Improved dynamic artificial potential field-based control method and system for tower crane

Abstract

This invention discloses a control method and system for tower cranes based on an improved dynamic artificial potential field. The method includes establishing a three-dimensional working space coordinate system covering the entire working range of the tower crane and collecting working status data in real time; constructing a load-adaptive gravitational field by introducing a load compensation factor to overcome the response delay caused by large inertia; introducing a relative velocity vector into the repulsion model to construct a dynamic repulsion field with relative velocity correction, which is more sensitive to rapidly approaching obstacles; simultaneously establishing an environmental disturbance compensation model to calculate the additional thrust from wind loads and convert it into a potential energy compensation term; finally, eliminating path oscillations by introducing an adaptive virtual damping term related to wind speed, and achieving smooth control using a PID controller. This invention effectively solves the problems of poor adaptability to dynamic environments and weak anti-interference ability in existing technologies, enabling tower cranes to safely and smoothly avoid obstacles in complex wind load and dynamic obstacle environments.

Description

Technical Field

[0001] This invention belongs to the field of tower crane control technology, and more specifically, relates to a tower crane control method and system based on an improved dynamic artificial potential field. Background Technology

[0002] Tower cranes, as core lifting equipment in the construction industry, are widely used in the construction of high-rise and super high-rise buildings, large stadiums, bridge projects, and other construction scenarios. With the increase in construction density and the normalization of multiple tower cranes operating simultaneously, tower crane collision accidents occur frequently, easily causing equipment damage, personnel injuries and fatalities, and project delays. Collision avoidance control and path planning have become key technologies for safe tower crane operation.

[0003] Existing tower crane collision avoidance and path planning technologies have the following main shortcomings: Geometric collision avoidance algorithms: These algorithms are mostly based on two-dimensional plane projection for distance determination. They require separate boundary calculations for different tower crane placement postures and boom angles, resulting in low computational efficiency, failure to cover the risk of tilting collisions in three-dimensional space, and poor adaptability to three-dimensional operations.

[0004] Time slice prediction algorithm: It predicts trajectory based on the assumption of uniform motion, which has a large amount of computation and poor real-time performance. It cannot cope with sudden situations such as sharp turns and sudden appearances of obstacles. In addition, it does not consider the influence of the inertia of the suspended weight, resulting in insufficient prediction accuracy and low obstacle avoidance reliability.

[0005] Traditional artificial potential field method: The calculation is simple, but it has inherent defects when applied to tower cranes. It only sets the repulsive force based on the position relationship and ignores the inertial characteristics of the crane. When dynamic obstacles approach, the braking is lagging. It does not compensate for outdoor wind load disturbances. Under strong winds, the hook trajectory deviates from the planned path and is prone to actual collisions. At the same time, path oscillation is prone to occur near obstacles, resulting in poor motion stability.

[0006] In summary, existing technologies cannot simultaneously meet the requirements of dynamic environment adaptation, wind load interference compensation, heavy load inertia adaptation, and smooth motion. There is an urgent need for a tower crane anti-collision control and path planning technology that is dynamically responsive, has strong anti-interference capabilities, and provides smooth control. Summary of the Invention

[0007] To address the shortcomings of existing technologies, such as poor adaptability to dynamic environments, weak resistance to wind load interference, delayed obstacle avoidance response under heavy loads and large inertia, and the tendency for path oscillations to occur with traditional artificial potential field methods, this invention provides a tower crane control method and system based on an improved dynamic artificial potential field. A three-dimensional spatial coordinate system covering the entire operating range is established with the tower crane base as the origin. Multi-dimensional improvements and reconstructions are made to the traditional artificial potential field method: a load-adaptive gravitational field is constructed by introducing a load compensation factor, and the gravitational gain is adjusted in real time according to the load mass to overcome the delay caused by large inertia motion; the relative velocity vector between the hook and obstacles is incorporated into the repulsion model to construct a dynamically enhanced relative velocity-corrected dynamic repulsion field, achieving sensitive response and early avoidance of rapidly approaching obstacles. The system employs an environmental disturbance compensation model based on aerodynamic principles to accurately calculate the additional thrust from wind loads and convert it into a potential energy compensation term superimposed on the total potential field, effectively offsetting the trajectory deviation caused by wind loads. Simultaneously, an adaptive virtual damping term related to real-time wind speed is introduced to suppress path oscillations. A PID controller smoothly converts the resultant force command into motor control torque, ultimately forming an integrated anti-collision control and path planning scheme that considers load inertia adaptation, dynamic obstacle recognition, wind load disturbance compensation, and smooth motion control. This algorithm comprehensively addresses the inherent defects of traditional geometric anti-collision, time-slice prediction, and conventional artificial potential field methods, significantly improving the operational safety, control accuracy, and operational stability of tower cranes under complex conditions involving multiple tower cranes, strong outdoor winds, and dynamic obstacles.

