A control system and method for tower crane

Abstract

The present invention provides a control system for a tower crane, which includes a parameter training module and a trajectory control module; the parameter training module is used to automatically adjust the initial PID parameters according to the trajectory fit between the pre-motion trajectory of the tower crane hook and the planned trajectory, and obtain the adjusted PID parameters of the control system, wherein the pre-motion trajectory is the motion trajectory obtained when the tower crane hook is controlled to move toward the target point according to the initial PID parameters and the planned trajectory; the trajectory control module is used to control the hook to move toward the target point according to the adjusted PID parameters and the planned trajectory. The present invention also provides a control method for a tower crane accordingly. The technical solution of the present invention realizes high-precision motion control of the tower crane, reduces safety hazards, avoids manual participation in hoisting operations, and truly realizes unmanned hoisting.

Description

Technical Field

[0001] The present invention relates to the field of intelligent construction, and in particular to a control system and method for a tower crane. Background Art

[0002] Most of the tower cranes in the industry are operated manually on the spot by people on the tower crane. Considering the shortage of workers working at high altitude on the tower crane, some manufacturers have realized remote control. It is not so much remote control as it is remote operation. The cab control panel on the top of the tower crane is transplanted to the remote end through communication means, and then manually operated and controlled at the remote end. However, this remote operation method has certain disadvantages and does not change the original operation method. It still requires the cooperation of two personnel, the tower operator and the signalman.

[0003] For construction parties, the most important contradiction at present is the shortage of tower crane operators. Therefore, realizing automatic control of tower cranes while ensuring safety, reducing the demand for tower crane operators, and improving the operating efficiency of tower cranes are the core demands of various construction parties. Summary of the invention

[0004] In view of this, an embodiment of the present invention provides a control system and method for a tower crane, the control system comprising a parameter training module and a trajectory control module; the parameter training module is used to automatically adjust the initial PID parameters according to the trajectory fit between the pre-motion trajectory of the tower crane hook and the planned trajectory, and obtain the adjusted PID parameters of the control system, the pre-motion trajectory is the motion trajectory obtained when the tower crane hook is controlled to move toward the target point according to the initial PID parameters and the planned trajectory; the trajectory control module is used to control the hook to move toward the target point according to the adjusted PID parameters and the planned trajectory. The technical solution of the embodiment of the present invention realizes high-precision motion control of the tower crane, reduces safety hazards, avoids manual participation in hoisting operations, and truly realizes unmanned hoisting.

[0005] In the first aspect, an embodiment of the present invention provides a control system for a tower crane, comprising: a parameter training module and a trajectory control module; the parameter training module is used to automatically adjust the initial PID parameters according to the trajectory fit between the pre-motion trajectory and the planned trajectory of the tower crane hook, so as to obtain the adjusted PID parameters of the control system, the pre-motion trajectory being the motion trajectory obtained when the hook is controlled to move toward a target point according to the initial PID parameters and the planned trajectory; the trajectory control module is used to control the hook to move toward the target point according to the adjusted PID parameters and the planned trajectory.

[0006] From the above, according to the trajectory fit between the pre-motion trajectory of the hook and the planned trajectory, the initial PID parameters are automatically adjusted to obtain the adjusted PID parameters of the control system, and according to the initial PID parameters or the adjusted PID parameters and the planned trajectory, the hook is controlled to move toward the target point. The technical solution of the embodiment of the present invention realizes high-precision motion control of the tower crane, reduces safety hazards, avoids manual participation in hoisting operations, and truly realizes unmanned hoisting.

[0007] In a possible implementation of the first aspect, the adjusted PID parameters include process PID parameters and deceleration PID parameters; the process PID parameters are used to control the hook to move from the first planned trajectory point to the nth last planned trajectory point, and the deceleration PID parameters are used to control the hook to move from the nth last planned trajectory point to the target point and make the speed of the hook when it reaches the target point 0. In some embodiments, the nth planned trajectory point is the second to last trajectory point.

[0008] As described above, the tower crane hook is controlled to move to the target point through the process PID parameters and the deceleration PID parameters, and the speed when reaching the target point is 0. The technical solution of the embodiment of the present invention realizes higher-precision motion control of the tower crane and further reduces safety hazards.

