A multimodal adaptive switching method for container and bulk mixed use cranes

Abstract

The application relates to the technical field of intelligent control of port cranes, and particularly discloses a multimode adaptive switching method for a container and bulk cargo mixed use crane, which comprises the following steps: after a physical replacement of a tool is completed, a test excitation signal with a limited amplitude is generated and applied to an actuator; the mechanism displacement caused by the signal is smaller than the current real physical gap value of a tool connecting device, so that the system response is excited under the condition of no impact; actual response data are collected and actual dynamic response characteristics are obtained; meanwhile, an ideal model is constructed according to pre-stored static parameters of a new tool to obtain theoretical response characteristics; based on the effective deviation index between the actual dynamic response characteristics and the theoretical response characteristics, the process of dynamically adjusting control parameters from a first control parameter set corresponding to a current mode to a second control parameter set corresponding to a target mode is adjusted, and adaptive and non-disturbance switching of the control mode is completed. The application can realize smooth, safe and efficient transition of the control parameters after the tool is replaced, and supports online identification and performance self-optimization after the switching.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology for port cranes, and in particular to a multimodal adaptive switching method for a crane used for both container and bulk cargo transport. Background Technology

[0002] As port operations evolve towards multi-cargo and high-efficiency operations, container and bulk cargo mixed-use cranes are becoming increasingly common. These cranes utilize quick-change devices to rapidly switch between different attachments, such as container spreaders or bulk cargo grabs, on the same machine to adapt to varying operational tasks. However, the physical characteristics of different attachments differ significantly, and their corresponding control parameters must be adjusted accordingly; otherwise, it will lead to decreased positioning accuracy, failure of sway suppression, or even impact loads.

[0003] In existing technologies, engineering practice commonly employs a switching strategy that combines pre-stored parameter sets with fixed-duration transitions. This involves gradually transitioning the controller parameters from the current mode's preset parameter set to the target mode's nominal parameter set at a predetermined fixed rate or time after detecting attachment replacement. This approach has inherent limitations: First, a fixed transition time cannot balance safety and efficiency. If the transition is too rapid, the parameter step effect may trigger mechanical vibrations or even damage the quick-change structure; if the transition is too slow, the equipment remains in a suboptimal control state for an extended period, reducing operational efficiency. Second, the pre-stored parameters are based on the attachment's factory-specified condition. However, in actual use, the attachment's actual physical characteristics may deviate from the nominal values ​​due to factors such as adhered materials, structural wear, and deformation. Directly switching to the nominal parameter set in this case may lead to control instability or performance degradation. Third, existing solutions lack the means to perceive the actual connection gaps of the attachments, system damping, and other dynamic characteristics. They cannot assess the true safety status of the current system before switching, nor do they possess the ability to adaptively adjust the transition process based on the degree of deviation.

[0004] Therefore, there is an urgent need for a multimodal adaptive switching method for cranes that can be used for both container and bulk cargo transport to solve the above problems. Summary of the Invention

[0005] The purpose of this invention is to provide a multimodal adaptive switching method for a crane used for both container and bulk cargo transport, comprising the following steps: Receive the signal indicating that the physical replacement of the attachment is complete; Based on the attachment physical replacement completion signal, a amplitude-limited test excitation signal is generated and applied to an actuator of the crane. The amplitude of the amplitude-limited test excitation signal is limited such that the displacement of the mechanism caused by the signal is less than the current actual physical clearance value of the attachment connection device, so as to excite the dynamic response of the controlled system under no impact load conditions. During the application of the amplitude-limited test excitation signal, the actual response data of the actuator is collected, and the actual dynamic response characteristics are obtained based on the actual response data; The pre-stored static parameters of the new attachment are obtained based on the attachment physical replacement completion signal, and an ideal dynamic model is constructed based on the pre-stored static parameters. Then, the theoretical dynamic response characteristics are obtained based on the amplitude-limited test excitation signal and the ideal dynamic model. An effective deviation index is obtained based on the actual dynamic response characteristics and the theoretical dynamic response characteristics. The effective deviation index is used to characterize the degree of deviation between the current real dynamic characteristics of the controlled system and the ideal dynamic model. Based on the effective deviation index, the process of transitioning control parameters from the first set of control parameters corresponding to the current mode to the second set of control parameters corresponding to the target mode is dynamically adjusted to complete the adaptive and disturbance-free switching of control modes.

