Dynamic Positioning Control System Research Articles

Intelligent control algorithm for dynamic positioning control system

Introduction: The dynamic positioning system resists the environmental forces such as wind, wave and current acting on the ship through the thruster, so that the ship can remain in the position required by the sea level as much as possible, and the operation is very convenient. But its current dynamic positioning ability can not meet people's needs.Methods: A Kalman filter based on untracked optimization was designed for dynamic positioning control system. Then the intelligent control algorithm is designed for the dynamic positioning top-level controller and thrust optimal distribution controller, which occupy an important position in the system, namely the adaptive weight variation particle swarm optimization algorithm and thrust optimal distribution algorithm.Results and Discussion: The average position error of three degrees of freedom after filter processing is 1.53 m. Compared with other mainstream controllers, the mean root error of controllers based on adaptive weight variation particle swarm optimization in environment A and B is 2.295 and 1.8 m, respectively. In environment C, the controller based on thrust optimization allocation algorithm can get the optimal solution when the full rotary thruster reaches the 7 s and the channel thruster reaches the 4 s. The thrust exclusion zone is crossed at 46 s in environment D. In the dynamic positioning capability curve of the system, the experimental hull can balance the different environmental loads at all angles. In summary, the intelligent control algorithm proposed in this paper can effectively improve the positioning ability of the dynamic positioning control system and meet the needs of people for ship navigation today.

Finite‐time command filter control for dynamic positioning of remotely operated vehicles based on disturbance observer

AbstractTo deal with the problems of low positioning accuracy and poor stability caused by model parameter uncertainty and external disturbances in the remotely operated vehicle (ROV) dynamic positioning control system, the adaptive fuzzy control is combined with a disturbance observer to estimate the lumped disturbances and the error compensation mechanism is introduced to design the ROV dynamic positioning controller based on the finite‐time command filter. The combination of finite‐time command filter control and the backstepping method ensures that the positioning error converges to a smaller neighborhood near zero in finite time. The stability of the closed‐loop system is demonstrated according to the Lyapunov stability theory. The simulation results show that a 13% performance improvement over traditional backstepping methods is achieved by the designed controller, effectively suppressing system lumped disturbances and achieving fast and accurate positioning of the desired positions.

Dynamic positioning filter design applied on the small ship

This paper investigates a filter design method for dynamic positioning control system based on the wave peak frequency tracking algorithm. The wave peak frequency varies randomly with the sea condition, ship speed, wave direction and other factors. The performance of the filter is greatly affected by the real-time recognition of the wave peak frequency. The wave disturbance model is indicated as an autoregressive moving average (ARMA) model and the recursive extended least squares (RELS) algorithm is proposed to identify the wave peak frequency with the auxiliary model idea. A filter with the wave peak frequency tracker is constructed to evaluate the effectiveness of the proposed filter. Ultimately, simulation results show that the proposed filter can effectively track the wave peak frequency and can still effectively reduce the influence of waves on the ship control system when the peak frequency changes.

Automatic sea state estimation with online trust measure based on ship response measurements

The ever-changing sea state constitutes an integral part of situational awareness for vessels at sea. In this paper, a computationally efficient sea state estimation algorithm is extended by (1) automatic gain and tolerance calculation, and (2) trust measure for wave filtering condition identification. The resulting algorithm can run online in a control system without the need of user input, producing estimates of sea state parameters (significant wave height, peak wave frequency and main propagation direction), while simultaneously monitoring the quality of the estimates produced by identifying when wave filtering occurs. The algorithm is developed for application in dynamic positioning (DP) control systems, where the vessel has zero (or low) forward speed. The estimation method is tested with realistic values of measurement noise and sampling in terms of comprehensive time series simulations based on both long- and short-crested wave conditions. The sea state estimates correspond well with a state-of-the-art Bayesian estimation approach. This indicates that the simplifications made in order to enhance the computational speed, has not affected the quality of the estimates to any significant extent. The trust measure correctly identifies when wave filtering occurs in all simulated scenarios.

Safe Maneuvering Near Offshore Installations: A New Algorithmic Tool

Maneuvers of human-operated and autonomous marine vessels in the safety zone of drilling rigs, wind farms and other installations present a risk of collision. This article proposes an algorithmic toolkit that ensures maneuver safety, taking into account the restrictions imposed by ship dynamics. The algorithms can be used for anomaly detection, decision making by a human operator or an unmanned vehicle guidance system. We also consider a response to failures in the vessel’s control systems and emergency escape maneuvers. Data used by the algorithms come from the vessel’s dynamic positioning control system and positional survey charts of the marine installations.

