Ship berthing oscillation suppression control system

Abstract

The present application relates to the field of ship berthing safety and automatic control technology, in particular to a ship wharf berthing oscillation suppression control system, comprising an environment and state sensing unit for generating a dominant excitation frequency; a system dynamic characteristic identification unit for real-time estimating the current equivalent stiffness and equivalent damping of the ship mooring system; a resonance risk assessment unit for calculating the current system natural frequency and calculating the resonance risk index; a variable parameter active control unit for comparing the resonance risk index with a preset risk activation threshold; when the resonance risk index is not less than the risk activation threshold, a cooperative control instruction is calculated; when it is less than the risk activation threshold, the variable parameter active control unit generates a high-precision pose maintenance instruction; the present application eliminates the resonance condition through the advanced avoidance mechanism, improves the safety of ship berthing operation, and effectively prevents the risk of rope rupture or ship collision caused by oscillation aggravation.

Description

Technical Field

[0001] This invention relates to the field of ship berthing safety and automatic control technology, specifically a ship dock berthing oscillation suppression control system. Background Technology

[0002] When a ship is berthing at a dock, the hull, cables, and dock form a coupled dynamic system. This system is subject to continuous disturbances from environmental factors such as waves, resulting in oscillating motion. Such oscillations pose a potential threat to berthing stability and safety.

[0003] The key technical problem is that when the excitation frequency of external waves is close to the natural frequency of the mooring system itself, it will cause system resonance. Resonance will cause the ship displacement and cable tension to be amplified sharply, which may lead to serious safety accidents such as cable fatigue breakage or collision with the dock. Traditional control methods are mostly passive responses, that is, suppression after the oscillation occurs. However, this method has a delay and is difficult to cope with the real-time changes in the dynamic characteristics of the system. Due to the continuous changes in ship position, cable length and tension, the natural frequency of the system is time-varying, which makes it extremely difficult to predict and avoid resonance in advance. Therefore, the existing technology is insufficient in eliminating resonance conditions and actively ensuring system safety, and it is difficult to meet the dual requirements of high-precision positioning and high-safety operation. Summary of the Invention

[0004] To solve the above-mentioned technical problems, the present invention provides a ship dock berthing oscillation suppression control system. Specifically, the technical solution of the present invention includes:

[0005] An environment and state sensing unit is used to collect wave height time series data, cable tension data, ship displacement data, and ship speed data; the environment and state sensing unit is also used to process the wave height time series data to generate the dominant excitation frequency;

[0006] The system dynamic characteristic identification unit is used to estimate the current equivalent stiffness and equivalent damping of the ship mooring system in real time based on the cable tension data, the ship displacement data, the ship speed data and the dominant excitation frequency through an online parameter identification algorithm.

[0007] The resonance risk assessment unit is used to calculate the current system natural frequency based on the equivalent stiffness and the preset total equivalent mass of the system; the resonance risk assessment unit is also used to calculate the resonance risk index by combining the current system natural frequency and the dominant excitation frequency;

[0008] A variable parameter active control unit is used to compare the resonance risk index with a preset risk activation threshold;

[0009] When the resonance risk index is not less than the risk activation threshold, the variable parameter active control unit generates the target equivalent stiffness and the target equivalent damping, and calculates the cooperative control command based on the target equivalent stiffness and the target equivalent damping.

[0010] When the resonance risk index is less than the risk activation threshold, the variable parameter active control unit generates a high-precision pose maintenance command.

[0011] Preferably, the environment and state perception unit obtains the wave energy spectrum by performing a fast Fourier transform on the wave height time series data, and extracts the angular frequency corresponding to the peak value in the wave energy spectrum as the dominant excitation frequency.

[0012] Preferably, the resonance risk assessment unit calculates the resonance risk index by using a preset Gaussian function model and inputting the frequency difference between the current system's natural frequency and the dominant excitation frequency.

[0013] Preferably, the variable parameter active control unit calculates the target equivalent stiffness by using a preset S-shaped function and inputting the ratio of the resonance risk index to the risk activation threshold, between a preset high-precision mode stiffness and a preset safety avoidance mode stiffness.

