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The harsh ocean environment and complex operating conditions require high dynamic positioning (DP) capability of offshore vessel. The design, development, and performance evaluation of DP systems are generally carried out through numerical simulations or scale-model experiments. Simulations are a convenient and inexpensive alternative to experiments, but may not be practical due to the simplicity of the model. Thus, this paper presents a hybrid simulation and experiment test platform for DP vessels. For realistic calculating environmental loads and kinematic responses in hydrodynamic simulations, the 6DoF model is used to describe the dynamic response of DP vessels, considering fluid-memory effects and frequency-dependent hydrodynamic parameters. In the experiments, similarity theory based on the same Froude number is used to ensure consistency of the control parameters with the simulations, reducing the time for experimental tuning. Finally, a case study of a DP shuttle tanker is used to verify the credibility of the test platform. [ABSTRACT FROM AUTHOR]

The goal of this paper is to establish a motion control system for unmanned surface vehicles (USVs) that enables point-to-point tracking and dynamic positioning. This includes the heading control and path following control of USVs. A hardware and software platform for USVs using microcontrollers is designed. This paper presents the construction of a kinematics and dynamics model for an unmanned catamaran. The motion process is divided into two segments. In the target point tracking segment, the heading coordinate system and the ship coordinate system are established. Based on these, a control method using differential steering to track the desired yaw angle is designed to improve the tracking efficiency. And the accuracy of heading keeping and path following is improved by combining the cascade PID controller. In the dynamic positioning segment, a self-adjusting mechanism is designed, thereby enhancing the flexibility of thrust distribution and improving the accuracy of the USV's positioning retention in wind and wave environments. Finally, experimental validation is carried out to verify the effectiveness of the design proposed in this paper by issuing control commands and saving the return data through the upper computer, and then analyzing the return data with MATLAB (R2022b, MathWorks, Natick, MA, USA). [ABSTRACT FROM AUTHOR]

This paper presents a dynamic positioning control scheme for offshore drilling platforms using the equivalent-input-disturbance (EID) method with separated observers. The scheme incorporates observer-based disturbance compensation, wave-filtering state estimation, input transformation, and state feedback control to achieve robust control performance. The main contributions include the design of an EID scheme with separated observers, enabling enhanced disturbance-rejection performance, incorporating a notch filter in the EID estimator to reduce energy loss, and giving an observer tuning scheme to achieve a balanced performance between disturbance rejection and wave filtering. Simulation results demonstrate the effectiveness of the proposed scheme. This work provides valuable insights into designing stable and efficient dynamic positioning systems for offshore drilling platforms. [ABSTRACT FROM AUTHOR]

This paper proposes a novel tube model predictive control approach for dynamic positioning of autonomous underwater vehicles with state and input constraints. The cost function is selected as a mixture of weighted 1-norms and ∞-norms of states and inputs, which can be reconstructed into linear summation form. Specially, a method is presented to calculate the weighted matrix of the terminal cost so that closed-loop stability is achieved. The proposed control problem can be solved by linear programming, which provides high computational efficiency. Experimental results on “UVIC-I” AUV are conducted to validate the viability and validity of the presented method. [ABSTRACT FROM AUTHOR]

Technological advancements and the expanding scope of offshore dynamic positioning (DP) applications introduce new challenges in terms of safety and risk control. This paper provides an overview of a proposed methodology for reliability and risk analysis in the context of DP operations. Firstly, two typical DP operation contexts are discussed. Subsequently, a comprehensive survey is conducted to assess the reliability analysis methodologies applicable to DP systems, encompassing techniques such as Failure Mode and Effects Analysis (FMEA), fault tree analysis, Markov models, and Bayesian networks, which are employed to evaluate the technical and human reliability of DP Class 2 and Class 3 systems. Finally, the paper concludes with a discussion of future research directions and challenges pertaining to reliability analysis and risk management in DP operations. [ABSTRACT FROM AUTHOR]

The robust adaptive anti-disturbance fault-tolerant control strategy for the dynamic positioning (DP) system of ships is built on the disturbance observer, the adaptive fault observer with the vectorial backstepping approach. The disturbance observer is constructed to estimate the first-order Markov disturbances. The adaptive fault observer with the projection algorithm is designed to estimate partial thruster faults. By employing the vectorial backstepping method, the robust adaptive anti-disturbance fault-tolerant control law is developed to simultaneously achieve the disturbance compensation and the partial thruster fault tolerant. It is demonstrated using the Lyapunov functions that the robust adaptive anti-disturbance fault-tolerant controller can maintain the DP of the ship's position and heading to achieve the desired value, while guaranteeing the global stability of all signals in the DP closed-loop control system. Finally, different cases in the unknown ocean disturbance environment demonstrate the effectiveness of the robust adaptive anti-disturbance fault-tolerant control strategy. [ABSTRACT FROM AUTHOR]

