A large ship power positioning real-time thrust distribution method and system

Abstract

This invention relates to a method and system for real-time thrust allocation in dynamic positioning of large ships, comprising the following steps: S1, establishing a six-degree-of-freedom dynamic model of the ship in three-dimensional space; S2, using a sensor system to monitor external disturbances such as wind, waves, and currents in real time, and processing the monitoring information through a data fusion algorithm to estimate the external disturbance forces acting on the ship; S3, integrating the maximum thrust limit, total power limit, and turning angle limit of the propellers into a set of mathematical inequality constraints; S4, based on model predictive control theory, combining the dynamic model, the estimated external disturbance forces, and the mathematical inequality constraints, constructing an optimization problem with the objective of minimizing ship positioning error and propeller energy consumption, and obtaining the optimal thrust allocation scheme for each propeller in real time by solving this problem. This invention has the effects of improving positioning accuracy, improving power system efficiency, enhancing the real-time performance and adaptability of the system, and ensuring the safety of the power system.

Description

Technical Field

[0001] This invention relates to the field of ship dynamic positioning technology, and in particular to a method and system for real-time thrust distribution in dynamic positioning of large ships. Background Technology

[0002] Dynamic positioning systems (DPS) enable ships to maintain a preset position and heading at sea without relying on anchoring devices, and are now widely used in marine engineering operations, marine scientific research, and other fields. The marine operating environment of large ships is complex and variable, and there are stringent requirements for positioning accuracy and operational safety. The thrust distribution strategy of the dynamic positioning system directly determines its positioning effectiveness and the operational stability of the power system.

[0003] Currently, ship dynamic positioning technology has made significant progress. Early dynamic positioning systems used simple control algorithms, relying on manual adjustment of thrusters to complete positioning. With the continuous advancement of computer technology and automatic control theory, advanced algorithms such as PID control, fuzzy control, and neural network control have been gradually applied to modern dynamic positioning systems, improving the accuracy and stability of ship positioning to a certain extent. However, when applying these existing thrust distribution algorithms to large ship scenarios, there are still technical shortcomings that make them difficult to adapt to actual working conditions.

[0004] Large ships have massive propulsion systems with numerous thrusters. Existing algorithms struggle to achieve coordinated thrust distribution across these thrusters, leading to issues like some thrusters operating under overload while others remain idle and inefficient. This reduces the overall efficiency of the propulsion system and directly impacts the ship's positioning accuracy. Furthermore, large ships are significantly affected by dynamic external disturbances such as wind, waves, and currents during maritime operations. These disturbances continuously alter the ship's stress state, requiring real-time adjustments to the thrust distribution scheme. Existing algorithms lack precise monitoring and quantification mechanisms for wind, wave, and current disturbances, making it difficult to quickly adapt to real-time changes and prone to positioning errors. Moreover, large ship thrusters face rigid operational constraints such as maximum thrust, total power, and turning angle. Existing algorithms generally suffer from complex computational processes and insufficient real-time performance when handling these constraints, making it difficult to quickly optimize thrust distribution while meeting these constraints and ensuring the safe and stable operation of the propulsion system.

[0005] In summary, existing ship dynamic positioning thrust allocation algorithms cannot simultaneously solve the technical problems of unreasonable thrust allocation, poor adaptability to dynamic external interference, low efficiency in dynamic constraint processing, and poor real-time performance in large ship scenarios. They are insufficient to meet the comprehensive requirements of high precision, high efficiency, high real-time performance, and high safety in the dynamic positioning of large ships. Therefore, a new real-time thrust allocation method for dynamic positioning of large ships is urgently needed. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method and system for real-time thrust distribution in dynamic positioning of large ships, which improves positioning accuracy, increases power system efficiency, enhances the real-time performance and adaptability of the system, and ensures the safety of the power system.

[0007] The above-mentioned objective of this invention is achieved through the following technical solutions: A method for real-time thrust distribution in dynamic positioning of large ships includes the following steps: S1. Establish a six-degree-of-freedom dynamic model of the ship in three-dimensional space; S2. Utilize sensor systems to monitor external disturbances such as wind, waves, and currents in real time, and process the monitoring information through data fusion algorithms to estimate the external disturbance forces acting on the ship. S3. Integrate the maximum thrust limit, total power limit, and angle limit of the thruster into a set of mathematical inequality constraints; S4. Based on model predictive control theory, combined with the dynamic model, estimated external disturbance force and mathematical inequality constraints, an optimization problem is constructed with the goal of minimizing ship positioning error and propeller energy consumption. The optimal thrust distribution scheme of each propeller is obtained in real time by solving this problem.

[0008] Through the above technical solutions, a complete thrust allocation logic of "modeling-monitoring-constraint-optimization" is constructed. It integrates multi-sensor interference monitoring and model predictive control theory to realize real-time thrust allocation for dynamic positioning of large ships, taking into account both ship positioning accuracy and propeller energy consumption optimization. It effectively adapts to external interference in complex marine environments and provides core framework support for subsequent refinement of technical solutions.