[0014] Preferably, the variable parameter active control unit calculates the target equivalent damping by using a preset function and inputting the ratio of the resonance risk index to the risk activation threshold, between the inherent natural damping of the system identified by the system dynamic characteristic identification unit and the preset maximum active damping of the system.

[0015] Preferably, the process by which the variable parameter active control unit calculates the cooperative control command is as follows:

[0016] Based on the target equivalent stiffness, the target tension command of each cable winch is calculated by the inverse dynamics model.

[0017] Based on the target equivalent damping, the speed control commands for each cable winch are calculated using the inverse dynamics model.

[0018] The coordinated control command is generated by combining the target tension command and the speed control command.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] 1. This system can proactively avoid resonance risks rather than passively suppress oscillations. By identifying the dynamic characteristics of the system in real time, it can predict the degree of proximity between the external excitation frequency and the system's natural frequency, and proactively adjust the system's equivalent stiffness and damping before resonance occurs, adjusting the natural frequency to a safe range. This proactive avoidance mechanism eliminates resonance conditions, improves the safety of ship berthing operations, and effectively prevents the risk of cable breakage or ship collision with shore caused by intensified oscillations.

[0021] 2. This system achieves adaptive control of time-varying systems, improving control accuracy. During berthing, the ship's dynamic characteristics constantly change with factors such as position, attitude, and cable status. Through an online parameter identification algorithm, this system can accurately and in real-time obtain the system's current equivalent stiffness and damping, ensuring that control decisions are always based on the system's most realistic dynamic model. This adaptive capability enables it to precisely respond to various operating conditions, guaranteeing the continuous effectiveness of the control strategy.

[0022] 3. This system makes control decisions more scientific and reliable by establishing a quantitative resonance risk index. It not only considers the proximity of the excitation frequency to the natural frequency, but also incorporates factors such as wave energy intensity, transforming the abstract resonance risk into a precise mathematical measure. This quantitative assessment provides a clear basis for switching control modes, avoiding the ambiguity of traditional methods that rely on experience or simple threshold judgments, and making risk warning and avoidance responses more timely and accurate.

[0023] 4. This system, through intelligent dual-mode control, balances the dual requirements of high-precision berthing and high safety. When the resonance risk is low, the system aims to maintain high-precision pose to ensure operational efficiency. When the risk index exceeds the threshold, it seamlessly switches to active avoidance mode to prioritize safety. This design resolves the contradiction between high-rigidity positioning and high-flexibility risk avoidance in traditional technologies, achieving an effective balance between operational accuracy and system safety, and improving the overall performance of the system. Attached Figure Description

[0024] The present invention will be further explained below with reference to the accompanying drawings and embodiments:

[0025] Figure 1 This is a structural diagram of the system of the present invention. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments. Example 1:

[0027] Please see Figure 1 The ship berthing vibration suppression control system includes:

[0028] An environment and state sensing unit is used to collect wave height time series data, cable tension data, ship displacement data, and ship speed data; the environment and state sensing unit is also used to process the wave height time series data to generate the dominant excitation frequency;

[0029] The system dynamic characteristic identification unit is used to estimate the current equivalent stiffness and equivalent damping of the ship mooring system in real time based on the cable tension data, the ship displacement data, the ship speed data and the dominant excitation frequency through an online parameter identification algorithm.

[0030] The resonance risk assessment unit is used to calculate the current system natural frequency based on the equivalent stiffness and the preset total equivalent mass of the system; the resonance risk assessment unit is also used to calculate the resonance risk index by combining the current system natural frequency and the dominant excitation frequency;

[0031] A variable parameter active control unit is used to compare the resonance risk index with a preset risk activation threshold;

[0032] When the resonance risk index is not less than the risk activation threshold, the variable parameter active control unit generates the target equivalent stiffness and the target equivalent damping, and calculates the cooperative control command based on the target equivalent stiffness and the target equivalent damping.