Thrust allocation (TA) plays a critical role in the dynamic positioning system (DPS). The task of TA is to allocate the rotational speed and angle of each thruster to generate the generalized control forces. Most studies take TA as a single-objective optimization problem; however, TA is a multi-objective optimization problem (MOP), which needs to satisfy multiple conflicting allocation objectives simultaneously. This study proposes an improved multi-objective particle swarm optimization (IMOPSO) method to deal with the non-convex MOP of TA. The objective functions of reducing the allocation error, and minimizing the power consumption and the tear-and-wear of thrusters under physical constraints, are established and solved via MOPSO. To enhance the global seeking ability, the improved mutation strategy combined with the roulette wheel mechanism is adopted. It is shown through test data that IMOPSO converges better than multi-objective algorithms such as MOPSO and nondominated sorting genetic algorithm II (NSGA-II). Simulations are conducted for a DP ship with two propeller–rudder combinations. The simulation results with the single-objective PSO algorithm show that the proposed IMOPSO algorithm reduces thrust allocation errors in the three directions of surge, sway, and yaw by 48.48%, 39.64%, and 15.02%, respectively, and reduces power consumption by 44.53%, which demonstrates the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

As a substitute for human arms, underwater vehicle dual-manipulator systems (UVDMSs) have attracted the interest of global researchers. Visual servoing is an important tool for the positioning and tracking control of UVDMSs. In this paper, a reinforcement-learning-based adaptive control strategy for the UVDMS visual servo, considering the model uncertainties, is proposed. Initially, the kinematic control is designed by developing a hybrid visual servo approach using the information from multi-cameras. The command velocity of the whole system is produced through a task priority method. Then, the reinforcement-learning-based velocity tracking control is developed with a dynamic inversion approach. The hybrid visual servoing uses sensors equipped with UVDMSs while requiring fewer image features. Model uncertainties of the coupled nonlinear system are compensated by the actor–critic neural network for better control performances. Moreover, the stability analysis using the Lyapunov theory proves that the system error is ultimately uniformly bounded (UUB). At last, the simulation shows that the proposed control strategy performs well in the task of dynamical positioning. [ABSTRACT FROM AUTHOR]

Dynamic positioning systems ensure additional position accuracy in different operations in the maritime industry, such as shuttling, drilling, diving, pipe laying, and others. Although they are known to be robust systems, they are not exempt from failures leading to incidents, among which we can find human-related incidents. This research analyzes 62 human-related dynamic-positioning incidents and aims to determine which segment in the dynamic positioning system influences these occurrences by applying binary logistic regression modeling techniques in the test sample and validating the results using a control sample. The results indicate that thrusters have the most significant influence on human-related incidents; however, not all DP operations are affected in the same measure. By stratifying the database and considering the different operations in progress, it is noted that human-related incidents while drilling operations are in progress are effectively influenced using a higher percentage of thrusters online. [ABSTRACT FROM AUTHOR]

A Dynamic Positioning system automatically maintains both the position and heading of a vessel by using its thrusters in the presence of external disturbances. This goal is ensured by a controller that compensates for the environmental disturbances and computes the proper set-points for each actuator. The core of such a system is composed of force and thrust allocation modules that tailor the required forces and moment over the available actuators. The propulsion systems used are often over-actuated and the thrust allocation algorithm implies an infinite number of solutions since it is impossible to solve analytically the problem. Over the years efforts from the research community dealt with the optimization in terms of accuracy, energy consumption, and maintenance with innovative allocation strategies were investigated. However, no publications or rules indicate the procedure for the evaluation of exhaust gas emission during dynamic positioning operations. For such a reason, the paper aims to develop an optimization procedure that includes an ad-hoc objective function with relative non-linear constraints for the thrust allocation logic that tends to minimize the actuators' thrust. The procedure accounts for non-linear hydrodynamic effects on the thrust generation, including thruster-thruster and thruster-hull interactions, to obtain the most realistic results as possible. Moreover, following the IMO suggestions, the production of greenhouses gases emissions is evaluated in probabilistic terms. The proposed approach provides indicators in terms of yearly operability, fuel consumption, and environmental footprint during dynamic positioning operations that could be used for proper decisions in ship deployment. [ABSTRACT FROM AUTHOR]

To 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. [ABSTRACT FROM AUTHOR]

Real-time acquisition of location information for agricultural robotic systems is a prerequisite for achieving high-precision intelligent navigation. This paper proposes a data filtering and combined positioning method, and establishes an active screening model. The dynamic and static positioning drift points of the carrier are eliminated or replaced, reducing the complexity of the original Global Navigation Satellite System (GNSS) output data in the positioning system. Compared with the traditional Kalman filter combined positioning method, the proposed active filtering–Kalman filter algorithm can reduce the maximum distance deviation of the carrier along a straight line from 0.145 m to 0.055 m and along a curve from 0.184 m to 0.0640 m. This study focuses on agricultural robot positioning technology, which has an important influence on the development of smart agriculture. [ABSTRACT FROM AUTHOR]