[0009] In a possible implementation of the first aspect, the trajectory fitting degree is a coordinate fitting degree between the planned trajectory and the pre-motion trajectory in the tower crane axis space.

[0010] From the above, the trajectory fitting degree is the coordinate fitting degree of the tower crane axis space, so that the PID parameters generated based on it can better control the movement of each axis of the tower crane, thereby more accurately controlling the movement of the hook.

[0011] In a possible implementation of the first aspect, the process of obtaining the coordinate fitting degree includes: taking the axis space coordinates of one axis of the tower crane as the independent variable and the axis space coordinates of other axes of the tower crane as the dependent variable, and calculating the fitting degree between the dependent variables of the pre-motion trajectory and the planned trajectory.

[0012] From the above, the trajectory fitting problem of the trajectory composed of discrete data is solved by setting the independent variables and dependent variables.

[0013] In a possible implementation of the first aspect, when the parameter training module automatically adjusts the initial PID parameters according to the trajectory fit, the convergence target of the adjustment is set to at least include: the mean of the position deviation is lower than the first threshold, the amplitude of the position deviation is lower than the second threshold, and the time for the position deviation to converge to the third threshold is less than the fourth threshold, wherein the second threshold is greater than the first threshold, and the first threshold is greater than the third threshold, and the position deviation is the deviation between the simulated trajectory of the hook and the planned trajectory in the tower crane axis space during the automatic adjustment process.

[0014] From the above, PID parameter training is performed based on various convergence targets, so that the modulated PID parameters can adjust the motion trajectory accurately, converge quickly and react quickly.

[0015] In a possible implementation manner of the first aspect, a control system of a tower crane further includes: a position acquisition module, configured to acquire actual positions of the axes of the tower crane during movement of the hook through an encoder of the tower crane.

[0016] From the above, by collecting the actual positions of the axes of the tower crane during the hook movement, it not only provides samples for parameter training, but also facilitates monitoring the gap between the actual trajectory and the planned trajectory.

[0017] In a possible implementation of the first aspect, a control system of a tower crane also includes: a human-machine interface module and a trajectory planning module, the human-machine interface module is used to set the initial PID parameters and display the actual position, and the trajectory planning module is used to generate the planned trajectory; when generating the pre-motion trajectory, the human-machine interface module transmits the initial PID parameters to the trajectory control module, the trajectory planning module transmits the planned trajectory to the trajectory control module, and the position acquisition module transmits the actual position to the parameter training module; when adjusting the initial PID parameters, the human-machine interface module transmits the initial PID parameters to the parameter training module, and the trajectory planning module transmits the planned trajectory to the trajectory control module; when performing trajectory control on the hook, the parameter training module transmits the adjusted PID parameters to the trajectory control module, the trajectory planning module transmits the planned trajectory to the trajectory control module, and the position acquisition module transmits the actual position to the human-machine interface module.

[0018] From the above, by adding the trajectory planning module and the human-machine interface module, the motion trajectory of the tower crane hook is fully controlled, including trajectory planning, pre-motion, PID parameter adjustment, trajectory control and trajectory display.

[0019] In a possible implementation of the first aspect, a control system of a tower crane also includes: a real-time system, a non-real-time system and a virtual PLC controller; the parameter training module, the trajectory planning module and the human-machine interface module are deployed on the non-real-time system, the trajectory control module and the position acquisition module are deployed on the virtual PLC controller, and the virtual PLC controller runs on the real-time system; the real-time system and the non-real-time system exchange data through a virtual bus, and the virtual bus includes a bus based on shared memory address abstraction.

[0020] From the above, the trajectory planning and parameter training with large amount of calculation are realized through the non-real-time system, and the control instructions are generated in real time through the real-time system and the virtual PCL controller to control the movement of the tower crane and obtain the position of each axis in real time, thereby improving the real-time performance of the trajectory control on the basis of improving the accuracy of the tower crane control.