[0033] When the resonance risk index is less than the risk activation threshold, the variable parameter active control unit generates a high-precision pose maintenance command.

[0034] This embodiment provides a ship dock berthing vibration suppression and control system, which aims to eliminate the conditions for resonance in the ship-cable-shore coupling system by actively avoiding rather than passively suppressing it. The system constitutes a complete technical closed loop from environmental perception, system identification, risk assessment to decision execution.

[0035] The system includes: an environment and state perception unit, a system dynamic characteristic identification unit, a resonance risk assessment unit, and a variable parameter active control unit;

[0036] The environment and state perception unit functions to acquire external environmental excitation information and the ship's own state information in real time and accurately, providing necessary data input for subsequent system identification and risk assessment. In this embodiment, the unit continuously collects wave height time series data of the operating sea area through sensors such as radar or wave buoys configured near the dock. The wave height time series data is a series of wave surface height values ​​recorded in chronological order, reflecting the dynamic process of external wave disturbances. The source is the direct measurement value of physical sensors. At the same time, through tension sensors installed on the cable, shipborne inertial measurement unit (IMU), and global positioning system (GPS), the unit synchronously collects real-time tension data of the cable, precise displacement data of the ship, and real-time speed data. The unit is also responsible for processing the collected wave height time series data to generate the dominant excitation frequency. The dominant excitation frequency is the wave frequency that carries the most concentrated energy under the current sea state. It represents the external excitation source that poses the greatest potential threat to the mooring system. Its value is determined by subsequent spectrum analysis.

[0037] The system dynamic characteristic identification unit is designed to determine the intrinsic physical characteristics of the entire ship-cable-shore coupling system in real time, namely the equivalent stiffness and equivalent damping, to address the time-varying nature of the system caused by cable extension and contraction and changes in ship attitude during operation. In this embodiment, the unit simplifies the complex mooring system into a second-order oscillating system model in a specific degree of freedom.

[0038] This simplification is based on the following considerations: When a ship is subjected to lateral wave forces at the dock, its sway motion is often the main oscillation mode. The dynamic characteristics of the system under this mode can be well approximated by a mass-spring-damped system. In engineering practice, this can reduce model complexity and computational load while ensuring that key dynamic characteristics are captured, and meet the requirements of real-time identification. It receives cable tension data, ship displacement and velocity data, and time-domain sequence estimates of external excitation forces reconstructed based on the dominant excitation frequency from the environment and state sensing unit. To achieve this function, an online parameter identification algorithm is adopted. This algorithm can continuously update the model parameters based on real-time input and output data during system operation, thereby ensuring that the model can accurately reflect the current working state of the system.

[0039] To apply the online parameter identification algorithm, the following dynamic equations for the second-order system in the discrete-time domain are established:

[0040] ;

[0041] in, and Let k be the ship's displacement and velocity at time k, respectively. As an external incentive, For the overall equivalent mass of the system, Given the sampling period, the equation is rearranged into a linear regression form. :

[0042] ;

[0043] Wherein, parameter vector That is, the equivalent damping and equivalent stiffness to be identified;

[0044] In this embodiment, Recursive Least Squares (RLS) is specifically employed. This algorithm is used to analyze the input vector acquired in real-time. and output data For parameter vectors Through iterative updates, the unit can estimate the current equivalent stiffness of the ship's mooring system in real time during each control cycle. With equivalent damping The equivalent stiffness The equivalent damping is the overall resistance of the entire mooring system to displacement caused by external forces at time k, which determines the system's natural frequency and originates from the output of the online identification algorithm; It is the system's ability to consume oscillation energy at time k, and its influence on the decay rate of oscillation comes from the output of the online identification algorithm.

