Attitude control method and device for four-rope lifting appliance, terminal and medium

Abstract

The invention belongs to the technical field of port hoisting equipment, and particularly relates to an attitude control method and device for a four-rope lifting appliance, a terminal and a medium. Constructing a dynamic model; acquiring control information in real time; and predicting the movement track of the lifting appliance in a future period of time, and when the distance between a prediction point in the prediction track and the target container landing point is smaller than a precision threshold value, controlling the lifting appliance to descend to complete container landing. According to the method, a predictive control strategy is adopted, collected real-time position, posture, tension, wind speed and other information are substituted into a dynamic model, and motion trail numerical integration prediction in a period of time in the future is carried out through a differential equation set. The whole control process does not depend on a high-precision image recognition system, the dependence on a visual sensor and a complex image processing algorithm is reduced, and the universality and engineering adaptability of the system are improved.

Description

Technical Field

[0001] This invention belongs to the technical field of port lifting equipment, specifically relating to a posture control method, device, terminal, and medium for a four-rope sling. Background Technology

[0002] Among the many types of port equipment, heavy-duty equipment such as rail-mounted gantry cranes and quay cranes have become core equipment for port container handling operations due to their powerful lifting capacity and adaptability to large-scale operations. Four-rope spreaders, with their excellent structural stability, are widely used in these heavy-duty port equipment. They ensure the safety and stability of container handling during loading and unloading, laying a solid foundation for the efficient operation of the port.

[0003] However, in actual automated operations, it is difficult to achieve completely uniform force on the four ropes, especially when encountering complex working conditions such as wind load interference. The wind force acting on the spreader and container will form an additional, constantly changing external force, which further disrupts the dynamic balance of the spreader system, which already has tension differences and sway characteristics. As a result, the container landing accuracy is difficult to meet the requirements of precise loading and unloading.

[0004] Currently, most existing methods in the industry attempt to solve these problems using real-time visual correction or manual control. While real-time visual correction systems can detect positional deviations of the spreader and container to some extent and make timely adjustments, it is largely a passive approach, only correcting current deviations and lacking the ability to predict and model future swing trends of the spreader. Manual control, on the other hand, is limited by factors such as labor costs, personnel fatigue, and reaction speed, making it difficult to achieve stable and efficient continuous intervention throughout the entire automated process. Summary of the Invention

[0005] This invention addresses the problems in the prior art by providing a method, device, terminal, and medium for attitude control of a four-rope spreader. It solves the problems of low landing accuracy caused by data delay and inability to predict position when using real-time visual correction for container landing. It also solves the problems of low landing accuracy caused by limited space or insufficient human experience when using manual observation and experience control for container landing.

[0006] The technical solution adopted in this invention is as follows: In a first aspect, this application provides a method for attitude control of a four-rope lifting rig, comprising the following steps: Step S1: Establish a spatial model, which includes a trolley model, a lifting device model, and a rope model; Step S2: Construct a dynamic model, which includes a rope dynamic model and a lifting device dynamic model. The lifting device dynamic model is a rigid body system with six degrees of freedom. Euler angles are used as parameters to describe the attitude of the lifting device dynamic model. Step S3: Acquire control information in real time. The control information includes the position and attitude information of the lifting device, the tension information of each rope, and environmental information. Step S4: Substitute the control information obtained in step S3 into the dynamic model to predict the motion trajectory of the spreader in the future. When there is a predicted point in the predicted trajectory whose distance between the predicted point and the target landing point is less than the accuracy threshold, control the spreader to descend and complete the landing.

[0007] Preferably, in step S2, the state variables in the spreader dynamics model include the position of the spreader's center of mass. Attitude angle linear velocity of the center of mass Attitude angular velocity and angular velocity vector The relationship between angular velocity and Euler angles satisfies the following transformation relationship:

[0008] Among them, matrix This is the nonlinear transformation matrix of the Euler angle rotation velocity.

[0009] Preferably, in step S2, the rope model is an inextensible model, wherein the geometric constraints between each rope connection point are satisfied:

[0010] in, and These represent the first [number] on the trolley and the lifting device, respectively. The spatial coordinates of each anchor point , This refers to the fixed length of the rope. The above equality constraints are introduced into the Lagrange system equations, and the generalized coordinates of the system are: The Lagrange equation is corrected to:

[0011] in, For Lagrange multipliers, corresponding to the th The magnitude of the constraint force on a rope represents the tension in that rope, and this tension is constant along a unit vector:

[0012] in, Let be the direction of the tension, and let be the first . The rope is anchored at the lifting point. Pointing to the car anchor point The unit vector.

