Intelligent combined fleet sea state adaptation system

Abstract

The application relates to the technical field of sea state adaptation of a fleet, and discloses an intelligent combined fleet sea state adaptation system, which comprises a main wave direction and wave number measurement module, an efficiency observation calculation module, a scale rotation determination module, a target position and pose generation module, a position and pose error control module, a speed limit correction module and a thrust distribution adjustment module; the main wave direction and wave number measurement module is used for collecting the positions, headings and vertical accelerations of the whole fleet and calculating the main wave direction and wave number; the efficiency observation calculation module is used for calculating the sheltering efficiency value and the observability value; the scale rotation determination module is used for determining the first scale and the first rotation angle; the target position and pose generation module is used for generating the target positions and target headings of the slave ships; the position and pose error control module is used for generating the steering rate and acceleration instructions; the speed limit correction module is used for correcting the instructions according to the sea state speed limit; and the thrust distribution adjustment module is used for adjusting the thrust distribution in combination with the equipment limit. The application realizes the stable formation navigation and observation performance guarantee of the fleet in complex sea states.

Description

Technical Field

[0001] This invention belongs to the field of fleet sea state adaptation technology, specifically relating to an intelligent combined fleet sea state adaptation system. Background Technology

[0002] With the expansion of maritime operations and the diversification of missions, combined fleets are increasingly used in ocean shipping, marine engineering, and maritime rescue. However, complex and ever-changing sea conditions place higher demands on the stability, safety, and operational efficiency of fleet formations. During actual navigation, ships are affected by various marine environmental factors such as dominant wave direction, wave height, and wave frequency. These factors not only cause changes in ship attitude and motion disturbances but also significantly affect the shielding effectiveness, observability, and collision avoidance safety of the formation. Traditional fleet control methods rely heavily on static navigation parameter settings, lacking the ability to dynamically perceive and adaptively adjust to real-time sea conditions, making it difficult to maintain the stability of the formation structure while simultaneously meeting mission execution requirements.

[0003] In existing technologies, some methods attempt to estimate sea state using the motion response of a single ship or a small number of ships. However, due to limited observation baselines, it is difficult to accurately invert the dominant wave direction and wave number, resulting in insufficient accuracy and robustness of sea state adaptation strategies. Furthermore, in optimizing formation scale and rotation angle, commonly used methods based on human experience or fixed rules suffer from low search efficiency and are prone to getting trapped in local optima, failing to efficiently balance shielding, observation, and collision avoidance performance under multi-objective constraints. Summary of the Invention

[0004] This invention provides an intelligent combined fleet sea state adaptation system, which solves the technical problems of insufficient formation stability, decreased observation performance and unreasonable power distribution of fleets under complex and variable sea states in related technologies.

[0005] This invention provides an intelligent combined fleet sea state adaptation system, comprising:

[0006] The dominant wave parameter measurement module is used to obtain the position, heading, and bow vertical acceleration of the entire fleet, filter the bow vertical acceleration to determine the dominant wave frequency, extract the motion phase of each ship, calculate the phase difference, and obtain the wave number vector based on the phase difference and the position difference between ships to obtain the dominant wave direction and wave number magnitude.

[0007] The effectiveness observation and calculation module is used to calculate the shielding effectiveness value based on the dominant wave direction, wave number, formation rotation angle, formation scale, and the sum of the distances from the shielding ship on the windward side to the boundary of the stable corridor in the reference geometry; and to construct an array observation matrix based on the formation rotation angle, formation scale, and the relative positions of each ship in the reference geometry to calculate the observability value.

[0008] The scale rotation determination module is used to set the minimum threshold for shielding effectiveness, the minimum threshold for observability, and the collision avoidance constraint. It calculates the minimum scale that satisfies the shielding effectiveness threshold, the observability threshold, and the collision avoidance constraint, respectively, takes the maximum value among them, and compares it with the upper limit of the maximum scale to obtain the first scale; the formation rotation angle consistent with the dominant wave direction is taken as the first rotation angle.

[0009] The target pose generation module is used to rotate and scale the relative positions of each follower ship in the reference geometry to generate the target position of each follower ship, and set the target heading of the entire fleet as the first rotation angle.

[0010] The position and orientation error control module is used to obtain the actual position and heading of each ship, calculate the position error and error change rate by combining the target position and target heading, generate speed command value and heading command value, and convert them into turning rate command and acceleration command.

[0011] The speed limit correction module is used to calculate the variance based on the bow vertical acceleration of the entire fleet, take the maximum variance value and combine it with the reference speed, minimum safe speed and sea state sensitivity coefficient to determine the speed limit, and perform speed limit correction on speed commands and turning rate commands.

[0012] The thrust distribution adjustment module is used to distribute thrust based on the corrected speed command and steering rate command, combined with equipment thrust and rudder angle limits.

[0013] Furthermore, the bow vertical acceleration is filtered to determine the dominant wave frequency, the motion phase of each ship is extracted, the phase difference is calculated, and the wave number vector is obtained based on the phase difference and the position difference between ships, thus obtaining the dominant wave direction and wave number magnitude, including:

[0014] Step 11: The vertical acceleration of the bow is processed by bandpass filtering, and Fourier transform is performed on the filtered vertical acceleration of the bow to calculate the power spectral density of each ship. The frequency corresponding to the maximum power spectral density is taken as the dominant wave frequency.