[0045] The resonance risk assessment unit functions to establish a precise quantitative mapping from system state to safety risk, transforming resonance risk into a calculable and comparable mathematical metric, thereby providing a clear triggering basis for control decisions. This unit is based on the equivalent stiffness output by the system dynamic characteristic identification unit. And combined with a preset total equivalent mass of the system The natural frequency of the current system is calculated. The total equivalent mass of the system , which is the sum of the ship's mass and the hydrodynamic added mass, represents the system's inertia in the dynamic model, and its value is obtained through... The calculation shows that, among which The ship's own mass is obtained based on the ship's real-time load data. Adding mass to the hydrodynamic system can be done by consulting ship hydrodynamic performance databases or using empirical formulas based on the ship's geometry, such as estimation methods based on beam and draft, and determining the current system's natural frequency. The calculation follows the standard definition of a second-order oscillatory system;

[0046] To further clarify, the core function of this unit is to combine the calculated natural frequency of the current system. With the dominant excitation frequency from the environment and state sensing unit The resonance risk index is calculated using a specific mathematical model. The resonance risk index , is a dimensionless index constructed to achieve active avoidance of targets. It comprehensively evaluates the proximity of the excitation frequency to the natural frequency and the intensity of the excitation energy, thereby accurately measuring the instantaneous danger level of resonance. Its source is the calculation output of this unit.

[0047] The variable parameter active control unit functions to dynamically adjust the control mode based on the quantitative results of the resonance risk assessment unit, intelligently and smoothly switching between the two objectives of high-precision positioning and high-safety avoidance, and ultimately generating executable physical commands. This unit calculates the resonance risk index. With a preset risk activation threshold Real-time comparison is performed on the risk activation threshold. As an engineering boundary used to distinguish between safe and dangerous states, its function is to serve as a criterion for triggering active avoidance control logic. Its value is pre-calibrated based on the safety margin of key indicators such as cable tension through offline simulation or safety analysis.

[0048] When judging Less than When this occurs, it indicates that the system is in a safe operating zone, at which point the element will have the target equivalent stiffness. Set as preset high-precision mode stiffness The target is equivalent to damping The system's inherent natural damping is set to be obtained in real time by the system dynamic characteristic identification unit. Based on these two target parameters, the unit calculates the cooperative control command aimed at accurately maintaining the ship's attitude through the same inverse dynamics model as the active avoidance mode. Its purpose is to keep the ship's position accurately at the target berth. This is achieved by driving the cable winch to operate in a high-stiffness mode to compensate for conventional environmental disturbances.

[0049] And when judging Not less than Upon this, the system immediately enters active avoidance mode. At this time, the core task of this unit is to generate the target equivalent stiffness that can guide the system out of the resonance region. Equivalent damping to the target These two target parameters are dynamically calculated based on the overshoot of the risk index. Based on the physical state of these two macroscopic system targets, the unit further calculates the specific coordinated control instructions assigned to each cable winch through the built-in inverse dynamics model. These instructions contain precise requirements for the winding and unwinding speed and tension of each winch, thereby realizing the reconstruction of the dynamic characteristics of the entire system at the physical level.

[0050] The system provided in this embodiment, through the coordinated operation of the aforementioned units, achieves proactive prediction and avoidance of resonance risks in the mooring system. Compared to traditional passive control methods based on error feedback, which may exacerbate oscillations due to response delays under specific operating conditions, this invention can proactively adjust the system's own physical stiffness and damping characteristics before resonance occurs, thereby adjusting the system's natural frequency to a safe range far from the external excitation frequency, thus preventing resonance from occurring at its source. This improves the safety of ship berthing operations, and at the same time, through intelligent switching of control modes, it takes into account the high-precision berthing requirements under non-hazardous conditions, solving the technical balance problem between high berthing accuracy and high cable safety. Example 2:

[0051] The environment and state perception unit obtains the wave energy spectrum by performing a fast Fourier transform on the wave height time series data, and extracts the angular frequency corresponding to the peak value from the wave energy spectrum as the dominant excitation frequency.

[0052] This embodiment further defines the technical solution described in Embodiment 1. In particular, it provides a detailed description of the method by which the environment and state sensing unit processes wave height time series data to generate the dominant excitation frequency.