[0008] To achieve the above objectives, one aspect of the present invention provides a tower crane control method based on an improved dynamic artificial potential field, comprising the following steps: S1: Establish a three-dimensional spatial coordinate system covering the entire operating range of the tower crane with the center of the tower crane base as the origin. The system monitors and collects the current three-dimensional coordinates and velocity vector of the hook, the spatial position of the target point, the real-time mass of the hoisted load, and the real-time wind speed, wind direction and motion status data of dynamic obstacles in the working environment through sensors. S2: By introducing a load compensation factor, a load-adaptive gravitational field is constructed, and the gravitational gain is dynamically adjusted according to the real-time load mass to overcome the response delay caused by large inertia. At the same time, the relative velocity vector between the obstacle and the hook is introduced into the repulsion model to construct a dynamic repulsion field with relative velocity correction. When the two are moving towards each other, the intensity of the repulsion field is dynamically enhanced, thereby achieving sensitive response to dynamic obstacles and early obstacle avoidance. S3: Based on the principles of aerodynamics, an environmental disturbance compensation model is established. Taking into account factors such as air density, drag coefficient, boom windward area and wind direction angle, the model accurately calculates the additional thrust of the wind load on the structure and converts it into an independent potential energy compensation component, which is then superimposed on the total resultant force field to offset the hook trajectory deviation caused by the wind load in real time, thereby improving the accuracy of path planning and motion control. S4: The adaptive gravity of the load, the dynamic repulsive force of the relative velocity correction, and the wind load compensation force are vector superimposed to obtain the total potential field force; an adaptive virtual damping term related to the real-time wind speed is introduced to eliminate the oscillation phenomenon of the potential field method near the equilibrium point; finally, the final resultant force command is converted into the desired acceleration through the PID controller, and then the control torque of the motor is output to drive the crane to complete safe and smooth obstacle avoidance and path planning motion.

[0009] Furthermore, the construction of the load-adaptive gravitational field in step S2 includes: Using the relative distance between the current position of the hook and the target point as the variable, construct the basic gravitational potential function, the expression of which is: ,in, It is gravitational potential energy; Real-time three-dimensional coordinates of the hook; The target point's three-dimensional coordinates; This is the Euclidean distance between the hook and the target point; This is the gravity gain coefficient after adaptive correction based on load mass; Introducing real-time load mass as an adaptive adjustment variable, and adjusting the preset basic gravitational gain coefficient. Dynamic correction is performed, and the correction formula is as follows: , The load mass is collected in real time by the weighing sensor. Preset critical load mass; Taking the negative gradient of the gravitational potential function yields the adaptive gravitational force of the load acting on the hook; the expression is: , in, For gradient operators, This is the load-adaptive gravity vector.

[0010] Furthermore, constructing the dynamic repulsive field with relative velocity correction includes: The radius of influence of the pre-set obstacle repulsive force Real-time calculation of the Euclidean distance between the hook and the obstacle. : ,in, Real-time three-dimensional coordinates of the hook; Real-time 3D coordinates of the obstacle; only when The repulsive force field takes effect at this time; Obtain the real-time velocity vector of the hook Real-time velocity vector of obstacles Calculate the relative velocity between the hook and the obstacle. ; By introducing a relative velocity correction term into the traditional repulsive potential function, a dynamic repulsive potential function is formed: in, It is a dynamic repulsive potential energy; Based on the repulsive force gain coefficient, The relative velocity between the hook and the obstacle; This is the maximum relative speed allowed by the system; The negative gradient of the dynamic repulsive potential function is used to obtain the dynamic repulsive vector. : .

[0011] Further, step S3 includes: Based on the wind load calculation formula, the additional wind load thrust acting on the boom and hook system is obtained. : In the formula, air density (take) ); This refers to the drag coefficient; The windward area of ​​the boom; Real-time wind speed; The angle between the wind direction and the boom axis; Add thrust to wind load It is converted into a three-dimensional spatial vector and directly superimposed on the total potential field force as an independent compensating force component, thereby offsetting the drag and displacement of the hook position by the wind in real time. Further, step S4 includes: The initial total force acting on the hook is obtained by vector superposition of the load-adaptive attraction and the dynamic repulsion force from multiple obstacles. : in, The gravitational vector generated by the load-adaptive gravitational field; In order to conduct work within the work space The dynamic repulsion vectors of each obstacle are calculated separately and then summed. The negative gradient is obtained from the dynamic repulsive potential function corrected for relative velocity; Adaptive Virtual Damping Term The expression is: in, The real-time velocity vector of the hook is used to consume the system's kinetic energy and suppress high-frequency oscillations. The damping coefficient; The initial total resultant force and the adaptive virtual damping term are combined. By superimposing these forces, the final total force used for control is obtained. : .

[0012] Furthermore, the damping coefficient in step S4 The adjustment is based on real-time environmental wind speed and uses the following formula: in, This is the base damping coefficient, which is the default damping strength under no wind or light wind conditions. Real-time ambient wind speed; The wind speed threshold for safe tower crane operation.

[0013] Furthermore, step S4 also includes converting the final total resultant force into a desired acceleration command for the hook; The expression for the desired acceleration command is: ,in, For the real-time weight of the suspended load; The inherent mass of the hook and lifting equipment.

[0014] Furthermore, step S4 also includes using a PD-type PID controller to convert the deviation between the desired acceleration and the actual acceleration into motor control torque. : in, This is the actual acceleration of the hook; This is the proportionality coefficient; is the differential coefficient.