[0006] Furthermore, the present invention also discloses a multimodal adaptive switching system for a crane used for both container and bulk cargo transport, comprising: The first acquisition module is used to acquire the attachment physical replacement completion signal; A generation module is used to generate a test excitation signal with a limited amplitude based on the physical replacement completion signal of the attachment, and apply the test excitation signal with a limited amplitude to an actuator of the crane, wherein the amplitude of the test excitation signal with a limited amplitude is limited such that the displacement of the mechanism caused by the signal is less than the current actual physical clearance value of the attachment connection device, so as to excite the dynamic response of the controlled system under no impact load conditions; The acquisition module is used to acquire the actual response data of the actuator during the application of the amplitude-limited test excitation signal, and to obtain the actual dynamic response characteristics based on the actual response data; The processing module is used to obtain the pre-stored static parameters of the new attachment based on the attachment physical replacement completion signal, construct an ideal dynamic model based on the pre-stored static parameters, and then obtain the theoretical dynamic response characteristics based on the amplitude-limited test excitation signal and the ideal dynamic model. The second acquisition module is used to acquire an effective deviation index based on the actual dynamic response characteristics and the theoretical dynamic response characteristics. The effective deviation index is used to characterize the degree of deviation between the current real dynamic characteristics of the controlled system and the ideal dynamic model. The control module is used to dynamically adjust the transition process of the control parameters from the first set of control parameters corresponding to the current mode to the second set of control parameters corresponding to the target mode according to the effective deviation index, so as to complete the adaptive and disturbance-free switching of the control mode.

[0007] The beneficial effects of this application are as follows: Firstly, this invention calibrates the current actual physical gap of the attachment connection device online and uses this as a constraint to generate a test excitation signal with limited amplitude. This ensures that the displacement of the mechanism is always controlled within the gap range during the detection process, avoiding rigid collision between the pin and the hole wall. The system response data is obtained under zero impact load conditions, fundamentally guaranteeing the inherent safety of the characteristic detection before switching.

[0008] Secondly, this invention dynamically generates a transition rate based on the effective deviation index between the actual response and the ideal model under test stimulation. The smaller the deviation, the faster the transition, and the larger the deviation, the slower the transition. This maximizes the reduction of switching time while ensuring safety, eliminating the risk of safety redundancy waste or insufficient time in the fixed-duration mode, and achieving an automatic balance between safety and efficiency.

[0009] Thirdly, in this invention, after the transition is completed, the equivalent total inertia is identified online by using a pre-set no-load motion sequence and the recursive least squares method. Then, the actual mass, center of gravity position and swing damping coefficient of the attachment are calculated. Based on the real physical model, the optimal control parameters are solved using a linear quadratic regulator, so that the control system can adapt to the actual state of the attachment in real time and maintain optimal control performance in the long term. Attached Figure Description

[0010] Figure 1 This is a schematic diagram of a method flow proposed in an embodiment of this application.

[0011] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0012] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0013] like Figure 1 As shown, this application provides a multimodal adaptive switching method for a crane used for both container and bulk cargo transport, comprising the following steps: Example 1 like Figure 1As shown, this invention provides a multimodal adaptive switching method for a container and bulk cargo mixed-use crane. This method is applied to container and bulk cargo mixed-use cranes, which typically include a hoisting actuator, a quick-change attachment device, a main controller, a torque detection unit, a displacement encoder, a weighing sensor, and a status detection unit. The quick-change attachment device enables the physical replacement and mechanical locking of different modal attachments such as container spreaders and bulk cargo grabs. The hoisting actuator, as the core actuator, consists of a drive motor and a frequency converter, and is used to output torque and drive the attachments to complete hoisting and lowering movements. The main controller is used to run the control algorithm, realizing parameter transition calculations and system identification logic. Various sensing units are used to collect real-time operating data such as torque, displacement, speed, and load, providing feedback for the control logic.

[0014] The method includes the following steps: S1. Obtain the signal that the physical replacement of the attachment is complete; In this embodiment, the attachment physical replacement completion signal is a pre-triggered signal to initiate the entire adaptive switching process. It indicates that the crane's attachments have completed physical replacement, mechanical locking, and electrical and hydraulic connections, and are in a safe no-load state. Only when this signal is valid will the subsequent micro-motion detection and parameter switching processes be triggered, thereby avoiding safety risks caused by performing actions when the attachments are not reliably connected. In practical applications, the attachment physical replacement completion signal is generated by the main controller through comprehensive judgment of multiple status feedback signals.

[0015] The specific signal acquisition logic is as follows: S11. Obtain the mechanical locking limit signal of the attachment quick-change device; S12. Obtain the electrical connector connection feedback signal and the hydraulic connector connection feedback signal between the attachment and the frame; S13. Obtain the no-load status signal detected by the crane weighing sensor. The no-load status signal is determined by comparing the load value detected by the weighing sensor with a preset threshold of the attachment's self-weight. S14. When the mechanical locking limit signal, the electrical connector connection feedback signal, the hydraulic connector connection feedback signal, and the no-load status signal are all valid, a physical replacement completion signal for the attachment is generated.

[0016] In this embodiment, the mechanical locking limit signal is triggered by a limit switch or proximity switch installed on the quick-change device to confirm that the locking mechanism, such as the pin, has moved to the locking position and that the mechanical connection is reliable. The electrical connector connection feedback signal and the hydraulic connector connection feedback signal are used to confirm that the power supply, communication circuit, and hydraulic circuit of the attachment have been connected and that the drive and detection functions of the attachment can work normally. The no-load status signal is used to confirm that the attachment is not loaded with goods and is in a no-load state, ensuring the safety of load conditions during subsequent micro-motion detection and parameter switching processes.