[0013] Preferably, the magnitude of the tension is solved using the dynamic equilibrium equations and satisfies the overall translational equations:

[0014] Where M is the mass of the lifting device. Let be the acceleration vector of the center of mass of the spreader. External disturbance force; The external disturbance source is wind-borne interference, and its expression is:

[0015] in, The drag coefficient, Let A be the air density and A be the windward area of ​​the spreader and container. For the speed of the spreader, For wind speed, The direction of relative velocity.

[0016] Preferably, the rotational dynamics of the lifting device are based on Euler's rotational law, satisfying:

[0017] in, Let the inertia tensor of the spreading device be... For the first The position vector of the rope anchor point relative to the center of mass of the lifting device.

[0018] Preferably, in step S4, a prediction model is established, utilizing a system of differential equations within a time window. Numerical integration is performed to obtain the trajectory of the spreader's center of mass over a future time period. With attitude change curve The system of differential equations is as follows:

[0019] If within the predicted time window At a certain moment, memory The following triggering conditions must be met:

[0020] in, For the precision threshold, For the center of gravity of the spreading gear at all times The position vector, The target landing point location.

[0021] Preferably, the controller at time Issue descent control command, where The command includes the desired descent rate:

[0022] in, To control the descent speed, This is the advance compensation time for controller response lag. The vertical height of the target landing point. For the center of gravity of the spreading gear at all times vertical height The time required to trigger the descent maneuver in advance.

[0023] Secondly, this application provides an attitude control system for a four-rope lifting rig, comprising: The modeling module is used to establish the spatial and dynamic models of the four-rope lifting device. The spatial model includes a trolley model, a lifting device model, and a rope model. The dynamic model includes an inextensible rope model and a six-degree-of-freedom rigid body model of the lifting device described using Euler angles. The information acquisition module is used to acquire control information in real time. The control information includes: position information and attitude information of the lifting device, tension information of each rope, and environmental information. The position information and attitude information are acquired by a laser rangefinder, an inertial measurement unit, or a gyroscope. The tension information is acquired by a tension sensor. The environmental information includes wind speed data acquired by a wind speed sensor. The trajectory prediction module is used to substitute the control information into the dynamic model, perform numerical integration based on the translational equation and Euler rotational equation in the model, and calculate the center of mass trajectory and attitude change trajectory of the spreader in the future time window. The control judgment module is used to determine whether there is a moment in the predicted trajectory where the spatial distance between the corresponding centroid position and the target landing point is less than a preset accuracy threshold. If the threshold is met, a descent command is sent to the hoisting controller. The descent control module is used to calculate the descent speed based on the predicted trigger time and control the spreader to be lowered synchronously when it is predicted to reach the target point. The descent speed is determined by the current height, the target height, and the system response compensation time.

[0024] Thirdly, this application provides a terminal, including: Memory, used to store attitude control simulation programs; A processor is configured to implement the steps of the attitude control method for a four-rope sling as described in the first aspect when executing the attitude control system for the four-rope sling.

[0025] Fourthly, this application provides a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions from the storage medium, the computer executes an attitude control method for a four-rope sling as described in the first aspect.

[0026] As can be seen from the above technical solutions, this application has the following advantages: This invention provides a posture control method for a four-rope lifting device, which has significant technical effects and practical application value. The method establishes a spatial structure model including a trolley, lifting device, and ropes, and then constructs a dynamic model based on this model. This accurately reflects the coupled effects of various physical factors on the lifting device during actual operation, particularly the complex dynamic behavior caused by uneven rope tension and wind load disturbance. In the dynamic model, the lifting device is treated as a rigid body with six degrees of freedom, and its posture is described using Euler angles. By combining an inextensible rope model and the Lagrange multiplier method to model rope tension, the motion of the lifting device's center of mass and posture changes can be theoretically and accurately characterized.

[0027] Compared to existing passive correction control methods based on visual feedback, this invention employs a predictive control strategy. It utilizes real-time information such as position, attitude, tension, and wind speed, incorporating it into a dynamic model and using a system of differential equations to numerically predict the motion trajectory over a future period. The predicted trajectory is used to determine whether the spreader will reach the target landing point. If the accuracy requirements are met, the descent speed is calculated in advance, and a lowering control command is issued, ensuring that the spreader's descent is synchronized with the natural endpoint of its swing, thus significantly improving the success rate of automatic landing. The entire control process does not rely on a high-precision image recognition system, reducing dependence on visual sensors and complex image processing algorithms, and enhancing the system's versatility and engineering adaptability.