[0015] A second aspect of the present invention provides a tower crane control system based on an improved dynamic artificial potential field, for implementing the tower crane control method based on the improved dynamic artificial potential field, comprising: The data acquisition and coordinate system establishment module is used to establish a three-dimensional spatial coordinate system covering the entire working range of the tower crane with the center of the tower crane base as the origin. It monitors and collects the current three-dimensional coordinates and velocity vector of the hook, the spatial position of the target point, the real-time mass of the hoisted load, and the real-time wind speed, wind direction and motion status data of dynamic obstacles in the working environment through sensors. An improved dynamic artificial potential field construction module is included, comprising a load-adaptive gravitational field unit and a dynamic repulsive field unit. The load-adaptive gravitational field unit is used to introduce a load compensation factor and dynamically adjust the gravitational gain according to the real-time load mass to overcome the large inertial response delay. The dynamic repulsive field unit is used to introduce a relative velocity vector into the repulsive model and dynamically enhance the repulsive field strength when the obstacle and the hook move towards each other, thereby achieving sensitive response to dynamic obstacles and early obstacle avoidance. The environmental disturbance compensation module is used to establish an environmental disturbance compensation model based on aerodynamic principles. It comprehensively considers air density, drag coefficient, boom windward area, and wind direction angle to accurately calculate the additional thrust of the wind load on the structure and converts it into an independent potential energy compensation component, which is then superimposed on the total resultant force field to offset the hook trajectory deviation caused by wind load in real time, thereby improving the accuracy of path planning and motion control. Smooth control and drive execution module: It is used to vector superimpose the load adaptive attraction, the dynamic repulsive force of relative speed correction and the wind load compensation force to obtain the total potential force; it introduces an adaptive virtual damping term related to real-time wind speed to eliminate oscillations near the equilibrium point, and converts the final resultant force command into the desired acceleration and output motor control torque through the PID controller to drive the tower crane to complete safe and smooth obstacle avoidance and path planning motion.

[0016] A third aspect of the present invention provides a computer-readable storage medium storing a computer program that is executed by a processor to implement the tower crane control method based on an improved dynamic artificial potential field.

[0017] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects: (1) This invention introduces the relative velocity vector between the hook and the obstacle into the traditional repulsion model to construct a dynamic repulsion field with relative velocity correction. It can dynamically increase the intensity of the repulsion field when the hook and the obstacle are rapidly approaching each other, based on the real-time relative motion state of the hook and the obstacle, and significantly improve the response sensitivity to dynamic obstacles. At the same time, it is combined with the load adaptive gravitational field to dynamically adjust the gravitational gain coefficient according to the real-time mass of the load, effectively compensating for the motion response delay caused by the large inertia of the tower crane load. This allows the control system to trigger early obstacle avoidance actions before the obstacle enters the danger distance, fundamentally overcoming the defects of the traditional artificial potential field method that only judges obstacle avoidance based on positional relationship, brake lag under heavy load conditions, and insufficient dynamic obstacle response capability. It realizes early avoidance, smooth turning and precise protection of dynamic obstacles, and greatly improves the operating safety and obstacle avoidance reliability of tower cranes in multi-machine collaboration and complex dynamic obstacle operation environments.

[0018] (2) Based on the principle of aerodynamics, this invention constructs an environmental disturbance compensation model, which comprehensively calculates the additional thrust of wind load by taking into account air density, wind resistance coefficient, windward area of ​​boom and wind direction angle, and superimposes it as an independent potential energy compensation term into the total potential field. This can offset the influence of outdoor wind field on hook trajectory in real time, solve the problem that traditional algorithms do not consider wind load interference, resulting in large deviation between planned trajectory and actual movement, and significantly improve control stability and operation accuracy under complex meteorological conditions.

[0019] (3) In the calculation of total resultant force, the present invention introduces an adaptive virtual damping term related to real-time wind speed, which can dynamically adjust the damping coefficient according to the ambient wind speed, effectively suppressing the path oscillation and shaking phenomenon that is prone to occur at the edge of obstacles and near the equilibrium point in the traditional artificial potential field method. Combined with the PID controller, smooth torque output is achieved, making the hook motion curve continuous and stable, avoiding impact and trajectory change of the actuator, and improving the smoothness of the whole machine operation.