[0015] Step 12: Based on the dominant wave frequency, extract the motion phase of each ship, and calculate the phase difference between two ships by subtracting the motion phases;

[0016] Step 13: Obtain the position difference between the two ships, establish a linear relationship between the phase difference and the corresponding position difference between the ships, construct a system of equations that includes all ship pairs, solve the system of equations using the least squares method to obtain the wave number vector, determine the dominant wave direction based on the directional component of the wave number vector, and determine the wave number magnitude based on the magnitude of the wave number vector.

[0017] Furthermore, in step 13, before constructing the equation set and solving the wave number vector using the phase difference and the inter-ship position difference, the ship pairs participating in the calculation are geometrically screened. By calculating the modulus of the inter-ship position difference of each ship pair, ship pairs whose modulus of the inter-ship position difference is greater than a preset baseline threshold are selected for constructing the equation set.

[0018] Furthermore, the shielding effectiveness value is calculated based on the dominant wave direction, wave number, formation rotation angle, formation size, and the sum of the distances from the windward shielding vessel to the boundary of the stable corridor in the reference geometry, including:

[0019] Step 21: Multiply the formation scale by the sum of the distances from the upwind shielding ship to the boundary of the statically stable corridor in the reference geometry to obtain the equivalent shielding length. The formation scale is a uniform scaling ratio applied to the reference geometry, which represents the fixed relative coordinate arrangement of each follower ship relative to the leader ship at a unit scale.

[0020] Step 22: Calculate the angle between the dominant wave direction and the formation rotation angle, and use the product of the absolute value of the cosine of the angle, the wave number, and the equivalent shielding length as the shielding effectiveness index.

[0021] Step 23: Substitute the shielding effectiveness index into an exponential function containing an attenuation coefficient to calculate the shielding effectiveness value.

[0022] Furthermore, based on the formation rotation angle, formation scale, and the relative positions of each ship in the reference geometry, an array observation matrix is ​​constructed, and observability values ​​are calculated, including:

[0023] Step 31: Define a rotation matrix based on the formation rotation angle and formation scale. Calculate the relative displacement per unit scale for any ordered ship pair. Multiply the rotation matrix by the formation scale and the relative displacement in sequence to obtain the baseline vector.

[0024] Step 32: Arrange the baseline vectors of each ship pair in order to construct an array observation matrix, where each row of the array observation matrix corresponds to the baseline vector between a pair of ships.

[0025] Step 33: Calculate the determinant of the array observation matrix as the observability value.

[0026] Furthermore, the process of obtaining the first scale includes:

[0027] Step 41: When the formation rotation angle is taken as the dominant wave direction, take the absolute value of the cosine of the angle between the dominant wave direction and the formation rotation angle as 1, take the product of the wave number, the equivalent shielding length and the attenuation coefficient as the denominator, take the logarithm of the difference between 1 and the minimum shielding effectiveness threshold and take the opposite as the numerator, and take the ratio of the numerator to the denominator as the minimum scale to satisfy the minimum shielding effectiveness threshold.

[0028] Step 42: When the formation rotation angle is taken as the dominant wave direction, calculate the determinant value of the reference baseline matrix under that rotation angle, and take the fourth root of the ratio of the minimum observability threshold to the determinant value to obtain the minimum scale that satisfies the observability threshold; wherein, the reference baseline matrix is ​​formed by rotating the relative displacement of the ship pair under the unit scale.

[0029] Step 43: The ratio of the minimum allowable inter-ship distance to the minimum inter-ship distance under the reference geometry is used as the minimum scale under the collision avoidance constraint;

[0030] Step 44: Take the maximum value among the three minimum scales in steps 41 to 43 as the feasible lower limit. Within the interval formed by the feasible lower limit and the upper limit of the maximum scale of the formation, use Bayesian optimization to select the final scale and use it as the first scale.

[0031] Furthermore, Bayesian optimization is used to select the final scale, including:

[0032] Step 51: Select multiple initial scale samples within the interval formed by the feasible lower limit and the maximum scale upper limit of the formation, calculate the shading effectiveness value and observable value of each sample, and perform weighted summation according to preset weights to obtain the comprehensive effectiveness index. Using the comprehensive effectiveness index, establish a surrogate model based on Gaussian process regression and output the predicted mean.

[0033] Step 52: During the optimization process, the predicted mean is combined with the feasibility probability that meets the feasibility discrimination condition to construct the acquisition function. The feasibility discrimination condition means that the shading effectiveness value is not lower than the set effectiveness threshold and the observability value is not lower than the set observability threshold. In each iteration, the scale with the largest value of the acquisition function within the interval is selected for evaluation.

[0034] Step 53: When the number of iterations reaches the maximum number of iterations, the scale with the highest comprehensive performance index and that meets the feasibility judgment conditions during the iteration process is determined as the first scale.

[0035] Furthermore, the pose error control module specifically includes:

[0036] Step 61: Subtract the target position from the actual position to obtain the position error; subtract the position error of the previous sampling period from the position error of the current sampling period, and divide by the sampling period to obtain the position error change rate; wherein, the actual position, target position, and position error are all represented by two-dimensional column vector encoding.

[0037] Step 62: Multiply the position error by the proportional coefficient and take the opposite number; multiply the position error change rate by the differential coefficient and take the opposite number; add the two together to obtain the velocity command vector in vector form; calculate the magnitude of the velocity command vector to obtain the velocity command value; calculate the arctangent of the ratio of the longitudinal component to the lateral component of the velocity command vector to obtain the heading command value.

[0038] Step 63: Subtract the actual heading from the heading command value to obtain the heading difference. Normalize the heading difference and divide it by the sampling period to obtain the original steering rate command. Limit it according to the maximum steering rate threshold to obtain the steering rate command. Subtract the actual speed from the speed command value and divide it by the sampling period to obtain the original acceleration command. Limit it according to the maximum acceleration threshold to obtain the acceleration command.