[0028] Furthermore, this invention also possesses excellent disturbance adaptability and system robustness. By explicitly incorporating wind speed disturbance into the model, the coupling relationship between wind load and hoist response is established, and the changing trend of external disturbances is fully considered in predictive control. Attached Figure Description

[0029] To more clearly illustrate the technical solution of this application, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 Here are some spatial model diagrams illustrating various embodiments; Figure 2 This is a flowchart illustrating a posture control method for a four-rope sling, as shown in some embodiments. Detailed Implementation

[0031] To make the purpose, features, and advantages of this application more apparent and understandable, specific embodiments and accompanying drawings will be used to clearly and completely describe the technical solution protected by this application. Obviously, the embodiments described below are only some embodiments of this application, and not all embodiments. Based on the embodiments in this patent, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this patent.

[0032] Among the many types of port equipment, heavy-duty equipment such as rail-mounted gantry cranes and quay cranes have become core equipment for port container handling operations due to their powerful lifting capacity and adaptability to large-scale operations. Four-rope spreaders, with their excellent structural stability, are widely used in these heavy-duty port equipment. They ensure the safety and stability of container handling during loading and unloading, laying a solid foundation for the efficient operation of the port.

[0033] However, in actual automated operations, it is difficult to achieve completely uniform force on the four ropes, especially when encountering complex working conditions such as wind load interference. The wind force acting on the spreader and container will form an additional, constantly changing external force, which further disrupts the dynamic balance of the spreader system, which already has tension differences and sway characteristics. As a result, the container landing accuracy is difficult to meet the requirements of precise loading and unloading.

[0034] Currently, most existing methods in the industry attempt to solve these problems using real-time visual correction or manual control. While real-time visual correction systems can detect positional deviations of the spreader and container to some extent and make timely adjustments, it is largely a passive approach, only correcting current deviations and lacking the ability to predict and model future swing trends of the spreader. Manual control, on the other hand, is limited by factors such as labor costs, personnel fatigue, and reaction speed, making it difficult to achieve stable and efficient continuous intervention throughout the entire automated process.

[0035] This invention addresses the problems in the prior art by providing a method, device, terminal, and medium for attitude control of a four-rope spreader. It solves the problems of low landing accuracy caused by data delay and inability to predict position when using real-time visual correction for container landing. It also solves the problems of low landing accuracy caused by limited space or insufficient human experience when using manual observation and experience control for container landing.

[0036] like Figure 1 and Figure 2As shown, in some embodiments, this application provides an attitude control method for a four-rope lifting rig, including the following steps: Step S1: Establish a spatial model, which includes a trolley model, a lifting device model, and a rope model; In step S1, a spatial model for modeling the control system is established. This spatial model comprises three parts: a trolley model, a lifting device model, and a rope model. The trolley model describes the trolley's one-dimensional or two-dimensional movement on the track, serving as the upper support platform for the entire system. Its position is the initial reference point of the upper anchor point of the rope. The lifting device model is the core controlled object of the system. During modeling, the lifting device is considered a rigid body with six degrees of freedom, possessing three-dimensional translation and rotational capabilities. Its center of mass changes over time, and it is allowed to change its attitude angle around its own center of mass. The rope model connects the trolley and the lifting device. Four ropes of fixed length connect the four corner points of the trolley and the lifting device, forming a spatial tension chain. The ends of each rope are fixed at specific points on the trolley and the lifting device. During modeling, the ropes are assumed to be inextensible flexible cables, and their mass and elasticity are not considered, constituting the geometric constraints of the system.

[0037] Step S2: Construct a dynamic model, which includes a rope dynamic model and a lifting device dynamic model. The lifting device dynamic model is a rigid body system with six degrees of freedom. Euler angles are used as parameters to describe the attitude of the lifting device dynamic model. In step S2, a complete system dynamics model is established based on the aforementioned spatial structure. The dynamics model mainly consists of a lifting device dynamics model and a rope constraint model. The lifting device dynamics model uses Euler angles for attitude description, defining the lifting device's center of mass position (x, y, z) and attitude angles (pitch angle θ, roll angle φ, yaw angle ψ) as state variables, while introducing their first derivatives to constitute the velocity states (linear velocity and angular velocity). Combining rigid body dynamics principles, the translational and rotational equations of the lifting device are established respectively. The translational equations are constructed based on Newton's second law, considering the tension, gravity, and external disturbance forces acting on the lifting device; the rotational equations are based on Euler's rotational law, establishing an attitude change model through the lifting device's inertia tensor and angular acceleration. The rope dynamics model adopts the inextensibility assumption, constructing distance-invariant constraint equations for each rope, introducing Lagrange multipliers to represent rope tension, and coupling the tension force and torque terms into the lifting device dynamics, thus forming a multi-rigid-body system dynamics model with strong constraints.