[0020] (4) In the calculation of total resultant force, the present invention introduces an adaptive virtual damping term related to real-time wind speed, which can dynamically adjust the damping coefficient according to the ambient wind speed, effectively suppressing the path oscillation and shaking phenomenon that is prone to occur at the edge of obstacles and near the equilibrium point in the traditional artificial potential field method. Combined with the PID controller, smooth torque output is achieved, making the hook motion curve continuous and stable, avoiding impact and trajectory change of the actuator, and improving the smoothness of the whole machine operation. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating a tower crane control method based on an improved dynamic artificial potential field according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the overall process of the obstacle avoidance algorithm in a tower crane control method based on an improved dynamic artificial potential field according to an embodiment of the present invention. Figure 3 In an embodiment of the present invention, a control method for a tower crane based on an improved dynamic artificial potential field is described, wherein the control parameters are as follows: , A schematic diagram comparing the simulation of obstacle avoidance trajectories; Figure 4 In an embodiment of the present invention, a control method for a tower crane based on an improved dynamic artificial potential field is described, wherein the control parameters are as follows: , A schematic diagram comparing the simulation of obstacle avoidance trajectories; Figure 5 In an embodiment of the present invention, a control method for a tower crane based on an improved dynamic artificial potential field is described, wherein the control parameters are as follows: , A schematic diagram comparing the simulation of obstacle avoidance trajectories; Figure 6 In an embodiment of the present invention, a control method for a tower crane based on an improved dynamic artificial potential field is described, wherein the control parameters are as follows: , Simulation comparison of potential field intensity in the XY plane; Figure 7 In an embodiment of the present invention, a control method for a tower crane based on an improved dynamic artificial potential field is described, wherein the control parameters are as follows: , Simulation comparison of potential field intensity in the XY plane; Figure 8In an embodiment of the present invention, a control method for a tower crane based on an improved dynamic artificial potential field is described, wherein the control parameters are as follows: , Simulation comparison of potential field intensity in the XY plane; Figure 9 In an embodiment of the present invention, a control method for a tower crane based on an improved dynamic artificial potential field is described, wherein the control parameters are as follows: , Comparison of motion curve simulations; Figure 10 In an embodiment of the present invention, a control method for a tower crane based on an improved dynamic artificial potential field is described, wherein the control parameters are as follows: , Comparison of motion curve simulations; Figure 11 In an embodiment of the present invention, a control method for a tower crane based on an improved dynamic artificial potential field is described, wherein the control parameters are as follows: , Comparison of motion curve simulations; Figure 12 This is a schematic diagram of the structure of a tower crane control system based on an improved dynamic artificial potential field, according to an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0023] like Figure 1 As shown, one aspect of the present invention provides a tower crane control method based on an improved dynamic artificial potential field, comprising the following steps: S1: Establish a three-dimensional spatial coordinate system covering the entire operating range of the tower crane with the center of the tower crane base as the origin. The system monitors and collects the current three-dimensional coordinates and velocity vector of the hook, the spatial position of the target point, the real-time mass of the hoisted load, and the real-time wind speed, wind direction and motion status data of dynamic obstacles in the working environment through sensors. S2: By introducing a load compensation factor, a load-adaptive gravitational field is constructed, and the gravitational gain is dynamically adjusted according to the real-time load mass to overcome the response delay caused by large inertia. At the same time, the relative velocity vector between the obstacle and the hook is introduced into the repulsion model to construct a dynamic repulsion field with relative velocity correction. When the two are moving towards each other, the intensity of the repulsion field is dynamically enhanced, thereby achieving sensitive response to dynamic obstacles and early obstacle avoidance. S3: Based on the principles of aerodynamics, an environmental disturbance compensation model is established. Taking into account factors such as air density, drag coefficient, boom windward area and wind direction angle, the model accurately calculates the additional thrust of the wind load on the structure and converts it into an independent potential energy compensation component, which is then superimposed on the total resultant force field to offset the hook trajectory deviation caused by the wind load in real time, thereby improving the accuracy of path planning and motion control. S4: The adaptive gravity of the load, the dynamic repulsive force of the relative velocity correction, and the wind load compensation force are vector superimposed to obtain the total potential field force; an adaptive virtual damping term related to the real-time wind speed is introduced to eliminate the oscillation phenomenon of the potential field method near the equilibrium point; finally, the final resultant force command is converted into the desired acceleration through the PID controller, and then the control torque of the motor is output to drive the crane to complete safe and smooth obstacle avoidance and path planning motion.

[0024] Figure 2 This is the overall flowchart of the obstacle avoidance algorithm of the present invention, which fully demonstrates the execution process of the tower crane control based on the improved dynamic artificial potential field: First, in stage 1: the action of the gravitational field, the load-adaptive gravitational field drives the hook to move towards the target point through the gravitational gradient; when the hook enters stage 2: the obstacle influence zone, the dynamic repulsive field with relative velocity correction is activated, and the obstacle avoidance repulsive force is applied to the hook; then, in stage 3: dynamic path adjustment, the hook's movement direction is corrected in real time in combination with the relative velocity vector to achieve early avoidance of dynamic obstacles; then, in stage 4: damping and oscillation suppression, an adaptive virtual damping term is introduced to eliminate path oscillation, and the resultant force command is converted into smooth control torque through the PID controller, finally driving the hook to converge smoothly to the target point, completing the entire process of safe obstacle avoidance and path planning.

[0025] This invention can effectively solve the problems of poor dynamic environment adaptability, weak anti-interference ability and easy trajectory oscillation of existing tower crane anti-collision technology. It can realize safe, smooth and accurate obstacle avoidance and path planning of tower cranes in complex wind load and dynamic obstacle environment. It is suitable for complex construction scenarios such as multi-tower collaboration and strong wind outdoors.

[0026] The following is a detailed explanation of each step of the tower crane control method based on an improved dynamic artificial potential field according to the present invention.