[0009] As a further technical solution of the present invention: in the step of establishing a six-degree-of-freedom dynamic model of a ship in three-dimensional space, the basic equations of the dynamic model are: ;in, It is the inertia matrix. For the Coriolis and centripetal force matrices, Here is the damping matrix. For the thrust vector of the propulsion unit, The vector of external disturbance force; The inertia matrix in the dynamic model Coriolis and centripetal matrix and damping matrix It is determined through a systematic identification method and can be corrected in real time based on ship operating conditions and environmental data.

[0010] The above technical solutions clarify the core equations and parameter determination methods of the six-degree-of-freedom dynamic model, enabling the model to accurately reflect the ship's motion characteristics and the parameters to be dynamically corrected according to the working conditions and environment. This provides a reliable dynamic basis for the thrust distribution algorithm and improves the adaptability of the model to actual ship motion.

[0011] As a further technical solution of the present invention: the step S2, which involves using a sensor system to monitor external disturbances such as wind, waves, and currents in real time, includes: S21. Monitor wind speed using an anemometer and wind direction indicator. and wind direction Calculate the force of wind on a ship The formula is as follows: in, air density, For the windward area of ​​the ship, S22 represents the wind resistance coefficient; wave parameters are monitored using wave sensors, and the force exerted by the waves on the ship is calculated. The formula is as follows: in, The density of seawater, It is the acceleration due to gravity. For the ship in the Hydrodynamic coefficients at wave frequencies, For the first The amplitude of each wave component The direction function of wave force. The attitude angle of the ship; S23. Monitoring ocean current speed using a current meter. and flow direction And calculate the force of the flow on the ship. The formula is as follows: in, The density of seawater, The projected area of ​​the ship in the direction of the water flow. This is the flow resistance coefficient; S24. The Kalman filter algorithm is used to fuse and filter the monitoring data from multiple sensors.

[0012] The above technical solutions enable accurate monitoring and quantitative calculation of wind, wave, and current interference. By combining the Kalman filter algorithm to complete multi-sensor data fusion, data noise is effectively reduced, the accuracy of external interference force estimation is improved, and precise input is provided for the dynamic adjustment of thrust allocation schemes.

[0013] As a further technical solution of the present invention: step S3 specifically includes: S31. Define the thrust constraint conditions of the thruster and establish the mathematical expression for the thrust constraint, as follows: in, , The first Minimum and maximum thrust of each thruster For the number of thrusters; S32. Define the total power constraint condition of the thruster and establish the mathematical expression for the total power constraint, as follows: in, For the first The power of each thruster For the first The power coefficient of each thruster This is the upper limit of the total power of the thruster system; S33. Define the thruster rotation angle constraint conditions and establish the mathematical expression for the rotation angle constraint, as follows: in, , The first Minimum and maximum rotation angles of each thruster; S34. Integrate the mathematical expressions corresponding to the above thrust constraints, total power constraints and rotation constraints into a unified set of mathematical inequality constraints.

[0014] The above technical solutions transform the thrust, total power, and rotation angle constraints of the propeller into explicit mathematical inequalities, forming a comprehensive and quantifiable dynamic constraint system. This avoids propeller overload or unreasonable operation, ensures the safe and stable operation of the power system, and provides clear boundary conditions for optimization solutions.

[0015] As a further technical solution of the present invention: step S3 further includes S35: processing the mathematical inequality constraints integrated in S34 using the projection gradient method, the specific steps of which are as follows: S351, Initialize the thruster's thrust and corner This ensures that it satisfies the unified mathematical inequality constraints described in S34; S352. Calculate the gradient of the objective function. S353, the gradient Projecting the gradient onto the feasible region that satisfies the S34 constraint, we obtain the projection gradient. S354. Update the thrust and rotation angle of the thruster according to the projection gradient, using the following update formula: in, Step size, This represents the number of iterations. S355. Repeat steps S352 to S354 until the convergence condition is met, ensuring that the thrust and rotation angle obtained in each iteration are within the feasible region.

[0016] The above technical solution employs the projection gradient method to process the integrated multi-dimensional constraints of the thruster. Through initialization, gradient calculation, projection, updating, and iterative convergence processes, it ensures that the thrust and rotation angle meet safety limits. This method achieves rapid convergence, improves the efficiency of constraint processing and the real-time performance of the algorithm, and transforms formal constraints into executable guarantees. It not only ensures the safety and stability of the power system but also provides compliant boundary conditions for subsequent thrust allocation optimization, thereby enhancing the rationality of the solution.