[0017] By comprehensively judging the "AND" logic of multi-dimensional status signals, it is possible to avoid the process being triggered erroneously due to a single sensor failure or false signal, and ensure that the adaptive switching process is started only when the attachment has completed a reliable connection in all dimensions and is in a safe no-load condition, thus building a solid safety boundary from the process entry point.

[0018] S2. Based on the attachment physical replacement completion signal, generate a test excitation signal with limited amplitude and apply the test excitation signal with limited amplitude to an actuator of the crane, wherein the amplitude of the test excitation signal with limited amplitude is limited such that the displacement of the mechanism caused by the signal is less than the current actual physical clearance value of the attachment connection device, so as to excite the dynamic response of the controlled system under no impact load conditions. In this embodiment, the amplitude-limited test excitation signal is a drive control signal with strictly constrained amplitude. Its core function is to slightly drive the actuator to move without generating any mechanical impact load, thereby stimulating the dynamic response of the controlled system and providing excitation input for subsequent characteristic detection. The actuator is specifically the main hoisting actuator of a crane, which can respond to the control signal by outputting corresponding speed and torque.

[0019] The current actual physical clearance value of the attachment connection device is the inherent mechanical clearance of the attachment quick-change structure, specifically the fit clearance between the connecting pin and the upper frame connecting hole. This clearance is an essential structural feature of the quick-change device, designed to accommodate manufacturing tolerances, installation deviations, and thermal expansion and contraction during operation. This step, by constraining the amplitude of the test excitation, limits the amount of mechanical displacement caused by the excitation to within the range of this physical clearance. This ensures that the pin will not rigidly collide with the hole wall during the test, and the load-bearing structure will not bear impact loads. From a physical mechanism perspective, this guarantees zero impact risk during the detection process and achieves safe dynamic characteristic detection.

[0020] Furthermore, the specific steps for generating the amplitude-limited test excitation signal are as follows: S21. Before generating the amplitude-limited test excitation signal, according to the attachment physical replacement completion signal, control the actuator to perform a pre-action, the pre-action being a low-speed unidirectional drive; S22. During the execution of the pre-action, the torque feedback value and displacement feedback value of the actuator are collected in real time; S23. When the torque feedback value is detected to change non-zero for the first time, the corresponding displacement feedback value is recorded as the contact start displacement, and monitoring continues until the torque feedback value reaches the preset slope threshold. The displacement at this time is recorded as the contact termination displacement. S24. Obtain the current actual physical gap value of the attachment connection device based on the difference between the contact start displacement and the contact end displacement; S25. Based on the current actual physical gap value, determine the amplitude of the amplitude-limited test excitation signal according to a preset safety ratio, so that the displacement of the mechanism is limited to the preset safety ratio of the current actual physical gap value.

[0021] In this embodiment, the pre-action is a very low-speed unidirectional lifting drive, with a drive speed far lower than the normal operating speed. This is used to smoothly eliminate the gap and detect the gap boundary. The first non-zero change in the torque feedback value indicates that the pin begins to contact the hole wall, and the gap begins to be compressed. The preset slope threshold is the inflection point threshold of the torque rise rate. When the torque rise rate reaches this threshold, it means that the gap has been completely eliminated, and the pin is fully in contact with the hole wall. The difference between the contact start displacement and the contact end displacement is the actual physical gap value of the attachment connection device under the current wear state, rather than the factory design value.

[0022] The preset safety ratio is a constant less than 1, typically ranging from 0.5 to 0.8, used to ensure that the displacement caused by the test excitation always has a safety margin and will not touch the gap boundary. By calibrating the current actual physical gap value online, it can adapt to gap changes caused by wear after long-term use of the attachment. This avoids the problems of insufficient excitation amplitude and low response signal-to-noise ratio when the gap becomes larger, and also avoids the problems of excessive excitation and mechanical impact when the gap becomes smaller. It achieves adaptive safety configuration of the test excitation amplitude, ensuring the safety and effectiveness of the detection process under different wear conditions.

[0023] In this invention, the amplitude-limited test excitation signal is specifically implemented as a single-cycle sinusoidal velocity signal. This single-cycle sinusoidal velocity signal is superimposed on the speed control loop of the crane's main hoisting mechanism as an additional speed reference. The rope extension and retraction amount generated by the amplitude and period of the single-cycle sinusoidal velocity signal are strictly designed to be less than the total gap between the connecting pin and the upper frame hole. This ensures that during the excitation process, the wire rope only experiences tension and relaxation changes within the total gap between the connecting pin and the upper frame hole, without transmitting impact loads to the load-bearing structure. The rope extension and retraction amount is determined based on the integral value of the single-cycle sinusoidal velocity signal over half a cycle, and the total gap between the connecting pin and the upper frame hole is obtained online based on a gap calibration action triggered by the completion signal of the attachment physical replacement.