[0027] (1) Establishing a three-dimensional work space coordinate system and data acquisition Using the center of the tower crane's base as the origin of the coordinate system Establish a three-dimensional spatial coordinate system covering the entire operating range of the tower crane. The axis is along the horizontal extension direction of the boom; The axis runs along a horizontal direction perpendicular to the boom; The axis is aligned vertically upwards, and core operational data is collected and uploaded in real time via sensors. This includes the hook's current position, operating speed, actual lifting weight, ambient wind speed and direction, and the location and movement of obstacles within the work area. This provides a precise and real-time data foundation for subsequent potential field construction and path calculation. The current hook position coordinates are set as follows: Target point three-dimensional coordinates Dynamic obstacle location Hook velocity vector obstacle velocity vector ; (2) Constructing a load-adaptive gravitational field Using the target point of the tower crane as the gravitational source, a basic gravitational field pointing towards the target point is established. To overcome the large inertial motion lag problem caused by the heavy load, a load compensation factor is introduced. The gravitational gain coefficient is dynamically and adaptively adjusted based on the real-time mass of the suspended load collected by sensors, forming a load-adaptive gravitational field. The specific implementation process is as follows: Using the relative distance between the current position of the hook and the target point as the variable, construct the basic gravitational potential function, the expression of which is: ,in, It is gravitational potential energy; Real-time three-dimensional coordinates of the hook; The target point's three-dimensional coordinates; This is the Euclidean distance between the hook and the target point; This is the gravity gain coefficient after adaptive correction based on load mass; Considering the influence of load mass on the hook's motion inertia, real-time load mass is introduced as an adaptive adjustment variable, adjusting the preset basic gravitational gain coefficient. Dynamic correction is performed, and the correction formula is as follows: , The load mass is collected in real time by the weighing sensor. To preset the critical load mass, it is usually taken as 50% of the tower crane's rated load; when the load mass When increased, the corrected gravitational gain coefficient The synchronous increase makes the gravitational field strength stronger as the load increases, which offsets the problem of large inertia and slow response of the hook under large load; Taking the negative gradient of the gravitational potential function yields the adaptive gravitational force acting on the hook, with the direction of the force always pointing towards the target point. The expression for this force is: ; in For gradient operators, It is a load-adaptive gravity vector whose magnitude is dynamically adjusted according to the load mass, ensuring that the hook can move stably and quickly toward the target point under different load conditions, and avoiding excessive tracking errors due to excessive inertia; The calculated adaptive gravity As the output of the gravitational component of the total potential field, it is used to subsequently superimpose with the dynamic repulsive force and wind load compensation force to form the total resultant force. (3) Construct a dynamic repulsive field with relative velocity correction Using obstacles within the workspace as the repulsive force source, a relative velocity vector is introduced to dynamically correct the intensity of the repulsive field based on the traditional position-type repulsive field, forming a relative velocity-corrected dynamic repulsive field that can sensitively respond to dynamic obstacles. The specific implementation process is as follows: The radius of influence of the pre-set obstacle repulsive force Real-time calculation of the Euclidean distance between the hook and the obstacle: ,in, Real-time three-dimensional coordinates of the hook; Real-time 3D coordinates of the obstacle; This represents the real-time distance between the hook and the obstacle. The effective radius of the repulsive force of the obstacle is only when The repulsive force field takes effect at this time; Obtain the real-time velocity vector of the hook Real-time velocity vector of obstacles Calculate the relative velocity between the hook and the obstacle. : When the relative speed between the hook and the obstacle When the two are moving toward each other, it is determined to be a dangerous approaching state; By introducing a relative velocity correction term into the traditional repulsive potential function, a dynamic repulsive potential function is formed: in, It is a dynamic repulsive potential energy; Based on the repulsive force gain coefficient, The relative velocity between the hook and the obstacle; This is the maximum relative speed allowed by the system; When an obstacle approaches the hook, the relative velocity increases and the repulsive field is significantly enhanced, which not only ensures that no collision occurs, but also forces the hook to change its path in advance to avoid entering the danger zone. when hour, This indicates that the obstacle is more than the effective radius of the hook. At this point, the obstacle has no repulsive force on the hook and is only at a safe distance. when When the obstacle enters the collision avoidance warning range, the full dynamic repulsive potential function is activated, and a repulsive force is generated. It is the repulsive potential function of the traditional artificial potential field method, which is determined only by the positional distance; This is a relative velocity correction term, which occurs when the hook approaches an obstacle rapidly in opposite directions. The increase in the correction term significantly amplifies the total repulsive potential energy, forcing the hook to decelerate / turn earlier to avoid inertial collisions. When the two move in the same direction or their relative speed is very small, the correction term approaches 1, degenerating into a traditional position-type repulsive field, ensuring normal operating efficiency; Compared to traditional repulsive force fields that rely solely on location, this formula can identify both "static obstacles" and "rapidly approaching dynamic obstacles," providing enhanced protection for the latter in advance and resolving the problem of braking lag under the large inertia of tower cranes; through Set a collision avoidance warning distance; if the distance is exceeded, the repulsion force will automatically shut off to avoid unnecessary path interference. Limit the upper limit of speed correction to prevent excessive amplification of repulsive force from causing path oscillation; The negative gradient of the dynamic repulsive potential function is used to obtain the dynamic repulsive vector. : Dynamic repulsion vector The combined force, along with the load adaptive gravity, wind load compensation force, and damping force, is converted into the tower crane motor control torque through a PID controller, enabling smooth obstacle avoidance.

[0028] (4) Component environmental disturbance compensation model To address the deviation interference caused by wind load on the hook trajectory in outdoor operating environments, an environmental disturbance compensation model is established based on aerodynamic principles. This model converts the wind load into a superimposed potential energy compensation force to offset the wind-induced trajectory deviation. The specific implementation process is as follows: Real-time wind speed is collected using wind speed and direction sensors. with wind angle ,in, The angle between the wind direction and the boom axis; Based on the wind load calculation formula, the additional wind load thrust acting on the boom and hook system is obtained. : In the formula, air density (take) ); This refers to the drag coefficient; The windward area of ​​the boom; Real-time wind speed; The angle between the wind direction and the boom axis; Add thrust to wind load It is converted into a three-dimensional spatial vector and directly superimposed on the total potential field force as an independent compensating force component, which can offset the drag and offset of the hook position by the wind in real time, and ensure that the planned trajectory is consistent with the actual movement trajectory. Add thrust to wind load As a disturbance compensation component of the overall potential field, it participates in the calculation of the total resultant force.