[0053] Within this unit, to accurately identify the frequency components with the most concentrated energy from wave fluctuations, this embodiment employs the Fast Fourier Transform (FFT) algorithm. The Fast Fourier Transform is a digital signal processing technique that converts time-domain signals to the frequency domain for analysis. Its function is to efficiently calculate the distribution of wave energy at different frequencies. Specifically, this unit applies FFT to the acquired wave height time series data to obtain the wave energy spectrum. The wave energy spectrum is a function describing the change of wave energy density with angular frequency, which intuitively reveals the spectral structure of the external excitation energy. This unit performs peak search within the generated wave energy spectrum, extracting the angular frequency corresponding to the maximum value of the energy spectral density function, and uses this as the dominant excitation frequency. The output is used by subsequent units;

[0054] By employing the Fast Fourier Transform algorithm, this embodiment can quickly and accurately identify the dominant excitation frequency posing the greatest threat to the system from complex wave data. This method provides comprehensive frequency domain information, not only locating the dominant frequency but also quantifying its energy intensity, providing a data foundation for the accuracy of subsequent risk assessment, thereby improving the real-time performance and accuracy of the entire system's perception of environmental threats. Example 3:

[0055] The resonance risk assessment unit calculates the resonance risk index by using a preset Gaussian function model and inputting the frequency difference between the current system's natural frequency and the dominant excitation frequency.

[0056] This embodiment is a further optimization of the technical solution described in Embodiment 1, and specifically elaborates on the mathematical model for calculating the resonance risk index by the resonance risk assessment unit;

[0057] In this unit, to scientifically quantify resonance risk, this embodiment uses a pre-defined Gaussian function model to calculate the resonance risk index. The core of this model is to use the current system's inherent frequency. With dominant incentive frequency frequency difference As a key input, its specific calculation formula is as follows:

[0058] ;

[0059] in, The resonance risk index is a dimensionless pure number, derived from the calculation results of this formula.

[0060] The dominant frequency energy reflects the excitation intensity. After normalization, it is used as a dimensionless weighting factor, which is derived from the analysis results of the wave energy spectrum by the environment and state sensing unit.

[0061] The dominant wave frequency, measured in rad / s, originates from the output of the environment and state sensing unit.

[0062] The current system's natural frequency, measured in rad / s, is derived from the stiffness identified by this unit. The calculation results;

[0063] The frequency sensitivity factor, measured in rad / s, defines the sensitive bandwidth for risk assessment. It is derived from an offline calibration dataset and determined through numerical fitting. To clarify the determination process, a set of differences between the excitation frequency and the system's natural frequency at different excitation frequencies is obtained through simulation or model experiments. Below, the severity index of the system response By using regression analysis methods such as least squares, this set of data points By performing a fitting process, the optimal value can be determined. value;

[0064] A Gaussian function model is used to quantify resonance risk. This model not only considers the proximity of frequencies but also incorporates the excitation energy. As a weight, and using the square of the frequency difference to characterize the nonlinear effect of frequency detuning, this makes This approach accurately reflects the physical relationship between the degree of resonance risk and the excitation energy, and shows a nonlinear negative correlation with the degree of frequency detuning. Compared to simple threshold judgment, this method improves the accuracy and robustness of risk assessment, and can provide more refined guidance for subsequent control decisions. Example 4:

[0065] The variable parameter active control unit calculates the target equivalent stiffness by using a preset S-shaped function and inputting the ratio of the resonance risk index to the risk activation threshold, between a preset high-precision mode stiffness and a preset safety avoidance mode stiffness.

[0066] The variable parameter active control unit calculates the target equivalent damping by using a preset function and inputting the ratio of the resonance risk index to the risk activation threshold, between the inherent natural damping of the system identified by the system dynamic characteristic identification unit and the preset maximum active damping of the system.

[0067] This embodiment is a detailed design of the core control law of the variable parameter active control unit in the technical solution described in Embodiment 1. It clarifies how the system generates the target equivalent stiffness and the target equivalent damping when the resonance risk index is not less than the risk activation threshold. These two control laws are logically related and work together to achieve the dual goals of reducing stiffness and adjusting frequency and increasing resistance and dissipating energy.