Offshore drilling platforms are exposed to wind, waves, currents, and other unknown disturbances. Accurately estimating and rejecting these disturbances is the key to ensuring reliable station-keeping of the platforms. In this study, a novel dynamic positioning method using an improved equivalent-input-disturbance (EID) approach is proposed for offshore drilling platforms. An improved EID estimator is employed to estimate and suppress unknown disturbances, significantly enhancing the disturbance-rejection performance of the dynamic positioning system. The input channels are decoupled through linear transformation, and the parameter tuning process of the observer and controller is optimized, thus improving system performance. The bounded-input bounded-output stability of the closed-loop system is proved. This study provides insights into the design of dynamic positioning systems for offshore drilling platforms. • Effective disturbance compensation for offshore drilling platforms. • Input channel linear transformation improves disturbance-rejection performance. • Simplified parameter design using linear matrix inequalities. • Nonlinear state feedback and observer gains ensure the global stability of the system. [ABSTRACT FROM AUTHOR]

The development of dynamic positioning (DP) algorithms for an unmanned surface vehicle (USV) is attracting great interest, especially in support of complex missions such as sea rescue. In order to improve the simplicity of the algorithm, a DP algorithm based on its own path following control ability is proposed. The algorithm divides the DP problem into two parts: path generation and path following. The key contribution is that the DP ability can be realized only by designing the path generation method, rather than a whole complex independent DP controller. This saves the computing power of the USV onboard computer and can effectively reduce the complexity of the algorithm. In addition, the fixed-time LOS guidance law is designed to improve the convergence rate of the system state in path-following control. The reasonable selection of speed and a heading controller ensures that the number of design parameters to be determined is at a low level. The above algorithms have been thoroughly evaluated and validated through extensive computer simulations, demonstrating their effectiveness in simulated and real marine environments. The simulation results verify the ability of the proposed algorithm to realize the dynamic positioning of USVs, and provide a practical scheme for the design of the dynamic positioning controller of USVs. [ABSTRACT FROM AUTHOR]

The solution of ship dynamic positioning thrust allocation is a complex multi-constraint and multi-objective optimization problem, the Whale Optimization Algorithm (WOA) is more convenient and accurate in handling this type of problem compared to traditional thrust allocation algorithms, but at the cost of time, and needs to solve the problem of real-time reliable convergence. Aiming at the above problems, this paper proposed an improved whale thrust allocation algorithm, this algorithm used the solution coefficients of the particular solutions of the equality constraints as individual variables, reducing the search space dimension and range, laying the foundation for obtaining reliable solutions and fast convergence of the algorithm. In addition, the population initialization adopted space block and "elite" screening methods to increase the initial population dispersion and the number of "elite" individuals, improving optimization efficiency and convergence stability. It introduced dynamic population boundaries to obtain a reasonable search space and improve algorithm convergence speed. Finally, it proposed a "Gradient method" population updating method to simulate region traversal search and achieve less iterations to obtain reliable solutions. It takes the Cybership III ship model as an example for simulation verification, the simulation results show that the thrust allocation method is feasible, has good real-time performance and stable convergence, and improves thrust allocation performance. [ABSTRACT FROM AUTHOR]

This paper surveys the recent advances in dynamic positioning (DP) control for marine crafts. DP of marine crafts means that a craft can maintain a fixed position and heading, or move along a predetermined trajectory slowly without the anchoring system, using only its own thruster system to counteract ocean disturbances. The survey is by no means exhaustive but provides a survey of some of the major technological advancements in DP controller design over the years of research and development. Firstly, the model of marine crafts and some difficult problems in DP control are introduced including the impact of multiple source disturbance, unavailable velocity measurement information, resource conservation and performance optimization, destabilizing impact of faults and network security and compound multi-constraint restrictions. Then, the DP control schemes in recent years are summarized and classified in detail. Finally, some theoretical and technical problems are proposed, including online data-driven model-free control, man–machine combination intelligent control and composite hierarchical anti-disturbance control to guide future investigations. [ABSTRACT FROM AUTHOR]

The goal of this paper is to establish a motion control system for unmanned surface vehicles (USVs) that enables point-to-point tracking and dynamic positioning. This includes the heading control and path following control of USVs. A hardware and software platform for USVs using microcontrollers is designed. This paper presents the construction of a kinematics and dynamics model for an unmanned catamaran. The motion process is divided into two segments. In the target point tracking segment, the heading coordinate system and the ship coordinate system are established. Based on these, a control method using differential steering to track the desired yaw angle is designed to improve the tracking efficiency. And the accuracy of heading keeping and path following is improved by combining the cascade PID controller. In the dynamic positioning segment, a self-adjusting mechanism is designed, thereby enhancing the flexibility of thrust distribution and improving the accuracy of the USV’s positioning retention in wind and wave environments. Finally, experimental validation is carried out to verify the effectiveness of the design proposed in this paper by issuing control commands and saving the return data through the upper computer, and then analyzing the return data with MATLAB (R2022b, MathWorks, Natick, MA, USA).