[0029] (5) Smooth path control with integrated adaptive virtual damping Based on the improved dynamic artificial potential field, the total potential field force calculation is completed, adaptive virtual damping is introduced to suppress oscillations, and the final motor control torque is output through a PID controller to achieve smooth and stable obstacle avoidance movement of the tower crane hook, thus completing the final path planning and execution. The specific implementation process is as follows: By vector superimposing the load-adaptive attractive force and the dynamic repulsive force from multiple obstacles, the initial total resultant force acting on the hook is obtained: in, It is a gravitational vector generated by the load-adaptive gravitational field, whose direction always points to the target point and whose magnitude is dynamically adjusted according to the weight of the load. In order to conduct work within the work space The dynamic repulsion vectors of each obstacle are calculated separately and then summed. The resultant force is obtained by taking the negative gradient of the dynamic repulsive potential function corrected by relative velocity; this resultant force embodies the core obstacle avoidance logic of "moving towards the target point and moving away from obstacles"; To address the issue of path oscillations near local minima / equilibrium points in traditional artificial potential field methods, and to enhance motion stability in strong wind environments, an adaptive virtual damping term is introduced. : in, The real-time velocity vector of the hook is used to consume the system's kinetic energy and suppress high-frequency oscillations. This is the damping coefficient, which is not a fixed value but is adaptively adjusted according to the real-time ambient wind speed. The adjustment formula is as follows: , This is the basic damping coefficient, the default damping strength under no wind or light wind conditions; The absolute value of the real-time ambient wind speed is used to ensure that the damping coefficient is non-negative; The wind speed threshold for safe tower crane operation is used to normalize the impact of wind speed; the higher the wind speed, the lower the wind speed. The greater the synchronous increase, the stronger the damping effect, further offsetting the trajectory jitter and path oscillation caused by wind disturbance.

[0030] The initial total resultant force is superimposed with the adaptive damping force to obtain the final total resultant force used for control: This combined force simultaneously takes into account obstacle avoidance guidance, multi-obstacle protection, wind disturbance suppression and oscillation elimination, providing a stable force input for the generation of subsequent control commands; The final total force is converted into a desired acceleration command for the hook, which drives the tower crane's actuator; the expression for the desired acceleration command for the hook is: ,in, The real-time mass of the suspended load (collected by the load cell); The inherent mass of the hook and lifting gear is taken into account; based on Newton's second law, the force command is linearly mapped into the acceleration command, which conforms to the kinematic characteristics of the tower crane.

[0031] A PD-type PID controller (proportional-derivative) is used to convert the deviation between the desired acceleration and the actual acceleration into motor control torque. : in, The actual acceleration of the hook (obtained by the differential of the velocity sensor or directly by the accelerometer); This is a proportionality coefficient used to quickly reduce acceleration deviation; These are differential coefficients used to suppress the rate of change of acceleration and enhance system stability. Motor control torque The output is sent to the tower crane's luffing, slewing, or hoisting motors to drive the hook to move smoothly, without vibration, and precisely towards the target point along the planned path, completing the entire obstacle avoidance control process.

[0032] (6) Simulation verification A simulation environment was set up using MATLAB. After inputting the operating parameters, the following output was obtained: 3D obstacle avoidance trajectory diagram: Verify whether the hook can smoothly avoid dynamic obstacles; Potential field intensity distribution map: visually displays the spatial distribution of gravity, repulsion and damping; Motion curves (velocity / acceleration / torque): verify motion smoothness and oscillation suppression effect; 3D trajectory diagram (e.g.) Figures 3-5 As shown in the figure, the blue solid line represents the motion trajectory of the hook planned by the algorithm of this invention under different parameters, and the red dots represent the positions of dynamic obstacles. Simulation results show that when an obstacle intrusion is detected, the trajectory smoothly shifts outward (in the negative Y-axis direction). While successfully avoiding the obstacle's safe zone, the Z-axis height remains stable without drastic rises or falls, verifying the effectiveness of the algorithm.

[0033] Potential field intensity distribution map (e.g.) Figures 6-8The diagram shows the potential field intensity distribution under different parameters, with color depth representing potential field energy levels. The red ring-shaped area corresponds to the high repulsive potential energy region around the obstacle, while the blue area corresponds to the low gravitational potential energy region around the target point. The diagram shows that with the intervention of the relative velocity parameter, the red repulsive region in front of the obstacle significantly expands, forming an asymmetric "defense shield" that effectively prevents the hook from rushing into the danger zone due to inertia.

[0034] Motion curve (e.g.) Figures 9-11 As shown in the figure, the motion curves under different parameters are plotted, with the horizontal axis representing the number of iterations and the vertical axis representing the spatial position. The red, green, and blue curves correspond to the displacement changes along the X, Y, and Z axes, respectively. The curves are smooth and continuous overall, without high-frequency oscillations, proving that the variable damping term effectively suppresses system jitter and ensures stable motor output torque.