[0068] For target equivalent stiffness In this embodiment, the generation is achieved through a preset S-shaped function. This function can smoothly and non-linearly transition between two preset stiffness boundaries according to the degree of risk. Its input is the resonance risk index. With risk activation threshold The ratio is calculated as follows:

[0069] ;

[0070] in, Target equivalent stiffness, in N / m, is the output of this formula;

[0071] High-precision mode stiffness, measured in N / m, defines the upper limit of stiffness that the system should maintain in safe mode to ensure berth accuracy. It is derived from the estimation of the maximum allowable displacement required for dock operations and the normal environmental disturbance force.

[0072] Safety avoidance mode stiffness, in N / m, defines the lower limit of the stiffness that the system can tolerate to avoid resonance. It is derived from the safety boundary calculated based on the cable safety working load (SWL) and the worst resonance displacement.

[0073] : Stiffness conversion rate factor, a dimensionless adjustable parameter, controls the speed of the transition from high stiffness to low stiffness. It is derived from the calibration based on the dynamic response capability of the actuator winch.

[0074] For target equivalent damping The generation of this parameter is achieved in this embodiment through a preset function that is the opposite of the stiffness adjustment logic. Its input is also the ratio of the resonance risk index to the risk activation threshold. This design embodies the control principle that the higher the risk, the lower the stiffness, but the higher the required damping. The specific calculation method is as follows:

[0075]

[0076] in, Target equivalent damping, in N·s / m, is the calculation output of this formula;

[0077] The maximum active damping of the system, measured in N·s / m, defines the upper limit of the energy dissipation capacity that the system can provide through active control. It is determined based on the capabilities of the actuator and system stability constraints.

[0078] The inherent natural damping of the system, measured in N·s / m, serves as the lower limit of the damping adjustment reference. It is obtained in real time by the system dynamic characteristic identification unit during the identification process.

[0079] Damping conversion rate factor is a dimensionless adjustable parameter whose function is related to... Similarly, it is used to adjust the switching rate of damping;

[0080] By adjusting stiffness using an S-shaped function, a smooth and gradual transition from high-precision mode to safe mode is achieved, avoiding system shocks that may be caused by sudden changes in stiffness. Furthermore, this embodiment integrates stiffness control and damping control in a coordinated manner. While reducing stiffness to avoid resonance frequencies, damping is simultaneously increased to dissipate wave energy. This two-pronged strategy, compared to adjusting either parameter alone, can suppress oscillations more quickly and effectively, enhancing the robustness and effectiveness of the control system. Example 5:

[0081] The process by which the variable parameter active control unit calculates the cooperative control command is as follows:

[0082] Based on the target equivalent stiffness, the target tension command of each cable winch is calculated by the inverse dynamics model.

[0083] Based on the target equivalent damping, the speed control commands for each cable winch are calculated using the inverse dynamics model.

[0084] The coordinated control command is generated by combining the target tension command and the speed control command.

[0085] This embodiment is a detailed description of the final execution stage of the technical solution described in Embodiment 1. It describes in detail how the variable parameter active control unit converts the target physical state into specific and executable coordinated control commands for each cable winch.

[0086] The core of this process relies on an inverse dynamics model, which establishes the system-level target dynamic characteristics ( ) and execute commands with each independent cable winch, target tension Speed ​​command The mathematical relationship between them, the function of the inverse dynamic model is to solve in reverse the inputs that need to be applied to each actuator, which are the tension and speed commands of the winch, based on the expected system-level outputs, here target stiffness and target damping;

[0087] Based on target equivalent stiffness Generate target tension command: The total equivalent stiffness of the system in a certain degree of freedom (such as the sway direction) can be expressed as all Sum of contributions from each cable: ,in It is the first The tension of the cable, It is its length. It is the tangential stiffness of the cable itself, which is related to tension. This is the angle between the cable and the direction of that degree of freedom. The inverse dynamics model is based on this relationship, adjusting the target tension of each cable... This is done by changing its tangential stiffness, thereby making the total stiffness of the system approach the target value. The solution process is an optimization problem, which aims to meet the overall stiffness requirements while ensuring that the tension of each cable is within a safe range.