[0039] Furthermore, the speed limiting correction module specifically includes:

[0040] Step 71: Calculate the variance of the vertical acceleration of each bow section, and take the maximum value as the maximum variance.

[0041] Step 72: Multiply the maximum variance and the sea state sensitivity coefficient, and then multiply them by the preset time constant to obtain the speed correction amount. Subtract the speed correction amount from the base speed to obtain the sea state corrected speed. Compare the sea state corrected speed with the minimum safe speed and take the larger value as the speed limit.

[0042] Step 73: If the speed command value is greater than the speed limit, then the speed command value is corrected to the speed limit; otherwise, the original value is kept, and the steering ratio command is scaled proportionally according to the ratio of the speed command values ​​before and after correction to obtain the corrected speed command value and steering ratio command.

[0043] Furthermore, based on the revised speed and steering rate commands, and in conjunction with equipment thrust and rudder angle limits, thrust allocation is performed, including:

[0044] Step 81: Obtain the corrected speed command and steering rate command, calculate the resultant force required to achieve the speed change based on the ship kinematics model, and decompose the resultant force into longitudinal force components and lateral force components in combination with the thrust limit of the propulsion device and the rudder angle limit of the steering gear.

[0045] Step 82: Distribute the longitudinal force component according to the position distribution and thrust capability of the propulsion device to generate thrust commands for each propulsion device; convert the lateral force component into rudder angle commands for each rudder device by combining the installation position and hydrodynamic characteristics of the servo motor.

[0046] Step 83: After thrust allocation is completed, the shielding effectiveness value and observability value are detected. If the time for any index to be lower than the corresponding set threshold exceeds the corresponding preset time window, scale adjustment and formation adjustment are performed.

[0047] The beneficial effects of this invention are as follows: The dominant wave parameter measurement module extracts the dominant wave direction and wave number, achieving high-precision perception of complex sea conditions. The effectiveness observation and calculation module simultaneously quantifies shielding effectiveness and observability, enabling the formation to maintain good observation capabilities while avoiding wave interference. The scale rotation determination module integrates shielding effectiveness, observability, and collision avoidance constraints, using intelligent optimization methods to determine the optimal formation scale and rotation angle, improving deployment adaptability and safety. The target pose generation and pose error control modules work together to enable each ship to quickly adjust to the optimal formation, reducing phase difference and navigation errors. The speed limit correction module introduces a sea state sensitivity coefficient for dynamic speed limiting, preventing excessive speed from causing structural or maneuvering risks. The thrust distribution adjustment module combines equipment physical limitations and effectiveness feedback to distribute thrust and rudder angles, further improving control accuracy and system stability. The overall solution possesses the advantages of adaptability, efficiency, and robustness, making it suitable for intelligent fleet collaborative navigation in complex and variable sea conditions. Attached Figure Description

[0048] Figure 1 This is a schematic diagram of a module of an intelligent combined fleet sea state adaptation system according to the present invention. Detailed Implementation

[0049] The subject matter described herein will now be discussed with reference to exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and implement the subject matter described herein, and changes may be made to the function and arrangement of the elements discussed without departing from the scope of this specification. Various processes or components may be omitted, substituted, or added as needed in the examples. Furthermore, features described in some examples may be combined in other examples.

[0050] like Figure 1 As shown, an intelligent combined fleet sea state adaptation system includes:

[0051] The dominant wave parameter measurement module is used to obtain the position, heading, and bow vertical acceleration of the entire fleet, filter the bow vertical acceleration to determine the dominant wave frequency, extract the motion phase of each ship, calculate the phase difference, and obtain the wave number vector based on the phase difference and the position difference between ships to obtain the dominant wave direction and wave number magnitude.

[0052] The effectiveness observation and calculation module is used to calculate the shielding effectiveness value based on the dominant wave direction, wave number, formation rotation angle, formation scale, and the sum of the distances from the shielding ship on the windward side to the boundary of the stable corridor in the reference geometry; and to construct an array observation matrix based on the formation rotation angle, formation scale, and the relative positions of each ship in the reference geometry to calculate the observability value.

[0053] The scale rotation determination module is used to set the minimum threshold for shielding effectiveness, the minimum threshold for observability, and the collision avoidance constraint. It calculates the minimum scale that satisfies the shielding effectiveness threshold, the observability threshold, and the collision avoidance constraint, respectively, takes the maximum value among them, and compares it with the upper limit of the maximum scale to obtain the first scale; the formation rotation angle consistent with the dominant wave direction is taken as the first rotation angle.

[0054] The target pose generation module is used to rotate and scale the relative positions of each follower ship in the reference geometry to generate the target position of each follower ship, and set the target heading of the entire fleet as the first rotation angle.

[0055] The position and orientation error control module is used to obtain the actual position and heading of each ship, calculate the position error and error change rate by combining the target position and target heading, generate speed command value and heading command value, and convert them into turning rate command and acceleration command.

[0056] The speed limit correction module is used to calculate the variance based on the bow vertical acceleration of the entire fleet, take the maximum variance value and combine it with the reference speed, minimum safe speed and sea state sensitivity coefficient to determine the speed limit, and perform speed limit correction on speed commands and turning rate commands.

[0057] The thrust distribution adjustment module is used to distribute thrust based on the corrected speed command and steering rate command, combined with equipment thrust and rudder angle limits.