[0021] In a second aspect, an embodiment of the present invention provides a tower crane control method, comprising:

[0022] The initial PID parameters of the tower crane control system are set, and the hook is controlled to move toward the target point according to the initial PID parameters and the planned trajectory of the tower crane hook, and the axis space coordinates of each axis of the tower crane are collected through the encoder to obtain the pre-motion trajectory of the hook. According to the trajectory fit between the pre-motion trajectory and the planned trajectory, the initial PID parameters are automatically adjusted to obtain the adjusted PID parameters of the control system; according to the adjusted PID parameters and the planned trajectory, the hook is controlled to move toward the target point.

[0023] From the above, according to the trajectory fit between the pre-motion trajectory of the hook and the planned trajectory, the initial PID parameters are automatically adjusted to obtain the adjusted PID parameters of the control system, and according to the initial PID parameters or the adjusted PID parameters and the planned trajectory, the hook is controlled to move toward the target point. The technical solution of the embodiment of the present invention realizes high-precision motion control of the tower crane, reduces safety hazards, avoids manual participation in hoisting operations, and truly realizes unmanned hoisting.

[0024] In a possible implementation of the second aspect, the adjusted PID parameters include process PID parameters and deceleration PID parameters; the process PID parameters are used to control the hook to move from the first planned trajectory point to the nth last planned trajectory point, and the deceleration PID parameters are used to control the hook to move from the nth last planned trajectory point to the target point and make the speed of the hook when it reaches the target point 0. In some embodiments, the nth planned trajectory point is the second to last trajectory point.

[0025] As described above, the tower crane hook is controlled to move to the target point through the process PID parameters and the deceleration PID parameters, and the speed when reaching the target point is 0. The technical solution of the embodiment of the present invention realizes higher-precision motion control of the tower crane and further reduces safety hazards.

[0026] In a possible implementation of the second aspect, the trajectory fitting degree is a coordinate fitting degree between the planned trajectory and the pre-motion trajectory in the tower crane axis space.

[0027] From the above, the trajectory fitting degree is the coordinate fitting degree of the tower crane axis space, so that the PID parameters generated based on it can better control the movement of each axis of the tower crane, thereby more accurately controlling the movement of the hook.

[0028] In a possible implementation of the second aspect, the process of obtaining the coordinate fitting degree includes: taking the axis space coordinates of one axis of the tower crane as the independent variable, the axis space coordinates of other axes of the tower crane as the dependent variable, and calculating the fitting degree between the dependent variables of the pre-motion trajectory and the planned trajectory.

[0029] From the above, the trajectory fitting problem of the trajectory composed of discrete data is solved by setting the independent variables and dependent variables.

[0030] In a possible implementation of the second aspect, when the initial PID parameters are automatically adjusted according to the trajectory fit, the convergence target of the adjustment is set to at least include: the mean of the position deviation is lower than a first threshold, the amplitude of the position deviation is lower than a second threshold, and the time for the position deviation to converge to a third threshold is less than a fourth threshold, wherein the second threshold is greater than the first threshold, and the first threshold is greater than the third threshold, and the position deviation is the deviation between the simulated trajectory of the hook and the planned trajectory in the tower crane axis space during the automatic adjustment process.

[0031] From the above, PID parameter training is performed based on various convergence targets, so that the modulated PID parameters can adjust the motion trajectory accurately, converge quickly and react quickly.

[0032] In a possible implementation manner of the second aspect, a tower crane control method further includes: collecting actual positions of each axis of the tower crane during the movement of the hook through an encoder of the tower crane.

[0033] From the above, by collecting the actual positions of the axes of the tower crane during the hook movement, it not only provides samples for parameter training, but also facilitates monitoring the gap between the actual trajectory and the planned trajectory.

[0034] In a possible implementation of the second aspect, a tower crane control method further includes: obtaining a planned trajectory of the hook, including a position of each planned trajectory point in the tower crane axis space.

[0035] From the above, the planned trajectory is more suitable for trajectory control than a number of discrete path points.

[0036] In a possible implementation of the second aspect, a tower crane control method also includes: performing the parameter training through a non-real-time system to obtain adjusted PID parameters, performing trajectory control through a real-time system and a virtual PLC controller, and the virtual PLC controller runs in the real-time system; the real-time system and the non-real-time system exchange data through a virtual bus, and the virtual bus includes a bus based on shared memory address abstraction.