[0024] This single-cycle sinusoidal velocity signal features a smooth waveform and no abrupt changes. Superimposing it as a velocity input to the speed control loop enables smooth velocity changes in the actuator output, avoiding sudden torque shocks. The signal consists of only a single cycle, with a short excitation duration, minimizing its impact on normal operating procedures. By constraining the rope extension and retraction through velocity integration, zero-impact detection is ensured from a physical mechanism perspective. The online gap calibration method is adaptable to equipment wear conditions, making it highly practical for engineering applications.

[0025] S3. During the application of the amplitude-limited test excitation signal, the actual response data of the actuator is collected, and the actual dynamic response characteristics are obtained based on the actual response data; In this embodiment, actual response data refers to various real-time physical quantities output by the actuator under the action of a test excitation signal with limited amplitude, including but not limited to real-time torque and current values, motor speed values, and wire rope displacement values. Actual dynamic response characteristics are a set of features extracted from actual response data that can characterize the dynamic characteristics of the controlled system, reflecting the dynamic behavior of the real system composed of the attachment and the hoisting mechanism.

[0026] In practical applications, actual response data is synchronously collected at a high sampling rate using existing sensors on the crane, such as encoders and torque detection units, ensuring accurate time synchronization between data points and providing a reliable raw data foundation for subsequent deviation calculations. By preprocessing and feature extraction of the collected actual response data, the actual dynamic response characteristics that reflect the true dynamic properties of the system can be obtained.

[0027] S4. Obtain the pre-stored static parameters of the new attachment based on the attachment physical replacement completion signal, construct an ideal dynamic model based on the pre-stored static parameters, and then obtain the theoretical dynamic response characteristics based on the amplitude-limited test excitation signal and the ideal dynamic model. In this embodiment, the pre-stored static parameters are physical parameters corresponding to the nominal factory conditions of various attachments, which are pre-stored in the controller's storage unit. These include, but are not limited to, the theoretical mass, theoretical moment of inertia, and theoretical damping coefficient of the attachments. The ideal dynamic model is a standardized dynamic calculation model built based on the pre-stored static parameters. It is used to simulate the output response of the attachment system to the excitation signal under the nominal condition and serves as a benchmark model for comparison. The theoretical dynamic response characteristics are the response characteristics that the nominal system should exhibit under the action of a test excitation signal with the same amplitude limitation, calculated through the ideal dynamic model. They serve as a reference benchmark for comparison with the actual response.

[0028] Once the main controller receives the signal that the physical replacement of the attachment is complete, it automatically identifies the type of attachment that has been replaced and retrieves the pre-stored static parameters of the corresponding attachment. Based on the principles of classical dynamics, it constructs the corresponding ideal dynamic model. Then, it uses the applied test excitation signal with the same amplitude limitation as the model input to calculate the corresponding theoretical output, i.e., the theoretical dynamic response characteristics, thereby establishing a comparison benchmark between the real system and the nominal system.

[0029] S5. Obtain an effective deviation index based on the actual dynamic response characteristics and the theoretical dynamic response characteristics. The effective deviation index is used to characterize the degree of deviation between the current real dynamic characteristics of the controlled system and the ideal dynamic model. In this embodiment, the effective deviation index is a dimensionless indicator that quantifies the degree of difference between the actual dynamic characteristics of the controlled system and the ideal dynamic model. A larger effective deviation index indicates a greater deviation between the actual physical characteristics of the current attachment and the factory-specified model, typically meaning that the attachment may have issues such as material adhesion, wear, or aging that alter its physical characteristics. The effective deviation index is the core basis for subsequent parameter transition adjustments and safety judgments. By calculating the matching degree between the actual and theoretical response characteristics, the degree of deviation of system characteristics is transformed into a quantifiable numerical indicator, achieving quantitative perception of the attachment's actual physical state and providing a decision-making basis for subsequent adaptive control.

[0030] The specific calculation steps for step S5 are as follows: S51. Collect the actual torque response sequence and the actual velocity response sequence of the actuator, and use the actual torque response sequence and the actual velocity response sequence together as the actual dynamic response characteristics; S52. Obtain the theoretical moment of inertia and theoretical damping coefficient of the new attachment based on the pre-stored static parameters, and construct an ideal dynamic response calculation model based on the theoretical moment of inertia and theoretical damping coefficient. This model is used to generate the corresponding velocity sequence based on the input torque sequence. In this embodiment, the ideal dynamic response calculation model adopts a second-order linear transfer function model, and the specific formula is as follows: ; In the formula: For ideal dynamic transfer functions, For velocity frequency domain signals, This is a torque current frequency domain signal. The torque constant of the motor is... The theoretical moment of inertia, This is the theoretical damping coefficient. It is a complex frequency domain operator.

[0031] S53. Input the torque input sequence corresponding to the applied amplitude-limited test excitation signal into the ideal dynamic response calculation model to calculate the theoretical velocity response sequence, which is used as the theoretical dynamic response feature; S54. Calculate the dynamic time warping distance between the actual velocity response sequence and the theoretical velocity response sequence, and use the dynamic time warping distance as the effective deviation index.