Anti-disturbance control problem is studied for ship dynamic positioning systems with model uncertainties and ocean disturbances under thruster faults. For the ocean disturbance, a stochastic disturbance observer (SDO) is established to give the online estimation. For thruster faults, an adaptive law is used to evaluate, which is obtain from Lyapunov function. For model uncertainties, a robust control term with adaptive technology is used to attenuate it. Then, a composite anti-disturbance control (CADC) strategy is raised by combining disturbance observer-based control (DOBC), adaptive technology, and robust control term, which makes the position and yaw angle of ship reach the desired values. Finally, the simulation example proves the validity of the controller. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel nonlinear model predictive control (NMPC) algorithm based on the Laguerre function for dynamic positioning ships to solve the problems of input saturation, unknown time-varying disturbances, and heavy computation. The nonlinear model of a dynamic positioning ship is presented as a linear model, transformed from a standard affine nonlinear state-space model by precise feedback linearization. The environmental disturbance is overcome using an integrator. The time cost of the proposed nonlinear control algorithm is decreased by inducing the Laguerre function to describe the feedback-linearization system input increments. The Laguerre function reduces the matrix dimensions of the nonlinear optimization problem. The simulation results for a DP supply vessel showed that the novel algorithm maintained the effective control performance of the original nonlinear model predictive control algorithm and had a reduced computation load to satisfy the requirements of real-time operation. [ABSTRACT FROM AUTHOR]

Cargo transfer vessels (CTVs) are designed to transfer cargo from a floating production storage and offloading (FPSO) unit into conventional tankers. The dynamic positioning system allows the CTV to maintain a safe position relative to the FPSO unit using a flexible cargo transmission pipe, and the CTV tows the tanker during operating conditions. The operation mode can be considered a synchronization tracking control problem. In this paper, a synchronization control strategy is presented based on the virtual leader–follower configuration and an adaptive backstepping control method. The position and heading of the following vessel are proven to be able to globally exponentially converge to the virtual ship by the contraction theorem. Then, the optimization problem of the desired thrust command from the controller is solved through an improved firefly algorithm, which fully considers the physical characteristics of the azimuth thruster and the thrust forbidden zone caused by hydrodynamic interference. To validate the effectiveness of the presented synchronous following strategy and thrust allocation algorithm, a scale model experiment is carried out under a sea state of 4 in a seakeeping basin. The experimental results show that the CTV can effectively maintain a safe distance of 100 m with a maximum deviation of 3.78 m and an average deviation of only 0.99 m in the wave heading 180°, which effectively verifies that the control strategy proposed in this paper can achieve safe and cooperative operation between the CTV and the FPSO unit. To verify the advantages of the SAF algorithm in the thrust allocation, the SQP algorithm and PSO algorithm are used to compare the experimental results. The SAF algorithm outperforms the SQP and PSO algorithms in longitudinal and lateral forces, with the R-squared (R2) values of 0.9996 (yaw moment), 0.9878 (sway force), and 0.9596 (surge force) for the actual thrusts and control commands in the wave heading 180°. The experimental results can provide technical support to improve the safe operation of CTVs. [ABSTRACT FROM AUTHOR]

This work addresses the motion control problem for a 4-degree-of-freedom unmanned underwater vehicle (UUV) in the presence of nonlinear dynamics, parametric uncertainties, system constraints, and time-varying external disturbances. A disturbance observer-based control scheme is proposed, which is structured around the model predictive control (MPC) method integrated with an extended active observer (EAOB). Compared to the conventional disturbance observer, the developed EAOB has the ability to handle both external disturbances and system/measurement noises simultaneously. The EAOB leverages a combination of sensor measurements and a system dynamic model to estimate disturbances in real-time, which allows continuous estimation and compensation of time-varying disturbances back to the controller. The proposed disturbance observer-based MPC is implemented by feeding the estimated disturbances back into the MPC's prediction model, which forms an effective adaptive controller with a parameter-varying model. The proposed control strategy is validated through simulations in a Gazebo and robot operating system environment. The results show that the proposed method can effectively reject unpredictable disturbances and improve the UUV's control performance. [ABSTRACT FROM AUTHOR]