[0038] Step S3: Acquire control information in real time. The control information includes the position and attitude information of the lifting device, the tension information of each rope, and environmental information. In step S3, the system acquires control information in real time through various sensors. This control information includes the current position and attitude angle of the spreader, the tension of each rope, and environmental disturbance information. Specifically, position and attitude information can be acquired using laser rangefinders and inertial measurement units (IMUs), while rope tension information is collected by rope tension sensors mounted on the spreader. Environmental information mainly includes wind speed data, which can be measured by an anemometer installed on the crane platform or the spreader itself. All acquired information is synchronously uploaded to the control system via a data acquisition system to drive subsequent trajectory prediction calculations.

[0039] Step S4: Substitute the control information obtained in step S3 into the dynamic model to predict the motion trajectory of the spreader in the future. When there is a predicted point in the predicted trajectory whose distance between the predicted point and the target landing point is less than the accuracy threshold, control the spreader to descend and complete the landing.

[0040] In step S4, the control information obtained in step S3 is substituted into the system dynamics model established in step S2 to construct a prediction model and perform numerical integration to predict the motion trajectory of the spreader over a future period. The prediction model uses the current state of the spreader as initial conditions and obtains the sequence of changes in the spreader's center of mass position and attitude angle over a future period by integrating the acceleration equation and Euler rotation equation over a time window. The system controller judges the spatial distance between each predicted point in the predicted trajectory and the target landing point. When the spatial distance between any predicted point and the target point is less than a set accuracy threshold, it is considered that the spreader will automatically swing into the target area at that moment. Based on this, the controller calculates the descent speed and descent start time in advance and sends a descent control command to the hoisting device to achieve synchronous lowering of the spreader, thereby completing the automatic landing operation. Through this method, the spreader can effectively predict and control its future behavior under the influence of wind load interference and attitude sway, significantly improving operational accuracy and automation level.

[0041] In this embodiment, in step S2, the state variables in the spreader dynamics model include the position of the spreader's center of mass. Attitude angle linear velocity of the center of mass Attitude angular velocity and angular velocity vector The relationship between angular velocity and Euler angles satisfies the following transformation relationship:

[0042] Among them, matrix This is the nonlinear transformation matrix of the Euler angle rotation velocity.

[0043] In this embodiment, in step S2, the rope model is an inextensible model, wherein the geometric constraints between each rope connection point are satisfied:

[0044] in, and These represent the first [number] on the trolley and the lifting device, respectively. The spatial coordinates of each anchor point , This refers to the fixed length of the rope. The above equality constraints are introduced into the Lagrange system equations, and the generalized coordinates of the system are: The Lagrange equation is corrected to:

[0045] in, For Lagrange multipliers, corresponding to the th The magnitude of the constraint force on a rope represents the tension in that rope, and this tension is constant along a unit vector:

[0046] in, Let be the direction of the tension, and let be the first . The rope is anchored at the lifting point. Pointing to the car anchor point The unit vector.

[0047] By establishing a spatial structural model including the trolley, lifting device, and ropes, and constructing a dynamic model based on this model, the system accurately reflects the coupled effects of various physical factors on the lifting device during actual operation, particularly the complex dynamic behavior caused by uneven rope tension and wind load disturbance. In the dynamic model, the lifting device is treated as a rigid body with six degrees of freedom, and its attitude is described using Euler angles. By combining an inextensible rope model and the Lagrange multiplier method to model the rope tension, the motion of the lifting device's center of mass and attitude changes can be accurately characterized theoretically.

[0048] In this embodiment, the magnitude of the tension is solved using the dynamic equilibrium equations, and satisfies the overall translational equations:

[0049] Where M is the mass of the lifting device. Let be the acceleration vector of the center of mass of the spreader. External disturbance force; The external disturbance source is wind-borne interference, and its expression is:

[0050] in, The drag coefficient, Let A be the air density and A be the windward area of ​​the spreader and container. For the speed of the spreader, For wind speed, The direction of relative velocity.