[0037] From the above, the trajectory planning and parameter training with large amount of calculation are realized through the non-real-time system, and the control instructions are generated in real time through the real-time system and the virtual PCL controller to control the movement of the tower crane and obtain the position of each axis in real time, thereby improving the real-time performance of the trajectory control on the basis of improving the accuracy of the tower crane control.

[0038] In a third aspect, an embodiment of the present invention provides a computing device, comprising: a bus; a communication interface connected to the bus; at least one processor connected to the bus; and at least one memory connected to the bus and storing program instructions, wherein when the program instructions are executed by the at least one processor, the at least one processor executes any implementation described in the first aspect of the present invention.

[0039] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having program instructions stored thereon, wherein when the program instructions are executed by a computer, the computer executes any implementation method described in the first aspect of the application. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1A It is a structural schematic diagram of the application scenarios of various embodiments of the present invention;

[0041] Figure 1B A schematic diagram of a tower crane for application of various embodiments of the present invention;

[0042] Figure 2 It is a structural schematic diagram of a control system embodiment 1 of a tower crane of the present invention;

[0043] Figure 3A It is a schematic diagram of the trajectory difference when the parameter training module of the control system embodiment 1 of a tower crane of the present invention automatically adjusts the PID parameters;

[0044] Figure 3B It is a schematic diagram of the trajectory difference when the parameter training module of the control system embodiment 1 of a tower crane of the present invention automatically adjusts the PID parameters;

[0045] Figure 3C It is a schematic diagram of the trajectory difference when the parameter training module of the control system embodiment 1 of a tower crane of the present invention automatically adjusts the PID parameters;

[0046] Figure 4 It is a schematic diagram of the working process of a control system of a tower crane of the present invention;

[0047] Figure 5 It is a structural schematic diagram of a second embodiment of a tower crane control system of the present invention;

[0048] Figure 6It is a schematic diagram of a data interaction process between a real-time system and a non-real-time system in Embodiment 2 of a tower crane control system of the present invention;

[0049] Figure 7 A schematic diagram of a control method for a tower crane according to an embodiment of the present invention;

[0050] Figure 8 A schematic diagram of the structure of a computing device according to various embodiments of the present invention. DETAILED DESCRIPTION

[0051] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0052] In the following description, the terms "first\second\third, etc." or module A, module B, module C, etc. are only used to distinguish similar objects, or to distinguish different embodiments, and do not represent a specific ordering of the objects. It can be understood that the specific order or sequence can be interchanged where permitted, so that the embodiments of the present invention described here can be implemented in an order other than that illustrated or described here.

[0053] In the following description, the numbers representing the steps, such as S110, S120, etc., do not necessarily mean that the steps must be executed in this manner. If permitted, the order of the previous and next steps can be interchanged, or they can be executed simultaneously.

[0054] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein are only for the purpose of describing the embodiments of the present invention and are not intended to limit the present invention.

[0055] The embodiment of the present invention provides a control system and method for a tower crane, the control system includes a parameter training module and a trajectory control module; the parameter training module is used to automatically adjust the initial PID parameters according to the trajectory fit between the pre-motion trajectory of the tower crane hook and the planned trajectory, and obtain the adjusted PID parameters of the control system, the pre-motion trajectory is the motion trajectory obtained when the tower crane hook is controlled to move toward the target point according to the initial PID parameters and the planned trajectory; the trajectory control module is used to control the hook to move toward the target point according to the adjusted PID parameters and the planned trajectory. The technical solution of the embodiment of the present invention realizes high-precision motion control of the tower crane, reduces safety hazards, avoids manual participation in hoisting operations, and truly realizes unmanned hoisting.

[0056] According to the following Figures 1A to 8 Various embodiments of the present invention are described.

[0057] First combine Figure 1A and Figure 1B The application scenarios and tower cranes of various embodiments of the present invention are introduced.

[0058] Figure 1A The application scenarios of various embodiments of the present invention are shown, which include: a control system, a frequency converter, a motor and an encoder.

[0059] The control system generates control instructions for the frequency converter based on PID parameters and planned trajectories. The control instructions control the movement of the motor through the frequency converter to realize the final movement of the tower crane hook in a three-dimensional space.