More and more semi-submersible platforms are being employed in the deep-sea industry as a result of the offshore oil and gas industry's rapid growth, which also raises the bar for the positioning capabilities of semi-submersible platforms' positioning systems. Model predictive control is frequently used in dynamic positioning control because it is effective at addressing a variety of limitations. Yet, there are still issues to be resolved regarding how to enhance model predictive control's robustness under various working settings and how to offer workable solutions for model predictive control under stable conditions. The approach of stable fuzzy model predictive control for the dynamic placement of a semi-submersible platform is suggested in this research based on this. This method increases the tracking accuracy and tracking speed of dynamic positioning by incorporating the T-S fuzzy algorithm into model predictive control and allowing the coefficients in the weight matrix of the objective function to be modified adaptively. In addition, the solution is limited to the feasible domain by the addition of the control Lyapunov function, ensuring the stability and efficiency of the entire control procedure. A semi-submersible platform's fixed-point control and trajectory tracking can be accomplished using the proposed technique, which has better trajectory tracking effects than the conventional model predictive control, according to comprehensive simulation findings. [ABSTRACT FROM AUTHOR]

The GNSS receiver performs real-time satellite differential positioning and broadcasts RTK differential data as an RTK base station when GNSS mobile base station technology is applied in port and waterway engineering, by conducting a series of tests to evaluate the RTK positioning performance of the rover station. A test scheme about real-time dynamic positioning was developed by selecting a typical port and waterway engineering area located at the Yangtze River estuary. Referring to the synchronous PPK positioning results, the accuracy and influencing factors of RTK rover station and the stability of zero baseline in real-time dynamic positioning mode were analyzed. The experimental shows that the N and E directions of the RTK rover station can converge within 3 min, and the deviation RMS is less than 1.0 cm within 20 min after convergence; The H direction can converge within 4 min, and the deviation RMS is less than 3.0 cm within 20 min after convergence. When the relative distance between the mobile base station and the RTK rover station is too large or the relative height difference is suddenly reduced, the RTK rover station is prone to poor positioning. The difference in Nor E directions of the zero baseline positioning of two rover stations kept at millimeter level and the difference in H direction is less than 依1.5 cm, indicating high stability in positioning and orientation. [ABSTRACT FROM AUTHOR]

In this paper, a discrete-time online optimal control via time-based adaptive dynamic programming is developed for dynamic positioning (DP) of vessels in the presence of unknown system dynamic, energy conservation and wastage decrease of equipment. Firstly, a model network is established by a neural network (NN) to identify the DP system. And then, a NN optimal control scheme is developed, in which current and recorded data of DP vessel are utilized to train the critic network and action network. The optimal cost and control law are updated once at the sampling instant. The designed DP optimal control policy can maintain the vessel at desired position and heading angle, and guarantee the uniform ultimate boundedness of all the signals in the closed-loop system simultaneously. Finally, simulation results involving a supply vessel demonstrate the effectiveness of the proposed DP optimal control law. [ABSTRACT FROM AUTHOR]

Increased application of technical cybernetics- and control engineering have been considerable since the late 1960s. The driving forces have been many, such as improvements/pioneering in defense and space technology, maritime- and oil production technology, robotics and industrial control, enabled by a huge increase in available computing power. I have been involved in this development for the last 50 years. This paper sums up my work within areas such as mathematical modelling for control and estimation, Kalman filtering, and the development of software, simulators and applications for such purposes. During these years I worked, as examples, within the fields of ocean modelling for real-time estimation, oil production, dynamic positioning and industrial control in the fields of fertilizers, and aluminum production. The stories of starting up the company Prediktor and the following development of Manufacturing Execution Systems (MES systems) and my engagement in the use of optical NIR based technology for industrial control in various industries are told. My hope is that the story might be of interest to younger engineers today to understand the development in this engineering cybernetics field for 50 years as exemplified by my career.

Thrust allocation (TA) plays a critical role in the dynamic positioning system (DPS). The task of TA is to allocate the rotational speed and angle of each thruster to generate the generalized control forces. Most studies take TA as a single-objective optimization problem; however, TA is a multi-objective optimization problem (MOP), which needs to satisfy multiple conflicting allocation objectives simultaneously. This study proposes an improved multi-objective particle swarm optimization (IMOPSO) method to deal with the non-convex MOP of TA. The objective functions of reducing the allocation error, and minimizing the power consumption and the tear-and-wear of thrusters under physical constraints, are established and solved via MOPSO. To enhance the global seeking ability, the improved mutation strategy combined with the roulette wheel mechanism is adopted. It is shown through test data that IMOPSO converges better than multi-objective algorithms such as MOPSO and nondominated sorting genetic algorithm II (NSGA-II). Simulations are conducted for a DP ship with two propeller–rudder combinations. The simulation results with the single-objective PSO algorithm show that the proposed IMOPSO algorithm reduces thrust allocation errors in the three directions of surge, sway, and yaw by 48.48%, 39.64%, and 15.02%, respectively, and reduces power consumption by 44.53%, which demonstrates the feasibility and effectiveness of the proposed method.