[0058] In one embodiment of the present invention, the position of the entire fleet is collected by the Beidou navigation satellite system and represented by coordinates; the heading is provided by the inertial navigation system, which outputs the angle between the bow direction and due north; the vertical acceleration of the bow is collected by an acceleration sensor installed on the bow deck and processed into a digital signal by a conditioning circuit.

[0059] In one embodiment of the present invention, the bow vertical acceleration is filtered to determine the dominant wave frequency, the motion phase of each ship is extracted, the phase difference is calculated, and the wave number vector is obtained based on the phase difference and the position difference between ships to obtain the dominant wave direction and wave number magnitude, including:

[0060] Step 11: Bandpass filtering is used to process the bow vertical acceleration, and Fourier transform is performed on the filtered bow vertical acceleration to calculate the power spectral density of each ship. The frequency corresponding to the maximum power spectral density is taken as the dominant wave frequency. Bandpass filtering can eliminate high-frequency noise and low-frequency interference, focusing it on the frequency band where the dominant wave frequency is located. Taking the frequency corresponding to the maximum power spectral density as the dominant wave frequency can effectively identify the frequency component with the most concentrated wave energy, providing a clear frequency reference for subsequent phase extraction.

[0061] Step 12: Based on the dominant wave frequency, extract the motion phase of each ship, and calculate the phase difference between two ships by subtracting the motion phases;

[0062] Step 13: Obtain the position difference between the two ships, establish a linear relationship between the phase difference and the corresponding position difference, construct a system of equations encompassing all ship pairs, solve the system of equations using the least squares method to obtain the wave number vector, determine the dominant wave direction based on the direction component of the wave number vector, and determine the wave number magnitude based on the magnitude of the wave number vector. Specifically, the position difference between the ships is obtained by subtracting the position vectors obtained from the positions of the two ships; a linear relationship is established using the spatial coherence characteristics of ocean waves. ,in, Indicates phase difference, Represents the wavenumber vector. The wavenumber vector represents the positional difference between ships i and j, where i and j are ship indices; after obtaining the wavenumber vector using the least squares method, it is then processed... Determine the dominant wave direction, among which, Indicates the dominant wave direction, and atan2 represents the arctangent function. This represents the component of the wavenumber vector along the y-axis, i.e., the north-south direction in the fleet coordinate system. It represents the component of the wavenumber vector in the x-axis direction, i.e., the east-west direction in the fleet coordinate system; the magnitude of the wavenumber is determined by the magnitude of the wavenumber vector.

[0063] It should be noted that the wave number vector inversion method based on phase difference is based on the assumption that the waves are dominant unidirectional long-peaked waves. In actual complex sea states with short-peaked waves, the confidence level of the estimation results may decrease. Optionally, the residuals between the phase differences of all ship pairs and the fitted values ​​of the estimated wave number vectors can be calculated. If the mean residual exceeds a preset threshold, it can be determined that the current sea state does not conform to the model assumptions, and the system can switch to an alternative estimation mode based on the leader's motion spectrum analysis or historical average wave direction to ensure the robustness of the system.

[0064] This embodiment achieves robust solution of wave number vector through the least squares method, which can not only accurately invert the dominant wave direction, but also obtain its wave number magnitude, providing key sea state input parameters for dynamic adjustment of the formation, and significantly improving the adaptability and response accuracy to complex sea conditions.

[0065] In one embodiment of the present invention, in step 13, before constructing a set of equations and solving the wave number vector using the phase difference and the inter-ship position difference, the ship pairs involved in the calculation are geometrically screened. By calculating the modulus of the inter-ship position difference of each ship pair, ship pairs whose modulus of the inter-ship position difference is greater than a preset baseline threshold are selected for constructing the set of equations.

[0066] In one embodiment of the present invention, the shielding effectiveness value is calculated based on the dominant wave direction, wave number, formation rotation angle, formation size, and the sum of the distances from the upwind shielding vessel to the boundary of the stable corridor in the reference geometry, including:

[0067] Step 21: Multiply the formation scale by the sum of the distances from the windward shielding ships to the boundary of the stable corridor in the reference geometry to obtain the equivalent shielding length. The formation scale is a uniform scaling ratio applied to the reference geometry, which represents the fixed relative coordinate arrangement of each follower ship relative to the leader ship at a unit scale. The windward shielding ships are a predetermined group of ships located upstream of the dominant wave, and the stable corridor boundary is the boundary line of the target protection area on the back wave side.

[0068] Step 22: Calculate the angle between the dominant wave direction and the formation rotation angle, and use the product of the absolute value of the cosine of the angle, the wave number, and the equivalent shielding length as the shielding effectiveness index.

[0069] Step 23: Substitute the shielding effectiveness index into an exponential function containing an attenuation coefficient to calculate the shielding effectiveness value. The formula for calculating the shielding effectiveness value is as follows: , The value represents the shading effectiveness, and exp represents the exponential function. The value represents the attenuation coefficient, ranging from 0.4 to 1; k represents the wavenumber; and L represents the equivalent shielding length. This indicates the angle between the dominant wave and the rain formation's rotation angle.

[0070] Through the above steps, this embodiment can transform the complex interaction of ocean wave formations into a quantified shielding effectiveness value, which ranges from 0 to 1. The closer the value is to 1, the better the shielding effect. The shielding effectiveness value can not only intuitively reflect the protection capability of the current formation geometry against the calm corridor behind the waves, but also provide a clear quantitative basis for the subsequent optimization of the formation rotation angle and scale. This effectively improves the accuracy and controllability of the system's assessment of the shielding effect, ensuring that the formation can maintain ideal shielding effectiveness under different sea conditions.