[0035] Through MATLAB simulation, under the parameter settings, the algorithm plans a smooth 3D trajectory with the highest obstacle avoidance efficiency, effectively bypassing dynamic obstacles.

[0036] like Figure 12 As shown, a second aspect of the present invention provides a tower crane control system based on an improved dynamic artificial potential field for implementing the above method, comprising: The data acquisition and coordinate system establishment module is used to establish a three-dimensional spatial coordinate system covering the entire working range of the tower crane with the center of the tower crane base as the origin. It monitors and collects the current three-dimensional coordinates and velocity vector of the hook, the spatial position of the target point, the real-time mass of the hoisted load, and the real-time wind speed, wind direction and motion status data of dynamic obstacles in the working environment through sensors. An improved dynamic artificial potential field construction module is included, comprising a load-adaptive gravitational field unit and a dynamic repulsive field unit. The load-adaptive gravitational field unit is used to introduce a load compensation factor and dynamically adjust the gravitational gain according to the real-time load mass to overcome the large inertial response delay. The dynamic repulsive field unit is used to introduce a relative velocity vector into the repulsive model and dynamically enhance the repulsive field strength when the obstacle and the hook move towards each other, thereby achieving sensitive response to dynamic obstacles and early obstacle avoidance. The environmental disturbance compensation module is used to establish an environmental disturbance compensation model based on aerodynamic principles. It comprehensively considers air density, drag coefficient, boom windward area, and wind direction angle to accurately calculate the additional thrust of the wind load on the structure and converts it into an independent potential energy compensation component, which is then superimposed on the total resultant force field to offset the hook trajectory deviation caused by wind load in real time, thereby improving the accuracy of path planning and motion control. Smooth control and drive execution module: It is used to vector superimpose the load adaptive attraction, the dynamic repulsive force of relative speed correction and the wind load compensation force to obtain the total potential force; it introduces an adaptive virtual damping term related to real-time wind speed to eliminate oscillations near the equilibrium point, and converts the final resultant force command into the desired acceleration and output motor control torque through the PID controller to drive the tower crane to complete safe and smooth obstacle avoidance and path planning motion.

[0037] It should be noted that the tower crane control system based on the improved dynamic artificial potential field provided in this embodiment can be a computer program (including program code) running on a computer device. For example, the tower crane control system based on the improved dynamic artificial potential field is an application software. The tower crane control system based on the improved dynamic artificial potential field can be used to execute the corresponding steps in the methods provided in the embodiments of this application.

[0038] This application also provides a computer-readable storage medium storing a computer program that is executed by a processor to implement... Figure 1 The methods provided in each step are detailed in the implementation methods provided in the above steps, and will not be repeated here.

[0039] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A tower crane control method based on an improved dynamic artificial potential field, characterized in that, Includes the following steps: S1: Establish a three-dimensional spatial coordinate system covering the entire operating range of the tower crane, and monitor and collect in real time the current three-dimensional coordinates and velocity vector of the hook, the spatial position of the target point, the real-time mass of the hoisted load, and the real-time wind speed, wind direction and motion status data of dynamic obstacles in the operating environment. S2: By introducing a load compensation factor, a load-adaptive gravitational field is constructed, and the gravitational gain is dynamically adjusted according to the real-time load mass to overcome the response delay caused by large inertia. At the same time, the relative velocity vector between the obstacle and the hook is introduced into the repulsion model to construct a dynamic repulsion field with relative velocity correction. When the two are moving towards each other, the intensity of the repulsion field is dynamically enhanced, thereby achieving sensitive response to dynamic obstacles and early obstacle avoidance. S3: Based on the principles of aerodynamics, an environmental disturbance compensation model is established. Taking into account factors such as air density, drag coefficient, boom windward area and wind direction angle, the model accurately calculates the additional thrust of the wind load on the structure and converts it into an independent potential energy compensation component, which is then superimposed on the total resultant force field to offset the hook trajectory deviation caused by the wind load in real time, thereby improving the accuracy of path planning and motion control. S4: The adaptive gravity of the load, the dynamic repulsive force of the relative velocity correction, and the wind load compensation force are vector superimposed to obtain the total potential field force; an adaptive virtual damping term related to the real-time wind speed is introduced to eliminate the oscillation phenomenon of the potential field method near the equilibrium point; finally, the final resultant force command is converted into the desired acceleration through the PID controller, and then the control torque of the motor is output to drive the crane to complete safe and smooth obstacle avoidance and path planning motion.

2. The tower crane control method based on an improved dynamic artificial potential field according to claim 1, characterized in that: Step S2 involves constructing a load-adaptive gravitational field, including: Using the relative distance between the current position of the hook and the target point as the variable, construct the basic gravitational potential function, the expression of which is: ,in, It is gravitational potential energy; Real-time three-dimensional coordinates of the hook; The target point's three-dimensional coordinates; This is the Euclidean distance between the hook and the target point; This is the gravity gain coefficient after adaptive correction based on load mass; Introducing real-time load mass as an adaptive adjustment variable, and adjusting the preset basic gravitational gain coefficient. Dynamic correction is performed, and the correction formula is as follows: , The load mass is collected in real time by the weighing sensor. Preset critical load mass; Taking the negative gradient of the gravitational potential function yields the adaptive gravitational force of the load acting on the hook; the expression is: ， in, For gradient operators, This is the load-adaptive gravity vector.