[0060] The inverter receives the control command from the control system and controls the speed of the motor. The motor controls the movement of each axis of the tower crane, thereby driving the movement of the hook end in three-dimensional space.

[0061] The encoder is used to collect the coordinates of the actual position of each axis of the tower crane during its movement.

[0062] Figure 1B A tower crane to which various embodiments of the present invention are applied is shown, which comprises, by way of example, a slewing axis, a luffing axis and a height axis, and which is driven by a slewing motor, a luffing motor and a height lifting motor respectively to achieve movement of the hook end in a three-dimensional space.

[0063] Combine the following Figure 2 A control system embodiment 1 of a tower crane according to the present invention is introduced.

[0064] A control system for a tower crane Embodiment 1 Figure 1A The control system includes a parameter training module and a trajectory control module; the parameter training module is used to automatically adjust the initial PID parameters according to the trajectory fit between the pre-motion trajectory of the tower crane hook and the planned trajectory, and obtain the adjusted PID parameters of the control system, the pre-motion trajectory is the motion trajectory obtained when the tower crane hook is controlled to move toward the target point according to the initial PID parameters and the planned trajectory; the trajectory control module is used to control the hook to move toward the target point according to the adjusted PID parameters and the planned trajectory. The technical solution of the embodiment of the present invention realizes high-precision motion control of the tower crane, reduces safety hazards, avoids manual participation in hoisting operations, and truly realizes unmanned hoisting.

[0065] Figure 2 The structure of a first embodiment of a control system for a tower crane is shown, which includes: a trajectory planning module 110 , a position acquisition module 120 , a parameter training module 130 , and a trajectory control module 140 .

[0066] The trajectory planning module 110 is used to obtain the planned trajectory of the tower crane hook, including the coordinates of each planned trajectory point in the tower crane axis space.

[0067] In some embodiments, the working process of the trajectory planning module 110 includes:

[0068] 1) According to the known key points in the planned path of the tower crane hook movement, the planned trajectory of the tower crane hook in Cartesian space is obtained by trajectory interpolation method, wherein the key points include the points in front of the obstacles during the movement of the tower crane hook;

[0069] 2) According to the inverse kinematics process, the coordinates of the tower crane hook in the tower crane axis space are obtained, that is, the axis space of each axis is made into a planned trajectory of the tower crane motor.

[0070] The position acquisition module 120 is used to acquire the coordinates of the actual positions of the axes of the tower crane during the movement of the tower crane through encoders.

[0071] Among them, the coordinates of the actual positions of the axes of the tower crane constitute the motion trajectory of the tower crane hook in the tower crane axis space.

[0072] The parameter training module 130 is used to automatically adjust the initial PID parameters according to the trajectory fit between the pre-motion trajectory and the planned trajectory of the tower crane hook, so as to obtain the adjusted PID parameters of the control system.

[0073] The pre-motion trajectory is the motion trajectory obtained when the tower crane hook is controlled to move toward the target point according to the initial PID parameters and the planned trajectory. The present invention first controls the tower crane according to the initial PID parameters to obtain the motion trajectory of the hook, which is called the pre-operation trajectory. The PID parameters are then adjusted according to the pre-motion trajectory, and no adjustment is made according to the position difference in the subsequent control process.

[0074] The PID parameters include a proportional parameter P, an integral parameter I and a differential parameter D. The initial PID parameters are the values ​​of the proportional parameter P, the integral parameter I and the differential parameter D recommended by the application engineer of the tower crane control system from the experience value library.

[0075] Among them, the trajectory fitting degree is the coordinate fitting degree between the planned trajectory of the tower crane hook and the pre-motion trajectory in the tower crane axis space. Because the planned trajectory points and the pre-motion trajectory points are discrete points and it is difficult to correspond one to one, in some embodiments, the axis space coordinates of one axis of the tower crane are used as independent variables, and the axis space coordinates of the other axes of the tower crane are used as dependent variables to calculate the coordinate fitting degree between the dependent variables of the pre-motion trajectory and the planned trajectory in the tower crane axis space. The specific method is as follows:

[0076] 1) The coordinate of the tower crane axis x1 is taken as the independent variable, and the coordinates of the other two axes x2 and x3 are taken as the dependent variables. The axis x1 is any axis of the tower crane.