[0071] In one embodiment of the present invention, an array observation matrix is ​​constructed based on the formation rotation angle, formation scale, and the relative positions of each ship in the reference geometry, and the observability value is calculated, including:

[0072] Step 31: Define a rotation matrix based on the formation rotation angle and formation scale. Calculate the relative displacement per unit scale for any ordered ship pair. Multiply the rotation matrix by the formation scale and the relative displacement in sequence to obtain the baseline vector. This baseline vector quantifies the actual spatial position difference between the two ships after rotation and scaling.

[0073] Step 32: Arrange the baseline vectors of each ship pair in order to construct an array observation matrix, where each row of the array observation matrix corresponds to the baseline vector between a pair of ships.

[0074] Step 33: Calculate the determinant of the array observation matrix as the observability value; the value of the determinant directly reflects the non-degeneracy of the matrix. The larger the value, the richer the directional distribution of the baseline vector, the stronger the array's ability to resolve the spatial characteristics of the wave field, and the lower the redundancy of the observation information.

[0075] This embodiment establishes a quantitative correlation between formation rotation angle, formation size and observation capability. The resulting observability value provides a key constraint for optimizing formation size, effectively avoiding the decline in wavefield observation capability caused by excessive formation shrinkage or unreasonable orientation, and ensuring that the system maintains reliable sea state perception capability during dynamic adjustment.

[0076] In one embodiment of the present invention, the process of obtaining the first scale includes:

[0077] Step 41: When the formation rotation angle is taken as the dominant wave direction, take the absolute value of the cosine of the angle between the dominant wave direction and the formation rotation angle as 1. Use the product of wave number, equivalent shielding length, and attenuation coefficient as the denominator. Perform a logarithmic operation on the difference between 1 and the minimum shielding effectiveness threshold, and take the opposite as the numerator. Use the ratio of the numerator to the denominator as the minimum scale required to satisfy the minimum shielding effectiveness threshold. The formula for calculating the minimum scale is: , Indicates the smallest scale. This represents the minimum threshold for occlusion effectiveness, used to determine whether the occlusion effectiveness meets the minimum requirements under formation rotation angle.

[0078] Step 42: When the formation rotation angle is taken as the dominant wave direction, calculate the determinant value of the reference baseline matrix under that rotation angle, and take the fourth root of the ratio of the minimum observability threshold to the determinant value to obtain the minimum scale that satisfies the observability threshold; wherein, the reference baseline matrix is ​​formed by rotating the relative displacement of the ship pair under the unit scale; the minimum observability threshold is used to determine whether the observability meets the minimum requirements under the corresponding array geometry.

[0079] Step 43: The ratio of the minimum permissible inter-ship distance to the minimum ship spacing under the reference geometry is taken as the minimum scale under the collision avoidance constraint; wherein, the minimum permissible inter-ship distance is determined by the navigation safety rules, and the minimum ship spacing represents the minimum distance of the fleet per unit scale.

[0080] Step 44: Take the maximum value among the three minimum scales from steps 41 to 43 as the feasible lower bound. Within the interval formed by the feasible lower bound and the upper bound of the maximum formation scale, use Bayesian optimization to select the final scale, which is then used as the first scale, including:

[0081] Step 51: Select multiple initial scale samples within the interval formed by the feasible lower limit and the maximum scale upper limit of the formation, calculate the occlusion effectiveness value and observable value of each sample, and perform weighted summation according to preset weights to obtain the comprehensive effectiveness index. Using the comprehensive effectiveness index, establish a surrogate model based on Gaussian process regression and output the predicted mean. Specifically, the surrogate model assumes that the comprehensive effectiveness index follows a multivariate Gaussian distribution and describes the correlation between samples of different scales through the covariance function. The hyperparameters of the kernel function are fitted using the maximum likelihood estimation method through the radial basis function kernel, so that the model fits the nonlinear mapping relationship between scale and comprehensive effectiveness. The model outputs the predicted mean based on the probability distribution obtained from training.

[0082] Step 52: During the optimization process, a collection function is constructed by combining the predicted mean with the feasibility probability that meets the feasibility discrimination condition. The feasibility discrimination condition means that the occlusion effectiveness value is not lower than a set effectiveness threshold and the observability value is not lower than a set observability threshold. In each iteration, the scale with the largest value of the collection function within the interval is selected for evaluation. The comprehensive effectiveness index, occlusion effectiveness value, and observability value corresponding to this scale are actually calculated to update the training samples and surrogate model. The collection function is used to guide the selection of a new initial scale in each iteration. The value of the collection function is obtained by multiplying the predicted mean and the feasibility probability. This value reflects the expected improvement in comprehensive effectiveness and exploration potential. The feasibility probability is calculated based on the predicted mean and variance through a cumulative distribution function.

[0083] Step 53: When the number of iterations reaches the maximum number of iterations, the scale with the highest comprehensive performance index and that meets the feasibility judgment conditions during the iteration process is determined as the first scale.

[0084] Through the Bayesian optimization process described above, the formation scale with the highest overall performance can be efficiently found while satisfying the constraints of occlusion, observation, and collision avoidance. This avoids the blindness and high computational cost of traditional grid search or random search. At the same time, through the design of the surrogate model and acquisition function, the global optimality and engineering practicality of the optimization results are ensured. This allows the selection of the first scale to be adapted to the current sea state and to balance the performance requirements of multiple objectives, significantly improving the adaptive optimization efficiency of the system.