As a substitute for human arms, underwater vehicle dual-manipulator systems (UVDMSs) have attracted the interest of global researchers. Visual servoing is an important tool for the positioning and tracking control of UVDMSs. In this paper, a reinforcement-learning-based adaptive control strategy for the UVDMS visual servo, considering the model uncertainties, is proposed. Initially, the kinematic control is designed by developing a hybrid visual servo approach using the information from multi-cameras. The command velocity of the whole system is produced through a task priority method. Then, the reinforcement-learning-based velocity tracking control is developed with a dynamic inversion approach. The hybrid visual servoing uses sensors equipped with UVDMSs while requiring fewer image features. Model uncertainties of the coupled nonlinear system are compensated by the actor–critic neural network for better control performances. Moreover, the stability analysis using the Lyapunov theory proves that the system error is ultimately uniformly bounded (UUB). At last, the simulation shows that the proposed control strategy performs well in the task of dynamical positioning.

Ship retrofitting is one alternative solution to extend a ship’s life. Several component replacements were performed in the retrofitting process, remodelings to the ship’s main dimension, and state-of-the-art equipment and technology were added. As one of the ships that require regular renewal, especially in research equipment, retrofit processes are often carried out on research vessels. The current problem in the retrofit process for research vessels, especially in Indonesia, is that retrofits are not carried out with established methodology and planning. Thus, some retrofit projects are limited to major repairs and do not extend the ship’s life or performance. To solve that problem, a developed methodology for ship retrofitting was proposed, which consists of selecting the ship and the type of retrofit and its components, determining retrofit requirements, and designing the ship based on the retrofit project. In the design process, a modified spiral design is explicitly used for the retrofit process with some alterations compared with the conventional one, which is focused on analyzing the suitability and availability of space, consumable and tank requirements, analysis of power requirements, risk analysis, and project execution plan. A case study of this developed methodology has been undertaken in the concept design phase of RV Baruna Jaya 1’s retrofit, and the results show that the methodology is considered helpful as an approach for ship retrofitting. Moreover, several considerations were also obtained from the concept design stage and had to be analyzed at the following design stage to meet the retrofit design requirements.

The article presents an efficient method of optimal thrust allocation over the actuators in a dynamically positioned ship, according to the DNV-ST-0111 standard, Level 1. The optimisation task is approximated to a convex problem with linear constraints and mathematically formulated as quadratic programming. The case study is being used to illustrate the use of the proposed approach in assessing the DP capability of a rescue ship. The quadratic programming-based approach applied for dynamic positioning capability assessment allows for fast calculations to qualitatively compare different ship designs. In comparison with the DNV tool, it gives 100% successful validation for a ship with azimuth thrusters and a pessimistic solution for a ship equipped with propellers with rudders. Therefore, it can be safely applied at an early design stage.

We consider the problem of performing condition-based maintenance on a set of geographically distributed assets via a single maintenance resource that travels between the assets' locations. That is, we dynamically determine the optimal positioning of the maintenance resource and the optimal timing of condition-based maintenance interventions that the maintenance resource performs. These decisions are made as a function of the conditions of the assets and the current location of the maintenance resource to minimize total expected costs, which include downtime, travel, and maintenance expenses. This holistic approach enables us to study unique trade-offs, namely, maintaining an asset early if the maintenance resource is currently close by, or alternatively, optimally repositioning the maintenance resource or having it idle in key locations in anticipation of asset deterioration. We model the location of the maintenance resource and assets using a graph representation and the assets' deterioration process as a discrete-time Markov chain. We formulate a Markov decision process to obtain the optimal policy for the maintenance resource (i.e., where to travel, idle, or repair). We explore the properties of the optimal policies (analytically and numerically) and how they are affected by the graph structure. Finally, we develop and analyze some implementation-friendly heuristic policies. Funding: This research was supported by Pitt Momentum Fund Award (3463) and NSF [Grant CMMI-2002681]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2021.0302. [ABSTRACT FROM AUTHOR]

Summary: This article presents a model predictive control for dynamic positioning (DP) of floating caisson at different draughts. This article focuses on the maneuvres related to the control of the spatial situation of the caisson in connexion with the final caisson reference point and the process of descending to the seabed desired location. Different models of the caisson in order to perform realistic simulations and to test the robustness of the controller are considered. A gain scheduling model predictive control (GSMPC) has been implemented, with parameter switch among four model predictive control (MPC) controllers. In this way, a specific MPC for the dynamics of each draught will be used in each caisson model corresponding to a draught. Furthermore, a Kalman filter has been implemented to remove the disturbances. Finally, in the simulations results it is compared the performance of the proposed controller with a clasic one and also it is checked how the proposed controller is able to position the system in all draughts with stability and accurate dynamic control of the system. [ABSTRACT FROM AUTHOR]

Visual-based positioning technology plays a pivotal role in spatial artificial intelligence, facilitating precise perception and comprehension of the physical world for robotic platforms and augmented reality devices. In this study, we propose a binocular camera-based method for spatial localization of targets using CNN for instance segmentation while simultaneously providing target location information. The method encompasses image acquisition and correction, target recognition and segmentation, and stereo matching, among other components. Building upon this foundation, we introduce a pedestrian recognition segmentation network model with an attention mechanism. To accurately locate the target, we employ a multi-feature fusion feature point extraction and matching algorithm that combines edge information with semantic information. Finally, our proposed method is evaluated for dynamic pedestrian targets in indoor environments, achieving a horizontal positioning error of less than 0.25 m. [ABSTRACT FROM AUTHOR]