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

This paper discusses the predefined practical finite-time (PPFT) dynamic positioning (DP) control problem for DP vessels subject to internal/external uncertainties. Those heterogeneity uncertainties are handled by a separate-type treatment approach. The finite-time (FT) DP control is fulfilled by a predefined FT function on the basis of a time-based generator (TBG). Under the dynamic surface control together with the TBG design framework, the convergence time and control accuracy of the DP system can be determined by the designer offline. Meanwhile, the virtual derivation and computational burden problems are dissolved by using a first-order filter and virtual parameter learning technique. To reduce mechanical wear, an event-triggering protocol between the control law and the actuator is built to reduce the operating frequency of the actuator. An event-triggered neuroadaptive PPFT control scheme is presented for DP vessels. The stability of the closed-loop DP control systems is validated via the Lyapunov theorem. Approach efficiency is confirmed by numerical examples.

Composite finite-time adaptive anti-disturbance control for dynamic positioning of vessels with output constraints

Considering the high-complexity of offshore engineering and the limited operating time window in practice, the demands on the accuracy and performance of the dynamic positioning (DP) control system have been increased dramatically. However, the uncertainties caused by hydrodynamic variations and unknown environmental disturbances will decay the DP control performance. This study proposes a fast and precise composite control strategy for the DP of vessels in the presence of uncertainties and disturbances. To compensate for the uncertainties and disturbances, a finite-time adaptive disturbance observer (FADO) is constructed, in which an improved adaptive neural network technique is integrated. Then, a composite finite-time adaptive control strategy with prescribed output constraints is proposed. It is proved that both the positioning error and the compensation error will converge in finite time, and the positioning error will never violate its constraints. In addition, a joint high-fidelity simulation framework is developed to simulate the motion response of vessels under the DP control strategies and wave loads, through cross-platform interaction between robot operating system (ROS) and hydrodynamic programs. Thus, the control performance and complex hydrodynamics can be further realistically simulated in time domain. Finally, numerical simulations and high-fidelity simulations illustrate the effectiveness and superiority of the proposed DP control strategy.

Hydrodynamic Forces of DP Jack-Up Leg when Operating in Vicinity of Seabed

_ Leg placement and removal are the two most critical operational modes for dynamically positioned jack-ups when working close to an offshore asset. Any positional deviation may lead to collision and damage to the asset. The industry operates with a weak link between the dynamic positioning (DP) system and the jacking system. Current DP systems operate without any sensors identifying the hydrodynamic force variations on the legs and spudcans, which vary between different leg and spudcan designs. When the spudcan is near to the sea bottom, the hydrodynamic force must be reported to avoid large positional deviations driven by the DP system. This article promotes a mechanism to measure these forces using Computational Fluid Dynamics (CFD) analysis to analyze the jack-up behavior, when the spudcan assembly is operating close to the sea bottom. Introduction A jack-up’s dynamic positioning (DP) control system requires minimum 23–30 minutes for the mathematical model to learn the vessel’s hydrodynamic behavior and response to the environment. Although when moving between locations, DP jack-up vessels provide time for the DP model to learn the hydrodynamic behavior, the spudcan that holds the vessel position and headings does not allow the mathematical model to learn. The residual current remains constant until the spudcan is in the seabed. As a result, the DP mathematical model-building process does not help the DP system to estimate the additional forces in the form of residual current. Soon after the spudcan detaches from the seabed, the vessel drift occurs because the vessel thrusters’ response need a rapid response of thrust and azimuth (directions). The DP system manufacturers currently use a sensorless approach to account for the hydrodynamic forces on the legs and spudcans to build a factor into the mathematical model. The jack-up DP system addresses two simultaneous forces on the legs. The leg element in the air is subject to aerodynamic effects and the leg and spudcan elements in the water are subject to hydrodynamic effects. DP systems currently use drag coefficients (Cd) to compute drag forces, however the hydrodynamic force variations during the complete lowering and raising processes are never completely considered. This weak link in the overall operation leads to positional error and is generally unrecognized by the vessel operators. The risk falls to DP officer and the jacking master to handle. The DP and jacking simultaneous operations mode (SIMOPS) may easily last between 15 and 90 minutes, depending on jacking speed, operational water depth, and field procedures, on approach to the asset. The area of operation is close to the asset, which increases the risk of collision with the asset. Most of the studies on jack-up vessels focus on impact force acting on the leg during touchdown or penetrations, such as Elkadi et al. (2014) and Kreuzer et al. (2014).

Performance of an Advanced Intelligent Control Strategy in a Dynamic Positioning (DP) System Applied to a Semisubmersible Drilling Platform

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.

Robust Position Control of an Over-actuated Underwater Vehicle under Model Uncertainties and Ocean Current Effects Using Dynamic Sliding Mode Surface and Optimal Allocation Control.