[0017] As a further technical solution of the present invention: step S4 includes: S41. To minimize ship positioning error and propeller energy consumption, construct the objective function, the formula of which is as follows: in, To predict the time domain, This is the weighted matrix of positioning errors. for Diagonal positive definite matrix Indicates based on Time information prediction Positioning error at any moment express The thrust vector at time t; S42. The six-degree-of-freedom dynamic model is discretized using the Euler method, and the velocity update formula and position-heading update formula are derived as follows: The speed update formula is: The update equations for position and heading are: in Sampling time, This is the transformation matrix corresponding to three-degree-of-freedom motion; Predicting the future using discretization models The ship's state at a given moment; S43, based on the thruster constraints determined in step S3, combined with the thruster thrust constraints. Power constraints (ki is the power coefficient of the i-th thruster) and the rotation angle constraint are used to complete the constraint transformation, resulting in a unified system of linear inequalities. ,in, The constraint coefficient matrix, The constraint constant vectors are all generated from the dynamic constraint conditions; S44. Minimize the objective function With the goal of using a system of linear inequalities To constrain the problem, a quadratic programming problem is constructed, and the interior-point method is used to solve it to obtain the optimal thrust vector. Real-time monitoring of external interference information and changes in ship status; continuous repetition of steps S41 to S44; dynamic updating of thrust distribution scheme to ensure real-time thrust distribution.

[0018] The above technical solution constructs an objective function that takes into account both positioning error and energy consumption. By combining the Euler method discretization model and the interior point method to solve the quadratic programming problem, the optimal thrust vector can be efficiently solved. Furthermore, the solution can be iteratively updated in real time according to external disturbances and ship status, thereby improving the real-time performance and optimization effect of thrust allocation.

[0019] This invention also discloses a real-time thrust distribution system for dynamic positioning of large ships, comprising: The sensor data acquisition module is used to acquire real-time data on the ship's position, attitude, and external disturbances such as wind, waves, and currents. The data processing center is connected to the sensor data acquisition module and is used to perform noise reduction and fusion processing on the acquired data, and output ship status data and external interference data. The ship dynamics model is connected to the data processing center and is used to predict the ship's motion state based on discretized equations and output real-time ship motion trend data. The real-time interference monitoring module is connected to the data processing center and is used to analyze and calculate external interference data and output external interference force vector. The thrust allocation optimization module is connected to the ship dynamics model and the real-time disturbance monitoring module, respectively. It is used to generate a preliminary thrust allocation scheme by combining ship motion trend data and external disturbance force vectors and solving a quadratic programming problem. The dynamic constraint processing module is connected to the thrust allocation optimization module and is used to perform feasibility correction on the initial thrust allocation scheme based on the maximum thrust limit and total power limit of the thruster, and output a compliant thrust scheme. The thrust command generation module is connected to the dynamic constraint processing module and is used to convert the compliant thrust scheme into executable thrust control commands. The thruster execution module is connected to the thrust command generation module and is used to receive executable thrust control commands, adjust the thrust magnitude and angle of the thruster, and realize ship dynamic positioning. The ship status feedback module is used to monitor the ship's positioning status and propeller operating status, and output feedback data; The system optimization and adjustment module is connected to the ship status feedback module and is used to dynamically adjust system parameters based on feedback data.

[0020] Through the above technical solutions, a closed-loop system architecture of "acquisition-processing-prediction-monitoring-optimization-constraint-transfer of commands-execution-feedback-adjustment" is formed. Each module coordinates and adapts to the core steps of the thrust distribution method, ensuring the efficient implementation of the method, realizing dynamic monitoring and adaptive optimization of the ship's positioning status and the thruster's working status, and ensuring the stable and reliable operation of the dynamic positioning system.

[0021] In summary, the present invention has at least one of the following beneficial technical effects: 1. This invention discloses a real-time thrust allocation method for dynamic positioning of large ships. It achieves the accuracy and real-time performance of thrust allocation for dynamic positioning of large ships by constructing a six-degree-of-freedom dynamic model, fusing multi-sensor interference monitoring data and processing it with Kalman filtering for noise reduction, integrating multi-dimensional quantitative constraints of the thruster, and combining model predictive control theory and interior point method to solve the optimization problem. It also takes into account the improvement of positioning accuracy, the optimization of thruster energy consumption and the enhancement of system adaptability.

[0022] 2. This invention discloses a real-time thrust distribution system for dynamic positioning of large ships. Through a multi-module collaborative closed-loop architecture (acquisition-processing-prediction-optimization-constraint-execution-feedback-adjustment), it achieves precise adaptation and reliable implementation of the thrust distribution method and system modules, ensuring dynamic monitoring and adaptive optimization of the ship's positioning status and the thruster's working status, and simultaneously ensuring stable operation of the dynamic positioning system, achieving the required positioning accuracy, and ensuring the safety and efficiency of the power system. Attached Figure Description

[0023] Figure 1 This is a flowchart illustrating a real-time thrust distribution method for dynamic positioning of large ships according to the present invention.

[0024] Figure 2 for Figure 1 A schematic diagram of the specific process of S1.

[0025] Figure 3 for Figure 1 A schematic diagram of the specific process of S2 in the middle.

[0026] Figure 4 for Figure 1 A schematic diagram of the specific process of S3 in China.

[0027] Figure 5 for Figure 1 A schematic diagram of the specific process of S4 in China.