[0077] 2) Using each planned trajectory point to fit the coordinates of the two axes x2 and x3 with respect to the coordinates of the axis x1 in the tower crane axis space coordinates, the fitting analytical expressions f1 and f2 are obtained;

[0078] 3) Input the coordinates of axis x1 in the pre-motion trajectory into the fitting coordinates of axes x2 and x3 calculated using f1 and f2 respectively;

[0079] 4) Using the fitting coordinates of axes x2 and x3 and the coordinates of the two axes x2 and x3 of each planned trajectory point, the coordinate fitting degree of the planned trajectory and the pre-motion trajectory in the tower crane axis space is calculated according to the fitting degree formula.

[0080] Usually the control system improves the stability, accuracy and speed of real control by adjusting PID parameters, as follows:

[0081] 1) Stability, that is, when the system is disturbed in the equilibrium state, its controlled quantity must quickly return to the stable state, and the system stability can be improved by adjusting the differential parameter D;

[0082] 2) Accuracy, that is, when the system is in steady state, its steady-state error should be as small as possible, and the proportional parameter P and integral parameter I should be adjusted to improve the steady-state accuracy;

[0083] 3) Rapidity, that is, the system's dynamic response time should be short, which is generally measured by the length of the transition time. The response speed is generally increased by adjusting the proportional parameter P and the differential parameter D, while the response speed is reduced by adjusting I.

[0084] When the parameter training module 130 automatically adjusts the initial PID parameters, it adjusts them in the order of proportional parameter P, integral parameter I, and finally differential parameter D. When the output does not oscillate, the proportional parameter P is adjusted to make the final motion trajectory close to the planned trajectory, the integral time constant I is reduced to speed up the convergence speed, and the differential time constant D is increased to reduce the adjustment time.

[0085] Among them, when the parameter training module 130 automatically adjusts the initial PID parameters, the convergence targets of the adjustment are set to include at least: the mean of the position deviation is lower than the first threshold, the amplitude of the position deviation is lower than the second threshold, the time for the position deviation to converge to the third threshold is less than the fourth threshold, wherein the second threshold is greater than the first threshold, the first threshold is greater than the third threshold, and the position deviation is the deviation between the simulated trajectory of the tower crane hook calculated during the automatic adjustment process and the planned trajectory.

[0086] FIG. 3A to FIG. 3C Three examples of automatically tuning PID parameters for the parameter training module.

[0087] Figure 3A It means that the simulated trajectory and the planned trajectory are never in line, and the position deviation value will never converge, indicating that the proportional parameter P is too small and needs to be increased.

[0088] Figure 3B It means that the simulated trajectory and the planned trajectory are always in an overshoot state, and the position deviation value is always shaking up and down and cannot converge, indicating that the proportional parameter P is over-adjusted and needs to be reduced.

[0089] Figure 3C The simulated trajectory and the planned trajectory will eventually be consistent, but the position deviation value converges too slowly, indicating that the proportional parameter P has been set appropriately and the integral parameter I needs to be reduced.

[0090] The trajectory control module 140 is used to control the tower crane hook to move toward the target point according to the PID parameters and the planned trajectory.

[0091] Among them, when the PID parameters are initial PID parameters, the trajectory control module 140 is used to control the tower crane hook to perform the pre-movement according to the initial PID parameters and the planned trajectory, and provide samples for the parameter training module.

[0092] Among them, when the PID parameters are adjusted PID parameters, the trajectory control module 140 is used to control the motion trajectory of the tower crane hook according to the adjusted PID parameters and the planned trajectory, so that it can accurately reach the target point, and keep the speed, acceleration and jerk of each axis of the tower crane continuous during the movement and meet the kinematic constraints of each axis of the tower crane.

[0093] Combine the following Figure 4 , the working process of this embodiment is summarized, which includes:

[0094] 1) The trajectory planning module 110 and the position acquisition module 120 respectively output the planned trajectory and the pre-motion trajectory of the tower crane hook to the parameter training module 130.

[0095] 2) The parameter training module 130 obtains the trajectory fitting degree according to the planned trajectory and the pre-motion trajectory of the tower crane hook, and adjusts the initial PID parameters accordingly to obtain the adjusted PID parameters.