[0085] In one embodiment of the present invention, the process of generating the target positions of each follower ship and the heading of the entire fleet based on the first rotation angle, the first scale, and the real-time position of the leader ship includes:

[0086] Obtain the first rotation angle, the first scale, and the real-time position of the leader ship;

[0087] The relative positions of each follower ship are transformed. Specifically, for each follower ship's relative position vector in the reference geometry, it is first rotated using a rotation matrix, then multiplied by the first scale to obtain the relative position vector at the actual scale. Finally, the real-time position of the leader ship is added to this relative position vector to generate the target position of the follower ship.

[0088] Set the target heading of the entire fleet as the first rotation angle to ensure that the heading of all ships is consistent with the overall orientation of the formation.

[0089] In one embodiment of the present invention, the actual position and actual heading of each ship are obtained, and the position error and error change rate are calculated by combining the target position and target heading to generate speed command values ​​and heading command values, which are then converted into turning rate commands and acceleration commands, including:

[0090] Step 61: Subtract the target position from the actual position to obtain the position error; subtract the position error of the previous sampling period from the position error of the current sampling period, and divide by the sampling period to obtain the position error change rate; this is used to quantify the dynamic change trend of the position deviation; wherein, the actual position, target position, and position error are all represented by two-dimensional column vector encoding.

[0091] Step 62: Multiply the position error by the proportional coefficient and take the opposite number; multiply the rate of change of the position error by the differential coefficient and take the opposite number; add the two to obtain a velocity command vector in vector form; calculate the magnitude of this velocity command vector to obtain the velocity command value; calculate the arctangent of the ratio of the longitudinal component to the lateral component of this velocity command vector to obtain the heading command value, which is used to guide the adjustment direction of the ship's course; wherein, the proportional coefficient is used to adjust the influence weight of the position error on the velocity command, and its value range is positive real number, which is used to control the convergence speed; the differential coefficient is used to reflect the influence weight of the rate of change of the position error on the velocity command, and its value range is positive real number, which is used to suppress oscillations caused by rapid changes.

[0092] Step 63: Subtract the actual heading from the heading command value to obtain the heading difference. Normalize the heading difference and divide it by the sampling period to obtain the original steering rate command. Limit it according to the maximum steering rate threshold to obtain the steering rate command. Subtract the actual speed from the speed command value and divide it by the sampling period to obtain the original acceleration command. Limit it according to the maximum acceleration threshold to obtain the acceleration command.

[0093] This embodiment achieves the generation of steering rate and acceleration commands that take into account position accuracy, heading adjustment and motion stability by starting from the position and heading errors, thus effectively improving the attitude control accuracy and response stability of the fleet in formation movement.

[0094] In one embodiment of the present invention, the variance is calculated based on the bow vertical acceleration data of the entire fleet. The maximum variance value is then combined with the reference speed, minimum safe speed, and sea state sensitivity coefficient to determine the upper speed limit. Speed ​​commands and turning rate commands are then corrected for speed limits, including:

[0095] Step 71: Calculate the variance of the vertical acceleration of each bow section, and take the maximum value as the maximum variance.

[0096] Step 72: Multiply the maximum variance and the sea state sensitivity coefficient, and then multiply by the preset time constant to obtain the speed correction amount. Subtract the speed correction amount from the base speed to obtain the sea state corrected speed. Compare the sea state corrected speed with the minimum safe speed and take the larger value as the speed limit. The preset time constant is preferably set to 0.2 times the natural period of the ship's pitch. The sea state sensitivity coefficient is used to characterize the sensitivity of the bow vertical acceleration change to the ship's speed limit. Its value ranges from 0 to 1 and is obtained through statistical analysis of historical navigation data. The base speed represents the target cruising speed of the fleet under ideal and stable sea states.

[0097] Step 73: If the speed command value is greater than the speed limit, then the speed command value is corrected to the speed limit; otherwise, the original value is kept, and the steering ratio command is scaled proportionally according to the ratio of the speed command values ​​before and after correction to obtain the corrected speed command value and steering ratio command.

[0098] The above steps not only avoid ship instability and excessive equipment load caused by excessive speed in severe sea conditions, but also ensure the dynamic consistency of course control when speed is limited, thereby improving the overall safety and formation stability of the fleet in complex sea conditions.

[0099] In one embodiment of the present invention, thrust allocation is performed based on the modified speed command and steering rate command, combined with equipment thrust and rudder angle limits; and adjustments are made according to shielding effectiveness and observability values, including:

[0100] Step 81: Obtain the corrected speed command and steering rate command. Calculate the resultant force required to achieve this speed change based on the ship's kinematics model. Combining the thrust limitations of the propulsion system and the rudder angle limitations of the steering gear, decompose the resultant force into longitudinal and lateral force components. The calculation formulas for the longitudinal and lateral force components are as follows: , , This represents the longitudinal force component, used for acceleration and deceleration along the bow direction. This represents the lateral force component, used to control the ship's lateral drift and heading adjustment; m represents the ship's mass. Indicates longitudinal acceleration. Indicates lateral acceleration;

[0101] Step 82: Distribute the longitudinal force component according to the position distribution and thrust capability of the propulsion device to generate thrust commands for each propulsion device; convert the lateral force component into rudder angle commands for each rudder device by combining the installation position and hydrodynamic characteristics of the servo motor.

[0102] Step 83: After the thrust distribution is completed, the shielding effectiveness value and observability value are detected. If the time for which either index is lower than the corresponding set threshold exceeds the corresponding preset time window, it is determined that formation reconfiguration needs to be triggered. The system will set a reconfiguration flag. If the reconfiguration flag is detected after the current control cycle ends, the current pose tracking loop will be interrupted and the system will return to the scale rotation determination module to perform scale adjustment and formation adjustment.