[0028] Figure 6 This is an architectural diagram of a real-time thrust distribution system for dynamic positioning of a large ship according to the present invention. Detailed Implementation

[0029] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0030] In the description of this application, it should be noted that the terms "upper," "lower," "inner," "outer," "top / bottom," etc., indicating the orientation or positional relationship are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0031] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installed," "equipped with," "sleeved / connected," "connected," etc., should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances. Example

[0032] Reference Figure 1 The present invention discloses a real-time thrust allocation method for dynamic positioning of large ships, which includes the following four core steps: S1 establishing a ship dynamics model, S2 real-time monitoring of external interference, S3 considering dynamic constraints, and S4 designing a real-time thrust allocation algorithm. Through the coordinated operation of each step, the precise dynamic positioning of large ships is achieved.

[0033] First, step S1 is executed to establish a six-degree-of-freedom dynamic model of the ship in three-dimensional space. In a large ship dynamic positioning system, establishing an accurate ship dynamic model is the foundation for achieving real-time thrust distribution. This model treats the ship's motion in three-dimensional space as six-degree-of-freedom motion, taking into account factors such as the ship's inertia, damping, and external disturbances, in order to accurately describe the forces and motion state of the ship in the marine environment.

[0034] Reference Figure 2 S1 specifically includes the following three steps: S11. To accurately describe the motion of a ship, two coordinate systems are defined: the inertial coordinate system and the... and hull coordinate system Among them, the origin of the inertial coordinate system For fixed points, coordinate axes Pointing to the east, north, and zenith respectively; the origin of the ship's coordinate system. Located at the ship's center of gravity, coordinate axis These point to the bow, starboard side, and keel direction of the ship, respectively.

[0035] The position and attitude of a ship in an inertial coordinate system can be represented by vectors. It means that among them These are the coordinates of the ship's center of gravity in the inertial coordinate system. These represent the ship's roll, pitch, and bow angles, respectively. The ship's velocity vector in the hull coordinate system is... ,in These are the ship's coordinates in the hull coordinate system. linear velocity in the direction, These are the ship's coordinate systems around the hull. Angular velocity of the axis.

[0036] S12. Derivation of the dynamic equations: According to Newton's second law, the dynamic equations of a ship can be expressed as follows: in: This is the ship's inertia matrix, which contains information about the ship's mass and moment of inertia. For six degrees of freedom motion, It is The matrix can be represented as ,in Let the inertia matrix be that of a rigid body. This is the additional mass matrix. in, For the quality of the ship, These are the coordinates of the ship's center of gravity in the ship's coordinate system. These are the ship's moment of inertia and product of inertia.

[0037] Additional mass matrix It reflects the inertial effect of the fluid around the ship, and its elements depend on the shape and motion of the ship. The Coriolis and centripetal force matrices are antisymmetric matrices, which are related to the ship's velocity vector. The relevant elements can be calculated based on the ship's inertia matrix and velocity vector. This is the damping matrix, which describes the fluid damping forces acting on a ship during its motion. Damping matrix It can be divided into linear damping matrix and nonlinear damping matrix ,Right now Linear damping matrix The elements are usually determined experimentally or through numerical simulation; nonlinear damping matrix The nonlinear damping effect at higher ship speeds is taken into account. The thrust vector generated by the thruster is a The vector contains the thrust and torque of each propeller in the ship's coordinate system. This is the external disturbance force vector, which includes the forces and moments generated on the ship by external disturbances such as wind, waves, and currents.

[0038] S13. Determine the model parameters, such as the inertia matrix. Damping matrix Parameters, etc., need to be determined through systematic identification methods. Parameter estimation can be performed using ship design drawings, model test data, and actual navigation data, employing methods such as least squares and maximum likelihood estimation. In practical applications, model parameters can be adjusted in real time according to different ship operating conditions and environmental conditions to improve model accuracy.

[0039] By establishing the aforementioned ship dynamics model, the forces and motion states of large ships in the marine environment can be accurately described, providing a foundation for subsequent real-time thrust allocation algorithms.

[0040] Reference Figure 3 Next, step S2 is executed, which utilizes a sensor system to monitor external disturbances such as wind, waves, and currents in real time, while simultaneously collecting information on the ship's position, speed, and attitude. The monitored information is then processed using a data fusion algorithm to estimate the external disturbance force. This process is divided into four sub-steps: S21 is for wind interference monitoring. Wind is one of the important external factors affecting ship motion. To monitor wind information in real time, anemometers and wind direction indicators are installed at appropriate locations on the ship. The wind speed data measured by the anemometers... It includes the actual wind speed and the wind direction data measured by the anemometer. This represents the angle of the wind relative to the ship's bow. In order to incorporate the force of the wind on the ship into the dynamic model, the wind speed and direction information needs to be converted into the force of the wind on the ship.

[0041] According to the principles of aerodynamics, the force of wind on a ship It can be represented as: in, air density, For the windward area of ​​the ship, The drag coefficient is related to factors such as the ship's shape and wind direction.

[0042] To more accurately calculate the forces exerted by wind on ships, This can be further expressed as wind direction. function The specific expression of the function can be obtained through experiments or numerical simulations.