[0032] In this embodiment, the actual torque response sequence and the actual velocity response sequence are discrete-time sequences synchronously acquired at a fixed sampling frequency within the test excitation application period. They correspond to the changes in the actuator's output torque and operating speed over time, respectively. Together, they constitute the actual response characteristics that can fully characterize the dynamic properties of the system. Dynamic time warping distance is an algorithm for measuring the similarity between two time series. It can tolerate the stretching and shifting of the sequences on the time axis. Compared to ordinary Euclidean distance, it is more suitable for describing the degree of deviation between dynamic responses with time lag, and can more accurately reflect the differences in dynamic characteristics between the real system and the ideal model.

[0033] The above technical solution significantly improves the calculation accuracy and robustness of the effective deviation index by acquiring torque-velocity dual-dimensional response features, constructing a standardized ideal model, and quantifying the deviation through dynamic time warping distance, providing a reliable quantitative basis for subsequent adaptive parameter adjustment.

[0034] S6. Based on the effective deviation index, dynamically adjust the transition process of the control parameters from the first control parameter set corresponding to the current mode to the second control parameter set corresponding to the target mode, so as to complete the adaptive and disturbance-free switching of the control mode. In this embodiment, the first control parameter set is the complete set of control parameters corresponding to the crane's current operating mode before the attachment replacement, such as the speed control parameters, anti-sway control parameters, and positioning control parameters corresponding to the original container spreader. The second control parameter set is the nominal control parameter set corresponding to the target mode, that is, the preset control parameters corresponding to the new attachment in its factory nominal state. Control parameter transition refers to using interpolation to gradually and smoothly change the operating control parameters from the first control parameter set to the target parameter set, avoiding mechanical shocks and control oscillations caused by abrupt parameter changes.

[0035] This step abandons the traditional fixed-duration transition mode and achieves adaptive dynamic adjustment based on the effective deviation index. The specific steps are as follows: S61. Input the effective deviation index into a preset transition rate generation function, and obtain the parameter transition rate according to the output of the transition rate generation function, wherein the transition rate generation function is configured such that: when the effective deviation index is smaller, the output parameter transition rate is larger, and when the effective deviation index is larger, the output parameter transition rate is smaller. In this embodiment, the transition rate generation function adopts an sigmoid nonlinear mapping function, and the specific formula is as follows: ; In the formula: For real-time parameter transition rate, For minimum transition rate, For the maximum transition rate, This is the curve steepness coefficient. The effective deviation index, This is the deviation threshold constant.

[0036] S62. Based on the parameter transition rate, interpolate the first control parameter set and the second control parameter set to make the control parameter gradually transition from the first control parameter set to the second control parameter set at the parameter transition rate.

[0037] In this embodiment, the transition rate generation function enables the transition rate to smoothly and adaptively change with the degree of deviation, eliminating the problem of abrupt rate changes. The interpolation process employs a smooth interpolation algorithm, updating the control parameters in each control cycle to completely eliminate control oscillations and mechanical shocks caused by parameter step jumps, achieving a dynamic balance between safety and operational efficiency.

[0038] At the same time, this step configures a safety fallback mechanism, the specific steps of which are as follows: S63. Compare the effective deviation index with a preset danger threshold; S64. When the effective deviation index exceeds the preset danger threshold, the parameters reflecting the initial response slope and attenuation characteristics of the system are extracted as the initial dynamic characteristic parameters of the controlled system based on the actual response data collected during the application of the amplitude-limited test excitation signal. S65. Based on the initial dynamic characteristic parameters, match the characteristic parameter range among the pre-stored multiple safety mode parameter packages, select the safety mode parameter package with the highest matching degree as the third parameter set, and set the third parameter set as the transition target parameter set to replace the second control parameter set; S66. Gradually transition the control parameters from the first set of control parameters to the third set of parameters.

[0039] In this embodiment, the preset danger threshold is the safety critical value of the effective deviation index. Exceeding the threshold indicates a severe mismatch between the actual characteristics of the attachment and the nominal model, and a risk of control instability in the nominal second control parameter set. By extracting the initial dynamic characteristic parameters to quickly match the optimal safety parameter package and automatically replacing the transition target, a dual safety protection mechanism is constructed. This effectively solves the parameter adaptation risk under extreme working conditions such as severe attachment wear and material adhesion, and improves the system's adaptability to working conditions.

[0040] The technical solution described in the above embodiments, through the synergistic effect of the above steps, can effectively resolve the contradiction between safety and efficiency in switching control parameters after changing multi-modal attachments on multi-purpose cranes. First, the multi-signal joint judgment triggering mechanism ensures safe start-up of the process, and the impact-free micro-motion detection enables risk-free perception of the true characteristics of the attachments; the quantified deviation index enables accurate identification of working conditions, the adaptive rate transition balances safety and efficiency, and the safety fallback mechanism eliminates the risks of extreme working conditions, ultimately achieving smooth, safe, efficient, and disturbance-free switching of control modes.