[0051] In this embodiment, the rotational dynamics of the lifting device are based on Euler's rotational law, satisfying:

[0052] in, Let the inertia tensor of the spreading device be... For the first The position vector of the rope anchor point relative to the center of mass of the lifting device.

[0053] By explicitly introducing wind speed disturbance into the model, the coupling relationship between wind load and hoist response is established, and the changing trend of external disturbance is fully considered in predictive control.

[0054] In this embodiment, in step S4, a prediction model is established, and a system of differential equations is used within a time window. Numerical integration is performed to obtain the trajectory of the spreader's center of mass over a future time period. With attitude change curve The system of differential equations is as follows:

[0055] If within the predicted time window At a certain moment, memory The following triggering conditions must be met:

[0056] in, For the precision threshold, For the center of gravity of the spreading gear at all times The position vector, The target landing point location.

[0057] In this embodiment, the controller at time Issue descent control command, where The command includes the desired descent rate:

[0058] in, To control the descent speed, This is the advance compensation time for controller response lag. The vertical height of the target landing point. For the center of gravity of the spreading gear at all times vertical height The timing of the descent action is determined in advance. A predictive control strategy is employed, utilizing real-time information such as position, attitude, tension, and wind speed. This information is incorporated into a dynamic model, and the motion trajectory is predicted numerically over a future time period using a system of differential equations. The predicted trajectory is used to determine whether the spreader will reach the target landing point. If the accuracy requirements are met, the descent speed is calculated in advance, and a lowering control command is issued. This ensures that the spreader's descent is synchronized with the natural endpoint of its swing, significantly improving the success rate of automatic landing. The entire control process does not rely on a high-precision image recognition system, reducing dependence on visual sensors and complex image processing algorithms, and enhancing the system's versatility and engineering adaptability.

[0059] In some embodiments, this application provides an attitude control system for a four-rope lifting rig, including: The modeling module is used to establish the spatial and dynamic models of the four-rope lifting device. The spatial model includes a trolley model, a lifting device model, and a rope model. The dynamic model includes an inextensible rope model and a six-degree-of-freedom rigid body model of the lifting device described using Euler angles. The information acquisition module is used to acquire control information in real time. The control information includes: position information and attitude information of the lifting device, tension information of each rope, and environmental information. The position information and attitude information are acquired by a laser rangefinder, an inertial measurement unit, or a gyroscope. The tension information is acquired by a tension sensor. The environmental information includes wind speed data acquired by a wind speed sensor. The trajectory prediction module is used to substitute the control information into the dynamic model, perform numerical integration based on the translational equation and Euler rotational equation in the model, and calculate the center of mass trajectory and attitude change trajectory of the spreader in the future time window. The control judgment module is used to determine whether there is a moment in the predicted trajectory where the spatial distance between the corresponding centroid position and the target landing point is less than a preset accuracy threshold. If the threshold is met, a descent command is sent to the hoisting controller. The descent control module is used to calculate the descent speed based on the predicted trigger time and control the spreader to be lowered synchronously when it is predicted to reach the target point. The descent speed is determined by the current height, the target height, and the system response compensation time.

[0060] In some embodiments, this application provides a terminal, including: Memory, used to store attitude control simulation programs; A processor is configured to execute the steps of implementing the attitude control method for a four-rope sling when performing the attitude control system for the four-rope sling.

[0061] In some embodiments, this application provides a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the attitude control method for a four-rope sling.

[0062] The basic concepts have been described above. Obviously, for those skilled in the art, the detailed disclosure above is merely illustrative and does not constitute a limitation of this specification. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are suggested in this specification and therefore remain within the spirit and scope of the exemplary embodiments described herein.

[0063] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and should be considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. A method for attitude control of a four-rope lifting rig, characterized in that, Includes the following steps: Step S1: Establish a spatial model, which includes a trolley model, a lifting device model, and a rope model; Step S2: Construct a dynamic model, which includes a rope dynamic model and a lifting device dynamic model. The lifting device dynamic model is a rigid body system with six degrees of freedom. Euler angles are used as parameters to describe the attitude of the lifting device dynamic model. Step S3: Acquire control information in real time. The control information includes the position and attitude information of the lifting device, the tension information of each rope, and environmental information. Step S4: Substitute the control information obtained in step S3 into the dynamic model to predict the motion trajectory of the spreader in the future. When there is a predicted point in the predicted trajectory whose distance between the predicted point and the target landing point is less than the accuracy threshold, control the spreader to descend and complete the landing.