[0043] S22 is for wave interference monitoring. The effects of waves on ships are complex, generating not only vertical forces but also movements such as rolling, pitching, and bowing. Wave sensors are typically used to monitor wave parameters, such as wave height. ,wavelength and wave direction According to linear wave theory, the force of waves on a ship It can be calculated using the following formula: in, The density of seawater, It is the acceleration due to gravity. For the ship in the Hydrodynamic coefficients at wave frequencies, For the first The amplitude of each wave component The direction function of wave force. This refers to the ship's attitude angle.

[0044] To accurately calculate the force of waves on a ship, it is necessary to perform spectral analysis on the waves, decompose the waves into multiple wave components with different frequencies and directions, calculate the force of each component on the ship separately, and finally superimpose them.

[0045] S23 is for current disturbance monitoring. Ocean currents exert a continuous force on ships, affecting their positioning. A current meter is used to monitor the speed of the ocean current. and flow direction The force of the current on the ship It can be calculated based on the principles of fluid mechanics: in, The density of seawater, The projected area of ​​the ship in the direction of the water flow. It is the flow resistance coefficient, which is related to the ship's shape and flow regime.

[0046] S24 represents data fusion and processing. To improve the accuracy and reliability of external interference information, it is necessary to fuse data from multiple sensors, including wind speed, wind direction, wave height, wavelength, wave direction, flow velocity, and flow direction. Digital filtering methods such as mean filtering and median filtering can be used to assist in noise reduction. Then, a Kalman filter algorithm is employed to achieve data fusion. Assuming the sensor measurements are... The system state vector is Then the prediction equation and update equation of the Kalman filter are as follows: Prediction equation: Update equation: in, Here is the state transition matrix. To control the input matrix, To control the input vector, and These are the prediction error covariance matrix and the update error covariance matrix, respectively. The process noise covariance matrix is... For the observation matrix, To observe the noise covariance matrix, This is the Kalman gain.

[0047] The Kalman filter algorithm can effectively remove noise from sensor data, improve the accuracy of external interference information, and provide accurate data support for the real-time updating of ship dynamics models.

[0048] Reference Figure 4 Then, step S3 is executed. In the thrust distribution process of dynamic positioning for large ships, fully considering the various dynamic constraints of the propeller is crucial to ensuring the safe and efficient operation of the power system. The following details how to handle constraints such as the maximum thrust limit and power limit of the propeller, and transform them into mathematical inequality constraints, specifically divided into five sub-steps: S31 represents the maximum thrust limit for the propellers. Each propeller has its maximum permissible thrust; exceeding this limit may damage the propeller or affect its service life. Assume the ship has common... The first thruster, the... The thrust of each thruster is Its maximum thrust is Minimum thrust is (Usually a negative value, representing reverse thrust), then the maximum thrust limit of the thruster can be expressed as: These inequality constraints ensure that the thrust of each thruster is within its safe operating range.

[0049] S32 represents the thruster power limit. The thruster's power consumption is closely related to its thrust, and can usually be approximated as power... With thrust It is proportional to the square of, that is: in It is the first The power coefficient of a propeller depends on factors such as the type and size of the propeller. Furthermore, ship propulsion systems typically have total power limitations. That is, the sum of the power of all thrusters cannot exceed this value: This inequality constraint ensures that the total power consumption of the ship's propulsion system is within the allowable range, thus preventing system failure due to power overload.

[0050] S33 represents the thruster angle limitation. Some thrusters have angle limitations, and these angles affect the thrust direction and thus the dynamic positioning effect. Let the first... The rotation angle of each thruster is Its maximum turning angle is The minimum turning angle is Then the thruster rotation angle limit can be expressed as: The angular limitation of a propeller affects the direction of its thrust, which in turn affects the dynamic positioning of the entire ship. Therefore, angular limitation needs to be taken into account during thrust distribution.

[0051] S34 integrates the dynamic constraints, combining the mathematical expressions corresponding to the thrust constraint in S31, the power constraint in S32, and the rotation angle constraint in S33 to obtain a complete set of mathematical inequality constraints, specifically: In the real-time thrust allocation algorithm based on model predictive control theory, these constraints are treated as part of the optimization problem. By solving the optimization problem with inequality constraints, the optimal thrust allocation scheme that satisfies the dynamic constraints is obtained.

[0052] S35 presents an innovative method for handling dynamic constraints. It employs the projected gradient method to efficiently address these constraints. In each iteration, this method first calculates the gradient direction under the unconstrained condition and then projects it onto the feasible region that satisfies the constraints, ensuring that the solution obtained in each iteration is within the feasible region. The specific steps are as follows: S351, Initialize the thruster's thrust and corner This ensures that the dynamic constraints are met.

[0053] S352. Calculate the gradient of the objective function. S353, Gradient Projecting the gradient onto the feasible region that satisfies the dynamic constraints yields the projection gradient. S354. Update the thrust and rotation angle of the thruster according to the projection gradient: in It's the step length. It represents the number of iterations.