[0103] The thrust distribution mechanism in this embodiment takes into account the physical limitations of the equipment and ensures that the ship can respond to motion commands efficiently through a reasonable force component decomposition and distribution strategy. Furthermore, the closed-loop adjustment based on shielding effectiveness and observability further ensures that the core functions of the formation do not fail under complex sea conditions, significantly improving the robustness and adaptability of the system.

[0104] It should be noted that the interval and threshold sizes are set for ease of comparison. The size of the threshold depends on the amount of sample data and the base number set by those skilled in the art for each set of sample data, as long as it does not affect the proportional relationship between the parameter and the quantized value. Furthermore, the above formulas are all dimensionless calculations, and the formulas are derived from software simulations using a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0105] The embodiments of the present invention have been described above, but the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms based on the guidance of the present embodiments, all of which are within the protection scope of the present embodiments.

Claims

1. An intelligent combined fleet sea state adaptation system, characterized in that, include: The dominant wave parameter measurement module is used to obtain the position, heading, and bow vertical acceleration of the entire fleet, filter the bow vertical acceleration to determine the dominant wave frequency, extract the motion phase of each ship, calculate the phase difference, and obtain the wave number vector based on the phase difference and the position difference between ships to obtain the dominant wave direction and wave number magnitude. The effectiveness observation and calculation module is used to calculate the shielding effectiveness value based on the dominant wave direction, wave number, formation rotation angle, formation scale, and the sum of the distances from the shielding ship on the windward side to the boundary of the stable corridor in the reference geometry; and to construct an array observation matrix based on the formation rotation angle, formation scale, and the relative positions of each ship in the reference geometry to calculate the observability value. The scale rotation determination module is used to set the minimum threshold for shielding effectiveness, the minimum threshold for observability, and the collision avoidance constraint. It calculates the minimum scale that satisfies the shielding effectiveness threshold, the observability threshold, and the collision avoidance constraint, respectively, takes the maximum value among them, and compares it with the upper limit of the maximum scale to obtain the first scale; the formation rotation angle consistent with the dominant wave direction is taken as the first rotation angle. The target pose generation module is used to rotate and scale the relative positions of each follower ship in the reference geometry to generate the target position of each follower ship, and set the target heading of the entire fleet as the first rotation angle. The position and orientation error control module is used to obtain the actual position and heading of each ship, calculate the position error and error change rate by combining the target position and target heading, generate speed command value and heading command value, and convert them into turning rate command and acceleration command. The speed limit correction module is used to calculate the variance based on the bow vertical acceleration of the entire fleet, take the maximum variance value and combine it with the reference speed, minimum safe speed and sea state sensitivity coefficient to determine the speed limit, and perform speed limit correction on speed commands and turning rate commands. The thrust distribution adjustment module is used to distribute thrust based on the corrected speed command and steering rate command, combined with equipment thrust and rudder angle limits.

2. The intelligent combined fleet sea state adaptation system according to claim 1, characterized in that, The bow vertical acceleration is filtered to determine the dominant wave frequency. The motion phases of each ship are extracted, and the phase difference is calculated. Based on the phase difference and the inter-ship position difference, the wave number vector is obtained to determine the dominant wave direction and wave number magnitude, including: Step 11: The vertical acceleration of the bow is processed by bandpass filtering, and Fourier transform is performed on the filtered vertical acceleration of the bow to calculate the power spectral density of each ship. The frequency corresponding to the maximum power spectral density is taken as the dominant wave frequency. Step 12: Based on the dominant wave frequency, extract the motion phase of each ship, and calculate the phase difference between two ships by subtracting the motion phases; Step 13: Obtain the position difference between the two ships, establish a linear relationship between the phase difference and the corresponding position difference between the ships, construct a system of equations that includes all ship pairs, solve the system of equations using the least squares method to obtain the wave number vector, determine the dominant wave direction based on the directional component of the wave number vector, and determine the wave number magnitude based on the magnitude of the wave number vector.

3. The intelligent combined fleet sea state adaptation system according to claim 2, characterized in that, In step 13, before constructing the equation set and solving the wave number vector using the phase difference and the inter-ship position difference, the ship pairs involved in the calculation are geometrically screened. By calculating the modulus of the inter-ship position difference of each ship pair, ship pairs whose modulus of the inter-ship position difference is greater than a preset baseline threshold are selected for constructing the equation set.

4. The intelligent combined fleet sea state adaptation system according to claim 1, characterized in that, The shielding effectiveness is calculated based on the dominant wave direction, wave number, formation rotation angle, formation size, and the sum of the distances from the windward shielding vessel to the boundary of the stable corridor in the reference geometry. This includes: Step 21: Multiply the formation scale by the sum of the distances from the upwind shielding ship to the boundary of the statically stable corridor in the reference geometry to obtain the equivalent shielding length. The formation scale is a uniform scaling ratio applied to the reference geometry, which represents the fixed relative coordinate arrangement of each follower ship relative to the leader ship at a unit scale. Step 22: Calculate the angle between the dominant wave direction and the formation rotation angle, and use the product of the absolute value of the cosine of the angle, the wave number, and the equivalent shielding length as the shielding effectiveness index. Step 23: Substitute the shielding effectiveness index into an exponential function containing an attenuation coefficient to calculate the shielding effectiveness value.

5. The intelligent combined fleet sea state adaptation system according to claim 1, characterized in that, An array observation matrix is ​​constructed based on the formation rotation angle, formation scale, and the relative positions of each ship in the reference geometry. Observability values ​​are calculated, including: Step 31: Define a rotation matrix based on the formation rotation angle and formation scale. Calculate the relative displacement per unit scale for any ordered ship pair. Multiply the rotation matrix by the formation scale and the relative displacement in sequence to obtain the baseline vector. Step 32: Arrange the baseline vectors of each ship pair in order to construct an array observation matrix, where each row of the array observation matrix corresponds to the baseline vector between a pair of ships. Step 33: Calculate the determinant of the array observation matrix as the observability value.