[0041] After the adaptive, disturbance-free switching of the control mode is completed, the system enters the performance optimization phase, achieving an upgrade from safe and available to optimal performance. The specific steps are as follows: S7. Obtain the adaptive transition completion signal; S8. Based on the adaptive transition completion signal, control the crane to automatically execute a preset no-load motion sequence, wherein the no-load motion sequence includes at least one uniform acceleration motion and one uniform deceleration motion. S9. During the execution of the no-load motion sequence, the torque data and speed data of the actuator are collected; S10. Based on the torque data and the velocity data, the equivalent total inertia of the controlled system is identified online using the recursive least squares method. In this embodiment, the core objective function formula for equivalent total inertia identification is as follows: ; In the formula: The equivalent total inertia, For frictional torque, The torque constant of the motor is... for Torque current at any moment for Angular acceleration at time t.

[0042] S11. Obtain at least one set of real physical parameters of the new attachment based on the equivalent total inertia, and solve for a set of optimal control parameters based on the set of real physical parameters. S12. Load the optimal control parameters into the controller of the crane to replace the control parameters obtained after adaptive transition.

[0043] In this embodiment, the adaptive transition completion signal serves as a marker of stable system operation, and the no-load standard motion sequence provides sufficient and stable excitation input for system identification. The recursive least squares method iteratively optimizes the identification results, accurately acquires the system's core dynamic parameters, and ultimately upgrades control performance through optimal parameter replacement.

[0044] Furthermore, the detailed steps for identifying the true physical parameters and solving for the optimal parameters are as follows: S111. After identifying the equivalent total inertia, control the actuator to perform a small-amplitude uniform lifting action and collect data on the change of lifting torque with lifting height. S112. Based on the changed data and the identified equivalent total inertia, calculate the actual mass and center of gravity of the new attachment; S113. Control the actuator to stop moving, and use the residual swing of the load or an actively applied anti-sway pulse to collect the attenuation data of the swing angle. S114. Fit the logarithmic decay rate based on the decay data to identify the equivalent swing damping coefficient of the system. S115. The actual mass, the center of gravity position, and the equivalent swing damping coefficient are used as the real physical parameters, and a state space model of the controlled object is constructed based on the real physical parameters. The optimal control parameters are solved using a linear quadratic regulator.

[0045] In this embodiment, real physical parameters of inertia, mass, center of gravity, and damping are obtained sequentially through a step-by-step identification method, accurately replicating the real dynamic characteristics of the current attachment. A state-space model constructed based on these real parameters is combined with a linear quadratic regulator to solve for the optimal control gain, achieving an optimal balance between system speed, stability, and smoothness. This completely eliminates the limitations of traditional preset parameters, allowing the crane's control performance to adapt to the actual working conditions of the attachment in real time.

[0046] The above-mentioned end-to-end technical solution constructs a complete closed-loop control architecture that includes safe micro-motion detection, adaptive parameter transition, fallback safety protection, online parameter identification, and optimal performance self-tuning. It solves the industry pain points of traditional multi-modal switching technology, such as fixed parameters, fixed transition time, inability to adapt to equipment aging and wear, and the inability to balance safety and efficiency. It has significant advantages such as inherent safety, strong adaptability, high engineering feasibility, and self-optimization of performance.

[0047] Example 2 This invention also discloses a multimodal adaptive switching system for a crane used for both container and bulk cargo transport, comprising: The first acquisition module is used to acquire the attachment physical replacement completion signal; A generation module is used to generate a test excitation signal with a limited amplitude based on the physical replacement completion signal of the attachment, and apply the test excitation signal with a limited amplitude to an actuator of the crane, wherein the amplitude of the test excitation signal with a limited amplitude is limited such that the displacement of the mechanism caused by the signal is less than the current actual physical clearance value of the attachment connection device, so as to excite the dynamic response of the controlled system under no impact load conditions. The acquisition module is used to acquire the actual response data of the actuator during the application of the amplitude-limited test excitation signal, and to obtain the actual dynamic response characteristics based on the actual response data; The processing module is used to obtain the pre-stored static parameters of the new attachment based on the attachment physical replacement completion signal, construct an ideal dynamic model based on the pre-stored static parameters, and then obtain the theoretical dynamic response characteristics based on the amplitude-limited test excitation signal and the ideal dynamic model. The second acquisition module is used to acquire an effective deviation index based on the actual dynamic response characteristics and the theoretical dynamic response characteristics. The effective deviation index is used to characterize the degree of deviation between the current real dynamic characteristics of the controlled system and the ideal dynamic model. The control module is used to dynamically adjust the transition process of the control parameters from the first set of control parameters corresponding to the current mode to the second set of control parameters corresponding to the target mode according to the effective deviation index, so as to complete the adaptive and disturbance-free switching of the control mode.

[0048] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in this application and in the embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0049] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0050] The above description is merely a preferred embodiment of the present invention and does not limit the scope of this application. Any equivalent results or equivalent process transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the scope of protection of this application.