Underwater vehicles (UVs) are subjected to various environmental disturbances due to ocean currents, propulsion systems, and un-modeled disturbances. In practice, it is very challenging to design a control system to maintain UVs stayed at the desired static position permanently under these conditions. Therefore, in this study, a nonlinear dynamics and robust positioning control of the over-actuated autonomous underwater vehicle (AUV) under the effects of ocean current and model uncertainties are presented. First, a motion equation of the over-actuated AUV under the effects of ocean current disturbances is established, and a trajectory generation of the over-actuated AUV heading angle is constructed based on the line of sight (LOS) algorithm. Second, a dynamic positioning (DP) control system based on motion control and an allocation control is proposed. For this, motion control of the over-actuated AUV based on the dynamic sliding mode control (DSMC) theory is adopted to improve the system robustness under the effects of the ocean current and model uncertainties. In addition, the stability of the system is proved based on Lyapunov criteria. Then, using the generalized forces generated from the motion control module, two different methods for optimal allocation control module: the least square (LS) method and quadratic programming (QP) method are developed to distribute a proper thrust to each thruster of the over-actuated AUV. Simulation studies are conducted to examine the effectiveness and robustness of the proposed DP controller. The results show that the proposed DP controller using the QP algorithm provides higher stability with smaller steady-state error and stronger robustness.

Particle Swarm Optimization of a Passivity-Based Controller for Dynamic Positioning of Ships

Dynamic positioning (DP) control system is an essential module used in offshore ships for accurate maneuvering and maintaining of ship’s position and heading (fixed location or pre-determined track) by means of thruster forces being generated by controllers. In this paper, an interconnection and damping assignment-passivity based control (IDA-PBC) controller is developed for DP of surface ships. The design of the IDA-PBC controller involves a dynamic extension utilizing the coordinate transformation which adds damping to some coordinates to ensure asymptotic stability and adds integral action to enhance the robustness of the system against disturbances. The particle swarm optimization (PSO) technique is one of the the population-based optimization methods that has gained the attention of the control research communities and used to solve various engineering problems. The PSO algorithm is proposed for the optimization of the IDA-PBC controller. Numerical simulations results with comparisons illustrate the effectiveness of the new PSO-tuned dynamic IDA-PBC controller.

Systematic reliability analysis of the Dynamic Positioning (DP) control system for a deepwater drilling rig

ABSTRACT The system-level reliability analysis of DPS-3 Dynamic Positioning (DP) control system is proposed, which include both a qualitative failure modes and effects analysis (FMEA) and a quantitative analysis. The FMEA results show that the single point failure of main components of DP control system will not have any global effect on automatic positioning, however, the components involved with high Risk Priority Number (RPNs) are advised to include in the quantitative analysis. Markov model method is used to quantitatively analyze the reliability of DPS-3 control system. To simplify the process of state transition, paralleled Markov models are built to model the main and back-up control systems respectively, the reliability of the whole DP control system would be obtained with the failure rates of main and back-up subsystems. The results show that the proposed method can treat the complex architecture of the control system in an efficient manner.

Dynamic Positioning System Design for A Marine Vessel with Unknown Dynamics Subject to External Disturbances Including Wave Effect

In this paper, a new control system is proposed for dynamic positioning (DP) of marine vessels with unknown dynamics and subject to external disturbances. The control system is composed of a substructure for wave filtering and state estimation together with a nonlinear PD-type controller. For wave filtering and state estimation, a cascade combination of a modified notch filter and an estimation stage is considered. In estimation stage, a modified extended-state observer (ESO) is proposed to estimate vessel velocities and unknown dynamics. The main advantage of the proposed method is its robustness to model uncertainties and external disturbances and it does not require prior knowledge of vessel model parameters. Besides, the stability of the cascade structure is analyzed and input to state stability (ISS) is guaranteed. Later on, a nonlinear PD-type controller with feedforward of filtered estimated dynamics is utilized. Detailed stability analyses are presented for the closed-loop DP control system and global uniform ultimate boundedness is proved using large scale systems method. Simulations are conducted to evaluate the performance of the proposed method for wave filtering and state estimation and comparisons are made with two conventional methods in terms of estimation accuracy and the presence of uncertainties. Besides, comparisons are made in closed-loop control system to demonstrate the performance of the proposed method compared with conventional methods. The proposed control system results in better performance in the presence of uncertainties, external disturbance and even in transients when the vessel is subjected to sudden changes in environmental disturbances.