[0054] S355. Repeat steps S352-S354 until the convergence condition is met.

[0055] This method allows for rapid convergence to the optimal thrust allocation scheme while ensuring dynamic constraints, thus improving the algorithm's real-time performance and effectiveness.

[0056] Reference Figure 5Next, step S4 is executed to design a real-time thrust allocation algorithm. Based on model predictive control theory, and combined with ship dynamics model and external disturbance information, the optimal thrust allocation scheme is obtained by constructing an objective function, predicting the ship's state, handling constraints, and solving the optimization problem. This is specifically divided into four sub-steps: S41 is the objective function. In the dynamic positioning of large ships, the positioning error of the ship and the energy consumption of the propellers need to be considered comprehensively. Let the vector composed of the ship's desired position and heading be... The actual position and heading vector are Then the positioning error vector is The energy consumption of the thruster is proportional to the square of the thrust. Let the thrust vector of the thruster be... ,in Let the number of thrusters be denoted by . Define the objective function. for: in, For prediction in the time domain, the value range is 10–50. The weighted matrix for the positioning error is a diagonal positive definite matrices, for example The weights are adjusted according to the actual situation to adjust the weights of positioning errors in different directions; The weighted matrix for the thruster thrust is a A diagonal positive definite matrix, used to adjust the weights of different thruster energy consumptions. Indicates based on Time information prediction Positioning error at any moment express The thrust vector at time t.

[0057] S42 is a prediction based on the ship dynamics model; the ship dynamics equations are: In discrete time, the Euler method is used for discretization: in, The sampling time is 0.1-1 seconds.

[0058] The update equations for position and heading are: in, From the velocity vector The transformation matrix to position and bow rate of change, for three-degree-of-freedom ship motion, for: Using the discretization model described above, we can determine the state at the current moment. and thrust vector Predicting the future The state at a given moment.

[0059] S43 addresses the dynamic constraints, where the thruster has both maximum thrust and power limits. The maximum thrust limit can be expressed as: in, and The first The minimum and maximum thrust of each thruster.

[0060] Regarding power limitations, let the first... The power of each thruster is ,and With thrust Existence Relationship = ( (where the power factor is ), then the power limitation can be expressed as: These constraints are transformed into linear inequality constraints for handling in the optimization problem.

[0061] S44 is for solving the optimization problem, with the objective function... The minimization problem is transformed into a quadratic programming problem with constraints: in, and These are matrices and vectors derived from dynamic constraints. The interior-point method is used to solve the above quadratic programming problem to obtain the optimal thrust vector. This vector represents the optimal thrust distribution scheme for each thruster. The data is sent to the controllers of each thruster. The controllers precisely adjust the thruster's thrust by regulating control parameters such as motor speed and blade angle. Simultaneously, they monitor the ship's positioning error (allowable range of ±0.5 meters for position error and ±1° for heading error) and the thruster's operating status in real time. If the positioning error exceeds the allowable range or the thruster malfunctions (such as excessive thrust, excessive power, or excessive steering angle), the weighting matrix in the objective function is adjusted promptly. Or predict the time domain Alternatively, the faulty thruster can be isolated and a backup thruster activated to ensure stable system operation. In practical applications, as external interference information and the ship's status change in real time, the optimization process from S41 to S44 is continuously repeated to achieve real-time thrust distribution.

[0062] Reference Figure 6This invention also discloses a real-time thrust distribution system for dynamic positioning of large ships, comprising a sensor data acquisition module, a data processing center, a ship dynamics model, a real-time interference monitoring module, a thrust distribution optimization module, a dynamic constraint processing module, a thrust command generation module, a propeller execution module, a ship state feedback module, and a system optimization and adjustment module. The sensor data acquisition module acquires real-time data on the ship's position, attitude, and external interference such as wind, waves, and currents. The data processing center, connected to the sensor data acquisition module, performs noise reduction and fusion processing on the acquired data and outputs ship state data and external interference data. The ship dynamics model, connected to the data processing center, predicts the ship's motion state based on discretized equations and outputs real-time motion trend data. The real-time interference monitoring module, connected to the data processing center, analyzes and calculates the external interference data and outputs the external interference force vector. The thrust distribution optimization module is connected to the ship dynamics model and the data processing center. The mechanical model and real-time disturbance monitoring module are connected. Combining ship motion trend data and external disturbance force vectors, a preliminary thrust allocation scheme is generated by solving a quadratic programming problem. The dynamic constraint processing module is connected to the thrust allocation optimization module. Based on the maximum thrust limit and total power limit of the thruster, the preliminary thrust allocation scheme is modified for feasibility and a compliant thrust scheme is output. The thrust command generation module is connected to the dynamic constraint processing module. The compliant thrust scheme is converted into an executable thrust control command. The thruster execution module is connected to the thrust command generation module. It receives the executable thrust control command output by the thrust command generation module and adjusts the thrust magnitude and angle of the thruster to achieve ship dynamic positioning. The ship status feedback module monitors the ship positioning status and the thruster working status and outputs feedback data. The system optimization and adjustment module is connected to the ship status feedback module. It dynamically adjusts the system parameters according to the feedback data, forming a complete closed-loop architecture.