Claims

1. A multimodal adaptive switching method for a crane used for both container and bulk cargo transport, characterized in that, Includes the following steps: Receive the signal indicating that the physical replacement of the attachment is complete; Based on the attachment physical replacement completion signal, a amplitude-limited test excitation signal is generated and applied to an actuator of the crane. The amplitude of the amplitude-limited test excitation signal is limited such that the displacement of the mechanism caused by the signal is less than the current actual physical clearance value of the attachment connection device, so as to excite the dynamic response of the controlled system under no impact load conditions. During the application of the amplitude-limited test excitation signal, the actual response data of the actuator is collected, and the actual dynamic response characteristics are obtained based on the actual response data; The pre-stored static parameters of the new attachment are obtained based on the attachment physical replacement completion signal, and an ideal dynamic model is constructed based on the pre-stored static parameters. Then, the theoretical dynamic response characteristics are obtained based on the amplitude-limited test excitation signal and the ideal dynamic model. An effective deviation index is obtained based on the actual dynamic response characteristics and the theoretical dynamic response characteristics. The effective deviation index is used to characterize the degree of deviation between the current real dynamic characteristics of the controlled system and the ideal dynamic model. Based on the effective deviation index, the process of transitioning control parameters from the first set of control parameters corresponding to the current mode to the second set of control parameters corresponding to the target mode is dynamically adjusted to complete the adaptive and disturbance-free switching of control modes.

2. The multimodal adaptive switching method for a container and bulk cargo mixed-use crane according to claim 1, characterized in that, The generation of a value-constrained test excitation signal further includes: Before generating the amplitude-limited test excitation signal, the actuator is controlled to perform a pre-action based on the attachment physical replacement completion signal. The pre-action is a low-speed unidirectional drive. During the execution of the pre-action, the torque feedback value and displacement feedback value of the actuator are collected in real time. When the torque feedback value is detected to change non-zero for the first time, the corresponding displacement feedback value is recorded as the contact start displacement, and monitoring continues until the torque feedback value reaches the preset slope threshold. The displacement at this time is recorded as the contact termination displacement. The current actual physical gap value of the attachment connection device is obtained based on the difference between the contact start displacement and the contact end displacement. Based on the current actual physical gap value, the amplitude of the amplitude-limited test excitation signal is determined according to a preset safety ratio, so that the displacement of the mechanism is limited to the preset safety ratio of the current actual physical gap value.

3. The multimodal adaptive switching method for a container and bulk cargo mixed-use crane according to claim 1, characterized in that, The process of obtaining the effective deviation index based on the actual dynamic response characteristics and the theoretical dynamic response characteristics specifically includes: The actual torque response sequence and actual velocity response sequence of the actuator are collected, and the actual torque response sequence and actual velocity response sequence are used together as the actual dynamic response characteristics; The theoretical moment of inertia and theoretical damping coefficient of the new attachment are obtained based on the pre-stored static parameters, and an ideal dynamic response calculation model is constructed based on the theoretical moment of inertia parameters and the theoretical damping parameters. This model is used to generate the corresponding velocity sequence based on the input torque sequence. The torque input sequence corresponding to the applied amplitude-limited test excitation signal is input into the ideal dynamic response calculation model to calculate the theoretical velocity response sequence, which is used as the theoretical dynamic response feature. Calculate the dynamic time warping distance between the actual velocity response sequence and the theoretical velocity response sequence, and use this dynamic time warping distance as the effective deviation index.

4. The multimodal adaptive switching method for a container and bulk cargo mixed-use crane according to claim 1, characterized in that, The process of dynamically adjusting the control parameters from the first set of control parameters corresponding to the current mode to the second set of control parameters corresponding to the target mode based on the effective deviation index specifically includes: The effective deviation index is input to a preset transition rate generation function, and the parameter transition rate is obtained according to the output of the transition rate generation function. The transition rate generation function is configured such that: when the effective deviation index is smaller, the output parameter transition rate is larger; when the effective deviation index is larger, the output parameter transition rate is smaller. Based on the parameter transition rate, interpolation is performed on the first control parameter set and the second control parameter set so that the control parameter gradually transitions from the first control parameter set to the second control parameter set at the parameter transition rate.

5. The multimodal adaptive switching method for a container and bulk cargo mixed-use crane according to claim 1, characterized in that, The process of dynamically adjusting the control parameters from the first control parameter set corresponding to the current mode to the second control parameter set corresponding to the target mode based on the effective deviation index further includes: The effective deviation index is compared with a preset danger threshold. When the effective deviation index exceeds the preset danger threshold, parameters reflecting the initial response slope and decay characteristics of the system are extracted as the initial dynamic characteristic parameters of the controlled system based on the actual response data collected during the application of the amplitude-limited test excitation signal. Based on the initial dynamic characteristic parameters, the characteristic parameter range is matched among multiple pre-stored safety mode parameter packages. The safety mode parameter package with the highest matching degree is selected as the third parameter set, and the third parameter set is set as the transition target parameter set to replace the second control parameter set. The control parameters are then gradually transitioned from the first control parameter set to the third parameter set.