[0088] Based on target equivalent damping The system generates speed control commands: Active damping is achieved by the winch generating a control force opposite to the direction of the ship's velocity. The total equivalent damping of the system can be expressed as: ,in It is the first The active damping coefficient provided by the winch-cable system. This damping force is achieved by controlling the winch's winding and unwinding speed, i.e. This requires a winch at a speed Perform compensating motion. The inverse dynamics model is based on the target equivalent damping. and ship real-time speed Calculate the damping coefficient required for each winch. And ultimately translated into specific speed control commands. ;

[0089] This unit combines the generated target tension command with the speed control command to generate the final coordinated control command, which is then sent to multiple automatic cable winches on the dock for execution.

[0090] This embodiment solves the problem of allocating instructions from macroscopic system objectives to microscopic actuators by introducing an inverse dynamics model. It transforms a multivariable system control problem into direct and explicit control of multiple independent actuators, ensuring that upper-level control strategies such as variable stiffness and variable damping can be accurately and collaboratively reproduced by winches in the physical world. It is a key link connecting control algorithms and engineering practice, improving control accuracy and response speed.

[0091] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A ship dock berthing vibration suppression control system, characterized in that, include: The environment and state sensing unit is used to collect wave height time series data, cable tension data, ship displacement data, and ship speed data; The environment and state perception unit is also used to process the wave height time series data to generate the dominant excitation frequency; The system dynamic characteristic identification unit is used to estimate the current equivalent stiffness and equivalent damping of the ship mooring system in real time based on the cable tension data, the ship displacement data, the ship speed data and the dominant excitation frequency through an online parameter identification algorithm. The resonance risk assessment unit is used to calculate the current system natural frequency based on the equivalent stiffness and the preset total equivalent mass of the system; the resonance risk assessment unit is also used to calculate the resonance risk index by combining the current system natural frequency and the dominant excitation frequency; A variable parameter active control unit is used to compare the resonance risk index with a preset risk activation threshold; When the resonance risk index is not less than the risk activation threshold, the variable parameter active control unit generates the target equivalent stiffness and the target equivalent damping, and calculates the cooperative control command based on the target equivalent stiffness and the target equivalent damping. When the resonance risk index is less than the risk activation threshold, the variable parameter active control unit generates a high-precision pose maintenance command.

2. The ship dock berthing oscillation suppression control system according to claim 1, characterized in that, The environment and state perception unit obtains the wave energy spectrum by performing a fast Fourier transform on the wave height time series data, and extracts the angular frequency corresponding to the peak value from the wave energy spectrum as the dominant excitation frequency.

3. The ship dock berthing oscillation suppression control system according to claim 1, characterized in that, The resonance risk assessment unit calculates the resonance risk index by using a preset Gaussian function model and inputting the frequency difference between the current system's natural frequency and the dominant excitation frequency.

4. The ship dock berthing oscillation suppression control system according to claim 1, characterized in that, The variable parameter active control unit calculates the target equivalent stiffness by using a preset S-shaped function and inputting the ratio of the resonance risk index to the risk activation threshold, between a preset high-precision mode stiffness and a preset safety avoidance mode stiffness.

5. The ship dock berthing oscillation suppression control system according to claim 1, characterized in that, The variable parameter active control unit calculates the target equivalent damping by using a preset function and inputting the ratio of the resonance risk index to the risk activation threshold, between the inherent natural damping of the system identified by the system dynamic characteristic identification unit and the preset maximum active damping of the system.

6. The ship dock berthing oscillation suppression control system according to claim 1, characterized in that, The process by which the variable parameter active control unit calculates the cooperative control command is as follows: Based on the target equivalent stiffness, the target tension command of each cable winch is calculated by the inverse dynamics model. Based on the target equivalent damping, the speed control commands for each cable winch are calculated using the inverse dynamics model. The coordinated control command is generated by combining the target tension command and the speed control command.

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