Dynamic positioning systems ensure additional position accuracy in different operations in the maritime industry, such as shuttling, drilling, diving, pipe laying, and others. Although they are known to be robust systems, they are not exempt from failures leading to incidents, among which we can find human-related incidents. This research analyzes 62 human-related dynamic-positioning incidents and aims to determine which segment in the dynamic positioning system influences these occurrences by applying binary logistic regression modeling techniques in the test sample and validating the results using a control sample. The results indicate that thrusters have the most significant influence on human-related incidents; however, not all DP operations are affected in the same measure. By stratifying the database and considering the different operations in progress, it is noted that human-related incidents while drilling operations are in progress are effectively influenced using a higher percentage of thrusters online.

Real-time acquisition of location information for agricultural robotic systems is a prerequisite for achieving high-precision intelligent navigation. This paper proposes a data filtering and combined positioning method, and establishes an active screening model. The dynamic and static positioning drift points of the carrier are eliminated or replaced, reducing the complexity of the original Global Navigation Satellite System (GNSS) output data in the positioning system. Compared with the traditional Kalman filter combined positioning method, the proposed active filtering–Kalman filter algorithm can reduce the maximum distance deviation of the carrier along a straight line from 0.145 m to 0.055 m and along a curve from 0.184 m to 0.0640 m. This study focuses on agricultural robot positioning technology, which has an important influence on the development of smart agriculture.

The development of dynamic positioning (DP) algorithms for an unmanned surface vehicle (USV) is attracting great interest, especially in support of complex missions such as sea rescue. In order to improve the simplicity of the algorithm, a DP algorithm based on its own path following control ability is proposed. The algorithm divides the DP problem into two parts: path generation and path following. The key contribution is that the DP ability can be realized only by designing the path generation method, rather than a whole complex independent DP controller. This saves the computing power of the USV onboard computer and can effectively reduce the complexity of the algorithm. In addition, the fixed-time LOS guidance law is designed to improve the convergence rate of the system state in path-following control. The reasonable selection of speed and a heading controller ensures that the number of design parameters to be determined is at a low level. The above algorithms have been thoroughly evaluated and validated through extensive computer simulations, demonstrating their effectiveness in simulated and real marine environments. The simulation results verify the ability of the proposed algorithm to realize the dynamic positioning of USVs, and provide a practical scheme for the design of the dynamic positioning controller of USVs.

Nowadays, many maritime structures require precise dynamic positioning (DP) of the constructive elements that compose them. In addition, the use of preconstructed elements that are later moved to the final location has become widespread. These operations have not been automated with the risks involved in carrying out the complex operations required. To minimize these operational risks and to perform a correct DP of floating structures, a new approach based on the L1 adaptive control technique is proposed. As an example of application, a proposed L1 adaptive controller was implemented in the dynamic positioning of a floating caisson. Several simulations of the system with wave disturbances were carried out, and the results were compared with those obtained by applying other classical and advanced control techniques, such as linear quadratic Gaussian control (LQG) and model predictive control (MPC). It was concluded that the proposed L1 adaptive controller performs correct dynamic positioning and reduces the tension generated on the lines concerning the other advanced control techniques with which it was compared. This reduction in line tension leads to an important improvement due to the possibility of reducing the size of the actuators or reducing their number, with the important economic and safety repercussions that these actions entail. [ABSTRACT FROM AUTHOR]

Planar type docking enables a convenient underwater energy supply for irregularly shaped autonomous underwater vehicles (AUVs), but the corresponding control method is still challenging. Conventional control methods for torpedo-shaped AUVs are not suitable for planar type docking due to the significant differences in system structures and motion characteristics. This paper proposes a two-step adaptive control method to solve the planar type docking problem. The method makes a seamless combination of horizontal dynamic positioning and visual servo docking considering ocean current disturbance. The current disturbance is estimated and canceled in the pre-docking step using a current observer, and the positioning error is further compensated for by the vertical visual servo technique in the docking step. Reduced order dynamic models are distinctively established for different docking steps according to the motion characteristics, based on which the dynamic controllers are designed considering the model parameter uncertainties. Simulation is conducted with an initial distance of 10 m in the horizontal direction and 3 m in depth. Stable and accurate dynamic positioning under up to 0.4 m/s of current disturbances with different directions is validated. A 0.5 m lateral positioning error is successfully compensated for by the visual servo docking step. The proposed control method provides a valuable reference for similar types of docking application. [ABSTRACT FROM AUTHOR]