6. The multimodal adaptive switching method for a container and bulk cargo mixed-use crane according to claim 5, characterized in that, After the adaptive, disturbance-free switching of the control mode is completed, the following is also included: Obtain the adaptive transition completion signal; Based on the adaptive transition completion signal, the crane is controlled to automatically execute a preset no-load motion sequence, which includes at least one uniform acceleration motion and one uniform deceleration motion. During the execution of the no-load motion sequence, the torque and speed data of the actuator are collected; Based on the torque data and the velocity data, the equivalent total inertia of the controlled system is identified online using the recursive least squares method. At least one set of real physical parameters of the new attachment are obtained based on the equivalent total inertia, and a set of optimal control parameters are solved based on the set of real physical parameters. The optimal control parameters are loaded into the controller of the crane to replace the control parameters obtained after adaptive transition.

7. The multimodal adaptive switching method for a container and bulk cargo mixed-use crane according to claim 6, characterized in that, The step of obtaining at least a set of real physical parameters of the new attachment based on the equivalent total inertia, and solving for a set of optimal control parameters based on the set of real physical parameters, further includes: After identifying the equivalent total inertia, the actuator is controlled to perform a small-amplitude, uniform lifting action, and the lifting torque data as a function of lifting height is collected. Based on the change data and the identified equivalent total inertia, the actual mass and center of gravity of the new attachment are calculated. The actuator is controlled to stop moving, and the attenuation data of the swing angle is collected using the residual swing of the load or an actively applied anti-sway pulse; Based on the attenuation data, a logarithmic attenuation rate is fitted to identify the equivalent oscillation damping coefficient of the system. The actual mass, the center of gravity position, and the equivalent swing damping coefficient are used as the real physical parameters. Based on these real physical parameters, a state-space model of the controlled object is constructed, and the optimal control parameters are solved using a linear quadratic regulator.

8. The multimodal adaptive switching method for a container and bulk cargo mixed-use crane according to claim 1, characterized in that, The amplitude-limited test excitation signal is specifically implemented as follows: A single-cycle sinusoidal speed signal is superimposed on the speed control loop of the crane's main hoisting mechanism as an additional speed reference. The amplitude and period of the single-cycle sinusoidal velocity signal are configured such that the rope extension amount generated by the signal is less than the current actual physical gap value between the connecting pin and the upper frame hole, and the rope extension amount is determined based on the integral value of the single-cycle sinusoidal velocity signal over half a cycle. During the excitation process, the displacement of the load-bearing structure caused by the rope extension is limited within the current actual physical gap value, so that the tension change of the wire rope does not transmit impact load to the load-bearing structure. The current actual physical gap value is obtained online based on a gap calibration action triggered by the attachment physical replacement completion signal.

9. The multimodal adaptive switching method for a container and bulk cargo mixed-use crane according to claim 1, characterized in that, The acquisition of the attachment physical replacement completion signal specifically includes: Obtain the mechanical locking limit signal of the attachment quick-change device; Obtain electrical and hydraulic connector connection feedback signals between the attachment and the upper frame; The no-load status signal detected by the crane's weighing sensor is obtained. The no-load status signal is determined by comparing the load value detected by the weighing sensor with a preset threshold of the attachment's self-weight. When the mechanical locking limit signal, the electrical connector connection feedback signal, the hydraulic connector connection feedback signal, and the no-load status signal are all in a valid state, the attachment physical replacement completion signal is generated.

10. A multimodal adaptive switching system for a crane used for both container and bulk cargo transport, characterized in that, include: The first acquisition module is used to acquire the attachment physical replacement completion signal; A generation module is used to generate a test excitation signal with a limited amplitude based on the physical replacement completion signal of the attachment, and apply the test excitation signal with a limited amplitude to an actuator of the crane, wherein the amplitude of the test excitation signal with a limited amplitude is limited such that the displacement of the mechanism caused by the signal is less than the current actual physical clearance value of the attachment connection device, so as to excite the dynamic response of the controlled system under no impact load conditions. The acquisition module is used to acquire the actual response data of the actuator during the application of the amplitude-limited test excitation signal, and to obtain the actual dynamic response characteristics based on the actual response data; The processing module is used to obtain the pre-stored static parameters of the new attachment based on the attachment physical replacement completion signal, construct an ideal dynamic model based on the pre-stored static parameters, and then obtain the theoretical dynamic response characteristics based on the amplitude-limited test excitation signal and the ideal dynamic model. The second acquisition module is used to acquire an effective deviation index based on the actual dynamic response characteristics and the theoretical dynamic response characteristics. The effective deviation index is used to characterize the degree of deviation between the current real dynamic characteristics of the controlled system and the ideal dynamic model. The control module is used to dynamically adjust the transition process of the control parameters from the first set of control parameters corresponding to the current mode to the second set of control parameters corresponding to the target mode according to the effective deviation index, so as to complete the adaptive and disturbance-free switching of the control mode.

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