Marine Contractors Association (IMCA) DP Incidents Analysis, DP control and thruster system failures have been the leading causes of incidents over the last ten years. This paper will investigate potential operational improvements for DP system accuracy by adding a Predictive Neural Network (PNN) control algorithm in the thruster allocation along with a nonlinear Proportional Integral derivative (PID) motion control system. A DP system’s performance on a drilling platform in oil and gas deep-water fields and subject to real weather conditions is simulated with these advanced control methods. The techniques are developed for enhancing the safety and reliability of DP operations to improve the positioning accuracy, which may allow faster response to a critical situation during DP drilling operations. The semisubmersible drilling platform’s simulation results using the PNN strategy show improved control of the platform’s positioning.

A Thrust Allocation Algorithm considering Dynamic Positioning and Roll Damping Thrust Demands using multi-step Quadratic Programming

Comparing Controllers for Dynamic Positioning of Ships in Extreme Seas

Small Autonomous Surface/Underwater Vehicles (S-ASUVs) are gradually attracting attention from related fields due to their small size, low energy consumption, and flexible motion. Existing dynamic positioning (DP) control approaches suffer from chronic restrictions that hinder adaptability to varying practical conditions, rendering performance poor. A new three-dimensional (3D) dynamic positioning control method for S-ASUVs is proposed to tackle this issue. Firstly, a dynamic model for the DP control problem considering thrust allocation was established deriving from dynamic models of S-ASUVs. A novel Lyapunov-based model predictive control (LBMPC) method was then designed. Unlike the conventional Lyapunov-based model predictive control (LMPC), this study used multi-variable proportional–integral–derivative (PID) control as the secondary control law, improving the accuracy and rapidity of the control performance significantly. Both the feasibility and stability were rigorously proved. A series of digital experiments using the S-ASUV model under diverse conditions demonstrate the proposed method’s advantages over existing controllers, affirming satisfactory performances for 3D dynamic positioning in complex environments.

A literature survey of broken ice-structure interaction modelling methods for ships and offshore platforms

In this paper, the situation of dynamic positioning ships operated in some special speed is considered, and the nonlinear ship motion model of three degrees of freedom that contains nonlinear velocity term is established. Based on active disturbance rejection theory, a kind of active disturbance rejection decoupling control method is applied in ship dynamic positioning system; compared with the closed-loop system with PID controllers, the simulation results show that ADRC possesses an advantage in decoupling and anti-interference.KeywordsDynamic positionADRCDecoupling

Stochastic stability algorithm is designed using Backstepping method on dynamic positioning system model. The dynamic positioning system is modeled as a stochastic differential equation. The design process and numerical solution are given. Simulation shows that the method is effective.