Fault-Tolerant Control for Dynamic Positioning Vessel With Thruster Faults Based on the Neural Modified Extended State Observer

A new fault-tolerant control (FTC) method based on the neural modified extended state observer (NMESO) is proposed for dynamic positioning (DP) vessel with thruster faults in this article. Through incorporating a compound orthogonal neural network (CONN) into the design process of the modified extended state observer (MESO), the NMESO is developed to estimate the uncertainties in the DP control system, such as the environmental disturbances and the unknown dynamics, as well as the thruster faults simultaneously without knowing any prior information of them. With the help of the accurate estimation of the total uncertainties by NMESO, a PD-like feedback controller is established to realize the FTC of the DP vessel toward the thruster faults. By utilizing the Lyapunov stability analysis, it is proved that all the error signals in the closed-loop cascade system formed by the NMESO and PD-like feedback controller are uniformly ultimately bounded (UUB) and the bounds could be arbitrarily small by choosing appropriate parameters. Simulation experiments on two typical thruster fault scenarios are carried out to validate the effectiveness and the performance of the proposed NMESO-FTC compared with the conventional ESO-FTC. The simulation results show the proposed approach has better fault-tolerant performance.

Design of Dynamic Positioning Control System for an ROV with Unknown Dynamics Using Modified Time Delay Estimation

Design of Dynamic Positioning Control System for an ROV with Unknown Dynamics Using Modified Time Delay Estimation

Joint estimation of vessel position and mooring stiffness during offshore crane operations

Abstract 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.

Backstepping Control Using Barrier Lyapunov Function for Dynamic Positioning Control System with Passive Observer

This paper presents a backstepping controller using barrier Lyapunov function (BLF) for dynamic positioning (DP) system. For safety reasons, the position and heading of DP ship are to be maintained in certain range. Thus, in this paper, a control law based on BLF and backstepping technique is proposed to limit the position and heading. The closed-loop system is proved stable in the sense of Lyapunov stability theories. In addition, since the velocities of ship are not measurable and the wave frequency (WF) motion is unavailable, a passive observer is adopted to estimate the velocities and the effect of WF motion. The simulation results show that the proposed controller can limit the position and heading of the vessel in a predefined range and verify the performance of the proposed controller and the passive observer.

A Finite-Time Output Feedback Control Scheme for Dynamic Positioning System of Ships

This paper develops a finite-time output feedback control scheme for dynamic positioning (DP) system of ships in the presence of unmeasured states of ships, unknown dynamic model parameters and unknown time-varying environment disturbances. A novel finite-time extended state observer (FTESO) is first proposed to simultaneously and precisely estimate the unmeasured states of ships, unknown dynamic model parameters, and unknown time-varying environment disturbances in finite time. Second, based on the outputs of FTESO, the terminal sliding mode (TSM) controller is designed to guarantee that the DP system can track the position and heading at desired values in finite time with precise performance. Then, it is proved that all error signals of the closed-loop DP control system can converge to zero in finite time by utilizing the homogeneous method and the Lyapunov stability theory. Finally, the numerical simulations on a supply ship are carried out to illustrate the effectiveness of the proposed finite-time output feedback control scheme.

Modern Dynamic Positioning (DP) System of ORP ‘Kormoran’ — Class Mine Destroyer

Abstract The paper presents the dynamic positioning system (DP), particularly its thruster allocation model, designed for ORP ‘Kormoran’, a Polish mine destroyer built for the Polish Navy in Remontowa Shipbuilding S.A. in Gdańsk. The ORP ‘Kormoran’ ship is the newest and best equipped minehunter ship in Europe. The main task of the new Polish mine destroyer is to search for, classify, identify and combat marine mines and improvised underwater explosives, recognize waterways, transport mines, deploy mines and provide remote control of self-propelled anti-mine platforms. The dynamic positioning control system of the ship presented in the article was constructed by Autocomp Management Ltd. from Szczecin, the only in Poland and one of the few producers of dynamic ship positioning systems in the world.

Robust adaptive NN control of dynamically positioned vessels under input constraints

Abstract A robust adaptive neural network (NN) control law is developed for dynamic positioning (DP) of vessels with unknown dynamics and unknown time-varying disturbances under input constraints through incorporating adaptive radial basis function (RBF) NNs, an auxiliary dynamic system and a robust control term into dynamic surface control method. The developed DP control law makes the DP closed-loop system be uniformly ultimately stable and the vessel's position and heading be maintained at the desired values with arbitrarily small errors. The advantages of the proposed control scheme are that: first, the developed DP control law does not require any priori knowledge of vessel dynamics and disturbances under input constraints, and prevents the presence of input constraints from degrading control performance and even destabilizing the DP control system; second, the developed DP control law compensates for not only unknown time-varying disturbances but also NN approximation errors for unknown vessel dynamics. Simulations on two supply vessels are conducted to exhibit the efficiency and control performance of the developed DP control law.