2. The attitude control method for a four-rope lifting device according to claim 1, characterized in that, In step S2, the state variables in the spreader dynamics model include the position of the spreader's center of mass. Attitude angle linear velocity of the center of mass Attitude angular velocity and angular velocity vector The relationship between angular velocity and Euler angles satisfies the following transformation relationship: Among them, matrix This is the nonlinear transformation matrix of the Euler angle rotation velocity.

3. The attitude control method for a four-rope lifting device according to claim 1, characterized in that, In step S2, the rope model is an inextensible model, wherein the geometric constraints between each rope connection point are satisfied: in, and These represent the first [number] on the trolley and the lifting device, respectively. The spatial coordinates of each anchor point , This refers to the fixed length of the rope. The above equality constraints are introduced into the Lagrange system equations, and the generalized coordinates of the system are: The Lagrange equation is corrected to: in, For Lagrange multipliers, corresponding to the th The magnitude of the constraint force on a rope represents the tension in that rope, and this tension is constant along a unit vector: in, Let be the direction of the tension, and let be the first . The rope is anchored at the lifting point. Pointing to the car anchor point The unit vector.

4. The attitude control method for a four-rope lifting device according to claim 3, characterized in that, The magnitude of the tension is determined by the dynamic equilibrium equations and satisfies the overall translational equations: Where M is the mass of the lifting device. Let be the acceleration vector of the center of mass of the spreader. External disturbance force; The external disturbance source is wind-borne interference, and its expression is: in, The drag coefficient, Let A be the air density and A be the windward area of ​​the spreader and container. For the speed of the spreader, For wind speed, The direction of relative velocity.

5. The attitude control method for a four-rope lifting device according to claim 2, characterized in that, The rotational dynamics of the spreader are based on Euler's rotational law and satisfy: in, Let the inertia tensor of the spreading device be... For the first The position vector of the rope anchor point relative to the center of mass of the lifting device.

6. The attitude control method for a four-rope lifting device according to claim 5, characterized in that, In step S4, a prediction model is established, utilizing a system of differential equations within a time window. Numerical integration is performed to obtain the trajectory of the spreader's center of mass over a future time period. With attitude change curve The system of differential equations is as follows: If within the predicted time window At a certain moment, memory The following triggering conditions must be met: in, For the precision threshold, For the center of gravity of the spreading gear at all times The position vector, The target landing point location.

7. The attitude control method for a four-rope lifting device according to claim 6, characterized in that, Controller at time Issue descent control command, where The command includes the desired descent rate: in, To control the descent speed, This is the advance compensation time for controller response lag. The vertical height of the target landing point. For the center of gravity of the spreading gear at all times vertical height The time required to trigger the descent maneuver in advance.

8. A posture control system for a four-rope lifting rig, characterized in that, include: The modeling module is used to establish the spatial and dynamic models of the four-rope lifting device. The spatial model includes a trolley model, a lifting device model, and a rope model. The dynamic model includes an inextensible rope model and a six-degree-of-freedom rigid body model of the lifting device described using Euler angles. The information acquisition module is used to acquire control information in real time. The control information includes: position information and attitude information of the lifting device, tension information of each rope, and environmental information. The position information and attitude information are acquired by a laser rangefinder, an inertial measurement unit, or a gyroscope. The tension information is acquired by a tension sensor. The environmental information includes wind speed data acquired by a wind speed sensor. The trajectory prediction module is used to substitute the control information into the dynamic model, perform numerical integration based on the translational equation and Euler rotational equation in the model, and calculate the center of mass trajectory and attitude change trajectory of the spreader in the future time window. The control judgment module is used to determine whether there is a moment in the predicted trajectory where the spatial distance between the corresponding centroid position and the target landing point is less than a preset accuracy threshold. If the threshold is met, a descent command is sent to the hoisting controller. The descent control module is used to calculate the descent speed based on the predicted trigger time and control the spreader to be lowered synchronously when it is predicted to reach the target point. The descent speed is determined by the current height, the target height, and the system response compensation time.

9. A terminal, characterized in that, include: Memory, used to store attitude control simulation programs; A processor, configured to implement the steps of the attitude control method for a four-rope sling as described in any one of claims 1-7 when executing the attitude control system for the four-rope sling.

10. A computer-readable storage medium, characterized in that, The storage medium stores computer instructions. When the computer reads the computer instructions in the storage medium, the computer executes the attitude control method for a four-rope sling as described in any one of claims 1 to 7.

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