6. The intelligent combined fleet sea state adaptation system according to claim 1, characterized in that, The process of obtaining the first scale includes: Step 41: When the formation rotation angle is taken as the dominant wave direction, take the absolute value of the cosine of the angle between the dominant wave direction and the formation rotation angle as 1, take the product of the wave number, the equivalent shielding length and the attenuation coefficient as the denominator, take the logarithm of the difference between 1 and the minimum shielding effectiveness threshold and take the opposite as the numerator, and take the ratio of the numerator to the denominator as the minimum scale to satisfy the minimum shielding effectiveness threshold. Step 42: When the formation rotation angle is taken as the dominant wave direction, calculate the determinant value of the reference baseline matrix per unit scale under that rotation angle, and take the fourth root of the ratio of the minimum observability threshold to the determinant value to obtain the minimum scale that satisfies the observability threshold; wherein, the reference baseline matrix is ​​formed by rotating the relative displacement of the ship pair per unit scale. Step 43: The ratio of the minimum allowable inter-ship distance to the minimum inter-ship distance under the reference geometry is used as the minimum scale under the collision avoidance constraint; Step 44: Take the maximum value among the three minimum scales in steps 41 to 43 as the feasible lower limit. Within the interval formed by the feasible lower limit and the upper limit of the maximum scale of the formation, use Bayesian optimization to select the final scale and use it as the first scale.

7. The intelligent combined fleet sea state adaptation system according to claim 6, characterized in that, The final scale is selected using Bayesian optimization, including: Step 51: Select multiple initial scale samples within the interval formed by the feasible lower limit and the maximum scale upper limit of the formation, calculate the shading effectiveness value and observable value of each sample, and perform weighted summation according to preset weights to obtain the comprehensive effectiveness index. Using the comprehensive effectiveness index, establish a surrogate model based on Gaussian process regression and output the predicted mean. Step 52: During the optimization process, the predicted mean is combined with the feasibility probability that meets the feasibility discrimination condition to construct the acquisition function. The feasibility discrimination condition means that the shading effectiveness value is not lower than the set effectiveness threshold and the observability value is not lower than the set observability threshold. In each iteration, the scale with the largest value of the acquisition function within the interval is selected for evaluation. Step 53: When the number of iterations reaches the maximum number of iterations, the scale with the highest comprehensive performance index and that meets the feasibility judgment conditions during the iteration process is determined as the first scale.

8. The intelligent combined fleet sea state adaptation system according to claim 1, characterized in that, The pose error control module specifically includes: Step 61: Subtract the target position from the actual position to obtain the position error; subtract the position error of the previous sampling period from the position error of the current sampling period, and divide by the sampling period to obtain the position error change rate; wherein, the actual position, target position, and position error are all represented by two-dimensional column vector encoding. Step 62: Multiply the position error by the proportional coefficient and take the opposite number; multiply the position error change rate by the differential coefficient and take the opposite number; add the two together to obtain the velocity command vector in vector form; calculate the magnitude of the velocity command vector to obtain the velocity command value; calculate the arctangent of the ratio of the longitudinal component to the lateral component of the velocity command vector to obtain the heading command value. Step 63: Subtract the actual heading from the heading command value to obtain the heading difference. Normalize the heading difference and divide it by the sampling period to obtain the original steering rate command. Limit it according to the maximum steering rate threshold to obtain the steering rate command. Subtract the actual speed from the speed command value and divide it by the sampling period to obtain the original acceleration command. Limit it according to the maximum acceleration threshold to obtain the acceleration command.

9. The intelligent combined fleet sea state adaptation system according to claim 1, characterized in that, The speed limiting correction module specifically includes: Step 71: Calculate the variance of the vertical acceleration of each bow section, and take the maximum value as the maximum variance. Step 72: Multiply the maximum variance and the sea state sensitivity coefficient, and then multiply them by the preset time constant to obtain the speed correction amount. Subtract the speed correction amount from the base speed to obtain the sea state corrected speed. Compare the sea state corrected speed with the minimum safe speed and take the larger value as the speed limit. Step 73: If the speed command value is greater than the speed limit, then the speed command value is corrected to the speed limit; otherwise, the original value is kept, and the steering ratio command is scaled proportionally according to the ratio of the speed command values ​​before and after correction to obtain the corrected speed command value and steering ratio command.

10. The intelligent combined fleet sea state adaptation system according to claim 1, characterized in that, Based on the revised speed and steering rate commands, thrust allocation is performed in conjunction with equipment thrust and rudder angle limits, including: Step 81: Obtain the corrected speed command and steering rate command, calculate the resultant force required to achieve the speed change based on the ship kinematics model, and decompose the resultant force into longitudinal force components and lateral force components in combination with the thrust limit of the propulsion device and the rudder angle limit of the steering gear. Step 82: Distribute the longitudinal force component according to the position distribution and thrust capability of the propulsion device to generate thrust commands for each propulsion device; convert the lateral force component into rudder angle commands for each rudder device by combining the installation position and hydrodynamic characteristics of the servo motor. Step 83: After thrust allocation is completed, the shielding effectiveness value and observability value are detected. If the time for any index to be lower than the corresponding set threshold exceeds the corresponding preset time window, scale adjustment and formation adjustment are performed.

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