[0063] The implementation principle of this invention is as follows: Through the closed-loop logical collaborative operation of "modeling-monitoring-constraint-optimization", a ship dynamics model covering six degrees of freedom motion is constructed based on Newton's second law. This model comprehensively considers factors such as the ship's inertia, damping, and external disturbances. Combining ship design drawings, model test data, and actual navigation data, core parameters such as the inertia matrix and damping matrix are determined using system identification methods such as the least squares method and the maximum likelihood method. These parameters can be dynamically corrected according to different operating conditions such as full load and empty load, as well as different sea states, providing a precise mathematical basis for thrust distribution. For the three core external disturbances of wind, waves, and current, dedicated sensors such as anemometers, wind direction meters, wave sensors, and current meters are used to collect parameters such as wind speed, wind direction, wave height, wavelength, wave direction, and current velocity. Then, wind forces are established using aerodynamics, linear wave theory, and fluid mechanics principles. Wave action Flow forces The quantitative model transforms physical parameters into disturbance force vectors. Then, a Kalman filter algorithm is used to fuse multi-sensor data and remove noise through prediction and update equations, outputting a high-precision estimate of the external disturbance force as a reliable input for real-time thrust allocation adjustment. This integrates the maximum and minimum thrust limits of the thrusters. Total power limit Maximum and minimum turning angle limits , Three types of constraints are transformed into a unified set of mathematical inequalities to clarify the safety boundary of thrust allocation. The projection gradient method is adopted, which involves initializing feasible solutions, calculating unconstrained gradients, projecting the gradients onto the feasible region, updating the solutions, and iteratively converging. This ensures that the thrust and rotation angle obtained in each iteration satisfy the constraints and converge quickly to the optimal solution, balancing the safety of the power system with the optimization effect of thrust allocation. Based on model predictive control theory, a dual objective function of "minimizing ship positioning error + minimizing propeller energy consumption" is constructed. Through the positioning error weighting matrix and thrust weighted matrix The priorities of the two objectives are dynamically adjusted, and the six-degree-of-freedom dynamic model is discretized using the Euler method to obtain the velocity update formula. Position and heading update formulas Predicting future based on current ship condition and disturbance forces The motion trend at each moment transforms the dynamic constraints into a system of linear inequalities. The optimal thrust vector is obtained by quickly solving the quadratic programming problem using the interior point method. Simultaneously, it continuously monitors changes in external disturbances and the ship's positioning and thruster operating status, it iterates and repeats the "prediction-optimization-solution" process in real time to update the thrust allocation scheme, and ultimately achieves deep coupling of each link through modeling to provide a precise calculation basis, monitoring to provide real-time disturbance input, constraints to define safety boundaries, optimization to output the optimal solution, and feedback to drive closed-loop iteration.

[0064] The embodiments described herein are preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape, and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for real-time thrust distribution in dynamic positioning of large ships, characterized in that, Includes the following steps: S1. Establish a six-degree-of-freedom dynamic model of the ship in three-dimensional space; S2. Utilize sensor systems to monitor external disturbances such as wind, waves, and currents in real time, and process the monitoring information through data fusion algorithms to estimate the external disturbance forces acting on the ship. S3. Integrate the maximum thrust limit, total power limit, and angle limit of the thruster into a set of mathematical inequality constraints; S4. Based on model predictive control theory, combined with the dynamic model, estimated external disturbance force and mathematical inequality constraints, an optimization problem is constructed with the goal of minimizing ship positioning error and propeller energy consumption. The optimal thrust distribution scheme of each propeller is obtained in real time by solving this problem.

2. The method for real-time thrust distribution in dynamic positioning of a large ship according to claim 1, characterized in that, In the step of establishing a six-degree-of-freedom dynamic model of a ship in three-dimensional space, the basic equations of the dynamic model are: ;in, It is the inertia matrix. For the Coriolis and centripetal force matrices, Here is the damping matrix. For the thrust vector of the propulsion unit, The vector of external disturbance force; The inertia matrix in the dynamic model Coriolis and centripetal matrix and damping matrix It is determined through a systematic identification method and can be corrected in real time based on ship operating conditions and environmental data.

3. The method for real-time thrust distribution in dynamic positioning of a large ship according to claim 1, characterized in that, Step S2, which involves using a sensor system to monitor external disturbances such as wind, waves, and currents in real time, includes: S21. Monitor wind speed using an anemometer and wind direction indicator. and wind direction Calculate the force of wind on a ship The formula is as follows: in, air density, For the windward area of ​​the ship, This refers to the wind resistance coefficient. S22. Monitor wave parameters using wave sensors and calculate the force of waves on the ship. The formula is as follows: in, The density of seawater, It is the acceleration due to gravity. For the ship in the Hydrodynamic coefficients at wave frequencies, For the first The amplitude of each wave component The direction function of wave force. The attitude angle of the ship; S23. Monitoring ocean current speed using a current meter. and flow direction And calculate the force of the flow on the ship. The formula is as follows: in, The density of seawater, The projected area of ​​the ship in the direction of the water flow. This is the flow resistance coefficient; S24. The Kalman filter algorithm is used to fuse and filter the monitoring data from multiple sensors.