3. The tower crane control method based on an improved dynamic artificial potential field according to claim 2, characterized in that: In step S2, constructing the dynamic repulsive field with relative velocity correction includes: The radius of influence of the pre-set obstacle repulsive force Real-time calculation of the Euclidean distance between the hook and the obstacle. : ,in, Real-time three-dimensional coordinates of the hook; Real-time 3D coordinates of the obstacle; only when The repulsive force field takes effect at this time; Obtain the real-time velocity vector of the hook Real-time velocity vector of obstacles Calculate the relative velocity between the hook and the obstacle. ; By introducing a relative velocity correction term into the traditional repulsive potential function, a dynamic repulsive potential function is formed: in, It is a dynamic repulsive potential energy; Based on the repulsive force gain coefficient, The relative velocity between the hook and the obstacle; This is the maximum relative speed allowed by the system; The negative gradient of the dynamic repulsive potential function is used to obtain the dynamic repulsive vector. : 。 4. A tower crane control method based on an improved dynamic artificial potential field according to any one of claims 1-3, characterized in that: Step S3 includes: Based on the wind load calculation formula, the additional wind load thrust acting on the boom and hook system is obtained. : In the formula, air density (take) ); This refers to the drag coefficient; The windward area of ​​the boom; Real-time wind speed; The angle between the wind direction and the boom axis; Add thrust to wind load It is converted into a three-dimensional spatial vector and directly superimposed on the total potential field force as an independent compensating force component, thereby offsetting the drag and displacement of the hook position by the wind in real time.

5. A tower crane control method based on an improved dynamic artificial potential field according to any one of claims 1-3, characterized in that: Step S4 includes: The initial total force acting on the hook is obtained by vector superposition of the load-adaptive attraction and the dynamic repulsion force from multiple obstacles. : in, The gravitational vector generated by the load-adaptive gravitational field; In order to conduct work within the work space The dynamic repulsion vectors of each obstacle are calculated separately and then summed. The negative gradient is obtained from the dynamic repulsive potential function corrected for relative velocity; Adaptive Virtual Damping Term The expression is: in, The real-time velocity vector of the hook is used to consume the system's kinetic energy and suppress high-frequency oscillations. The damping coefficient; The initial total resultant force and the adaptive virtual damping term are combined. By superimposing these forces, the final total force used for control is obtained. : 。 6. The tower crane control method based on an improved dynamic artificial potential field according to claim 5, characterized in that: Damping coefficient in step S4 The adjustment is based on real-time environmental wind speed and uses the following formula: in, This is the base damping coefficient, which is the default damping strength under no wind or light wind conditions. Real-time ambient wind speed; The wind speed threshold for safe tower crane operation.

7. A tower crane control method based on an improved dynamic artificial potential field according to claim 6, characterized in that: Step S4 also includes converting the final total resultant force into a desired acceleration command for the hook; The expression for the desired acceleration command is: ,in, For the real-time weight of the suspended load; The inherent mass of the hook and lifting equipment.

8. A tower crane control method based on an improved dynamic artificial potential field according to claim 7, characterized in that: Step S4 also includes using a PD-type PID controller to convert the deviation between the desired acceleration and the actual acceleration into motor control torque. : in, This is the actual acceleration of the hook; This is the proportionality coefficient; is the differential coefficient.

9. A tower crane control system based on an improved dynamic artificial potential field, characterized in that, A tower crane control method based on an improved dynamic artificial potential field as described in any one of claims 1-8, comprising: The data acquisition and coordinate system establishment module is used to establish a three-dimensional spatial coordinate system covering the entire working range of the tower crane with the center of the tower crane base as the origin. It monitors and collects the current three-dimensional coordinates and velocity vector of the hook, the spatial position of the target point, the real-time mass of the hoisted load, and the real-time wind speed, wind direction and motion status data of dynamic obstacles in the working environment through sensors. An improved dynamic artificial potential field construction module is included, comprising a load-adaptive gravitational field unit and a dynamic repulsive field unit. The load-adaptive gravitational field unit is used to introduce a load compensation factor and dynamically adjust the gravitational gain according to the real-time load mass to overcome the large inertial response delay. The dynamic repulsive field unit is used to introduce a relative velocity vector into the repulsive model and dynamically enhance the repulsive field strength when the obstacle and the hook move towards each other, thereby achieving sensitive response to dynamic obstacles and early obstacle avoidance. The environmental disturbance compensation module is used to establish an environmental disturbance compensation model based on aerodynamic principles. It comprehensively considers air density, drag coefficient, boom windward area, and wind direction angle to accurately calculate the additional thrust of the wind load on the structure and converts it into an independent potential energy compensation component, which is then superimposed on the total resultant force field to offset the hook trajectory deviation caused by wind load in real time, thereby improving the accuracy of path planning and motion control. Smooth control and drive execution module: It is used to vector superimpose the load adaptive attraction, the dynamic repulsive force of relative speed correction and the wind load compensation force to obtain the total potential force; it introduces an adaptive virtual damping term related to real-time wind speed to eliminate oscillations near the equilibrium point, and converts the final resultant force command into the desired acceleration and output motor control torque through the PID controller to drive the tower crane to complete safe and smooth obstacle avoidance and path planning motion.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that is executed by a processor to implement the tower crane control method based on an improved dynamic artificial potential field as described in any one of claims 1 to 8.

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