This paper presents the development of a dynamic positioning in ice validation platform (DPIVP) which is part of a larger research project aimed at developing dynamic positioning (DP) system technologies for ice-rich environments. One outcome is simulation software to aid research in this area. The DPIVP software was designed to realistically simulate the dynamics of ice-structure interactions for real-time applications and to validate components common to DP in ice simulations. The software consists of many components which the DPIVP ties together as a unified system. All components have well-defined interfaces. Many of them are also distributed, allowing execution on separate computers and/or CPUs which helps ensure real-time operation. These two characteristics also decreases coupling and encourages a more modular design with the benefit of easily substituting alternative component implementations without reprogramming the DPIVP. Alternate implementations are useful for conducting research in specific DP in ice areas without substantially changing the system, such as alternative ice force models, DP control algorithms, vessel models, 3D and 2D visualization, environment models, and data acquisition systems. The integrated system was tested and evaluated using unit testing, integration testing, and system testing. The completed system was also validated using test cases that match physical model tests; the results compared favorably. Although the software has some limitations, for example, validated ice-force models being limited to two vessels, and thus lacks the generality we wish, the end result is a working prototype that satisfies the research requirements and provides an architecture and framework for future development. [ABSTRACT FROM AUTHOR]

How does a vessel keep its position at sea without mooring? The answer is through dynamic positioning, or DP. Advanced technology, combining position reference sensors, computers, propellers and thrusters, is used to counteract environmental forces such as wind, currents and waves to dynamically position the vessel without using anchors or mooring lines. Today, DP systems are found in every ocean region in the world. The Kongsberg DP adventure began in 1975 when Kongsberg Våpenfabrikk signed its first contract. Eighteen months later, an Albatross DP system was installed on board a Norwegian diving vessel in the North Sea. Today, dynamic positioning equipment from the inland town of Kongsberg is found onboard a myriad of ship types including supply vessels, drilling rigs, pipe and cable layers, stone-dumping and bulk vessels, shuttle tankers, crane and lifting vessels, mine hunting vessels, cruise ships, floating hotels and yachts. Dynamic positioning is not limited to keeping a vessel on a fixed location but also to controlling the motions of vessels along predetermined tracks. After over 40 years in business, Kongsberg Maritime still maintains a world-leading position within dynamic positioning. This paper is based on the book “The Jewel in the Crown: Kongsberg Dynamic Positioning Systems 1975 – 2015”, (Kvaal and Østby, 2015).

Due to the highly dynamic changes of the environment, the frequent loss of signal will seriously reduce the accuracy of realtime dynamic positioning. Meanwhile, the ambiguity resolution for medium/long baseline is more affected by atmospheric delay. To solve this problem, an Inertial Navigation System (INS) assisted Beidou Navigation System (BDS) medium/long baseline partial ambiguity resolution (PAR) method is designed. Firstly, constructing the BDS/INS tight integrated system that uses INS provided initial information to ambiguity resolution when the signal outages. Secondly, the atmospheric delay constraint is introduced to improve the precision of float ambiguity. Finally, the PAR based on the elevation angle information is applied to enhance fixed speed and accuracy. The vehicle experiments show that the proposed algorithm can quickly fix the ambiguity of medium/long baseline when the satellite signal outages for a short time, and improve the positioning accuracy of medium/long baseline in the dynamic environment. [ABSTRACT FROM AUTHOR]

This paper surveys the recent advances in dynamic positioning (DP) control for marine crafts. DP of marine crafts means that a craft can maintain a fixed position and heading, or move along a predetermined trajectory slowly without the anchoring system, using only its own thruster system to counteract ocean disturbances. The survey is by no means exhaustive but provides a survey of some of the major technological advancements in DP controller design over the years of research and development. Firstly, the model of marine crafts and some difficult problems in DP control are introduced including the impact of multiple source disturbance, unavailable velocity measurement information, resource conservation and performance optimization, destabilizing impact of faults and network security and compound multi-constraint restrictions. Then, the DP control schemes in recent years are summarized and classified in detail. Finally, some theoretical and technical problems are proposed, including online data-driven model-free control, man–machine combination intelligent control and composite hierarchical anti-disturbance control to guide future investigations.

In this paper, we present a novel nonlinear model predictive control (NMPC) algorithm based on the Laguerre function for dynamic positioning ships to solve the problems of input saturation, unknown time-varying disturbances, and heavy computation. The nonlinear model of a dynamic positioning ship is presented as a linear model, transformed from a standard affine nonlinear state-space model by precise feedback linearization. The environmental disturbance is overcome using an integrator. The time cost of the proposed nonlinear control algorithm is decreased by inducing the Laguerre function to describe the feedback-linearization system input increments. The Laguerre function reduces the matrix dimensions of the nonlinear optimization problem. The simulation results for a DP supply vessel showed that the novel algorithm maintained the effective control performance of the original nonlinear model predictive control algorithm and had a reduced computation load to satisfy the requirements of real-time operation.