4. The method for real-time thrust distribution in dynamic positioning of a large ship according to claim 1, characterized in that, Step S3 specifically includes: S31. Define the thrust constraint conditions of the thruster and establish the mathematical expression for the thrust constraint, as follows: in, , The first Minimum and maximum thrust of each thruster For the number of thrusters; S32. Define the total power constraint condition of the thruster and establish the mathematical expression for the total power constraint, as follows: in, For the first The power of each thruster For the first The power coefficient of each thruster This is the upper limit of the total power of the thruster system; S33. Define the thruster rotation angle constraint conditions and establish the mathematical expression for the rotation angle constraint, as follows: in, , The first Minimum and maximum rotation angles of each thruster; S34. Integrate the mathematical expressions corresponding to the above thrust constraints, total power constraints and rotation constraints into a unified set of mathematical inequality constraints.

5. A method for real-time thrust distribution in dynamic positioning of a large ship according to claim 1, characterized in that, Step S3 further includes S35: processing the mathematical inequality constraints integrated in S34 using the projection gradient method, the specific steps of which are as follows: S351, Initialize the thruster's thrust and corner This ensures that it satisfies the unified mathematical inequality constraints described in S34; S352. Calculate the gradient of the objective function. S353, the gradient Projecting the gradient onto the feasible region that satisfies the S34 constraint, we obtain the projection gradient. S354. Update the thrust and rotation angle of the thruster according to the projection gradient, using the following update formula: in, Step size, This represents the number of iterations. S355. Repeat steps S352 to S354 until the convergence condition is met, ensuring that the thrust and rotation angle obtained in each iteration are within the feasible region.

6. The method for real-time thrust distribution in dynamic positioning of a large ship according to claim 1, characterized in that, The S4 step includes: S41. To minimize ship positioning error and propeller energy consumption, construct the objective function, the formula of which is as follows: in, To predict the time domain, This is the weighted matrix of positioning errors. for Diagonal positive definite matrix Indicates based on Time information prediction Positioning error at any moment express The thrust vector at time t; S42. The six-degree-of-freedom dynamic model is discretized using the Euler method, and the velocity update formula and position-heading update formula are derived as follows: The speed update formula is: The update equations for position and heading are: in Sampling time, This is the transformation matrix corresponding to three-degree-of-freedom motion; Predicting the future using discretization models The ship's status at any given moment; S43. Based on the thruster constraint conditions determined in step S3, combined with the thruster thrust constraint... Power constraints (ki is the power coefficient of the i-th thruster) and the rotation angle constraint are used to complete the constraint transformation, resulting in a unified system of linear inequalities. ,in, The constraint coefficient matrix, The constant vectors are all generated from the dynamic constraints. S44. Minimize the objective function With the goal of using a system of linear inequalities To constrain the problem, a quadratic programming problem is constructed, and the interior-point method is used to solve it to obtain the optimal thrust vector. Real-time monitoring of external interference information and changes in ship status; continuous repetition of steps S41 to S44; dynamic updating of thrust distribution scheme to ensure real-time thrust distribution.

7. A real-time thrust distribution system for dynamic positioning of large ships according to claim 1, characterized in that, include: The sensor data acquisition module is used to acquire real-time data on the ship's position, attitude, and external disturbances such as wind, waves, and currents. The data processing center is connected to the sensor data acquisition module and is used to perform noise reduction and fusion processing on the acquired data, and output ship status data and external interference data. The ship dynamics model is connected to the data processing center and is used to predict the ship's motion state based on discretized equations and output real-time ship motion trend data. The real-time interference monitoring module is connected to the data processing center and is used to analyze and calculate external interference data and output external interference force vector. The thrust allocation optimization module is connected to the ship dynamics model and the real-time disturbance monitoring module, respectively. It is used to generate a preliminary thrust allocation scheme by combining ship motion trend data and external disturbance force vectors and solving a quadratic programming problem. The dynamic constraint processing module is connected to the thrust allocation optimization module and is used to perform feasibility correction on the initial thrust allocation scheme based on the maximum thrust limit and total power limit of the thruster, and output a compliant thrust scheme. The thrust command generation module is connected to the dynamic constraint processing module and is used to convert the compliant thrust scheme into executable thrust control commands. The thruster execution module is connected to the thrust command generation module and is used to receive executable thrust control commands, adjust the thrust magnitude and angle of the thruster, and realize ship dynamic positioning. The ship status feedback module is used to monitor the ship's positioning status and propeller operating status, and output feedback data; The system optimization and adjustment module is connected to the ship status feedback module and is used to dynamically adjust system parameters based on feedback data.

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