[0096] 3) The trajectory control module 140 generates motor instructions according to the planned trajectory of the tower crane hook and the adjusted PID parameters, and controls the motor to move toward the target point.

[0097] In summary, a control system embodiment 1 of a tower crane uses a parameter training module to automatically adjust the initial PID parameters according to the trajectory fit between the pre-motion trajectory and the planned trajectory of the tower crane hook to obtain the adjusted PID parameters of the control system, and also uses a trajectory control module to control the hook to move toward the target point according to the adjusted PID parameters and the planned trajectory. The technical solution of this embodiment realizes high-precision motion control of the tower crane, reduces safety hazards, avoids manual participation in hoisting operations, and truly realizes unmanned hoisting.

[0098] A control system embodiment 2 of a tower crane is based on a control system embodiment 1 of a tower crane, and each functional module is implemented based on a heterogeneous system composed of a real-time system and a non-real-time system. The non-real-time system improves the computing power to complete the trajectory planning and parameter training modules. The real-time system provides real-time resources for the trajectory control module to achieve the real-time nature of the trajectory control, and divides the PID parameters output by the parameter training module into process PID parameters and deceleration PID parameters, which not only drives the tower crane hook to the target position but also makes the speed of reaching the target position 0, thereby achieving higher-precision motion control of the tower crane.

[0099] Figure 5 The structure of a second embodiment of a tower crane control system is shown, which includes: a trajectory planning module 210, a position acquisition module 220, a parameter training module 230, a trajectory control module 240, a human-machine interface module 250, a non-real-time system (NonRTOS) 310, a real-time system (RTOS) 320, a virtual PLC controller 330, a controller kernel 340, and a controller hardware 350.

[0100] The non-real-time system 310 has high computing power and can complete trajectory planning and parameter training with large computing volume. For example, the non-real-time system 310 is a Windows system. The trajectory planning module 210, the parameter training module 230 and the human-machine interface module 250 are on the non-real-time system 310.

[0101] The real-time system 320 has independent dedicated resources, and provides a real-time operating environment for the virtual PLC controller 330 , so that the virtual PLC controller 330 can perform real-time control. The virtual PLC controller 330 runs on the real-time system 320 .

[0102] The virtual PLC controller 330 controls the frequency converter of the tower crane in real time through the trajectory control module 240, thereby realizing the three-dimensional motion control of the tower crane hook, and also collects the positions of each axis of the tower crane through the position acquisition module 220 to provide a pre-motion trajectory for the parameter training module 230. The trajectory control module 240 and the position acquisition module 220 are on the virtual PLC controller 330, and the virtual PLC controller 330 runs on the real-time system 320.

[0103] The controller kernel 340 virtualizes the controller hardware 350 and provides kernel resources for the real-time system 320 and the non-real-time system 310. The real-time system 320 and the non-real-time system 310 run on the controller kernel 340, and builds virtual bus interaction data on the virtual kernel. For example, the controller kernel 340 is a Hypervisor, and the virtual bus is a bus abstracted from the shared memory.

[0104] The parameter training module 230 is based on the parameter training module 130 of the first embodiment of a tower crane control system, and the adjusted PID parameters include process PID parameters and deceleration PID parameters; the process PID parameters are used to control the hook to move from the first planned trajectory point to the nth last planned trajectory point; the deceleration PID parameters are used to control the hook to move from the nth last planned trajectory point to the target point and make the speed of the hook 0 when it reaches the target point.

[0105] Among them, the position of the nth point makes the overall movement time of the tower crane hook the shortest while meeting the safety requirements.

[0106] The trajectory control module 240 divides the control process of the trajectory control module 140 of the first embodiment of a tower crane control system into two parts:

[0107] 1) Use process PID parameters to control the hook to move from the first planned trajectory point to the nth last planned trajectory point;

[0108] 2) Use the deceleration PID parameters to control the hook to move from the penultimate n-th planned trajectory point to the target point and make the speed of the hook 0 when it reaches the target point.

[0109] The trajectory planning module 210 and the position acquisition module 220 are the same as the trajectory planning module 110 and the position acquisition module 120 of the first embodiment of a control system for a tower crane, and will not be described in detail here.

[0110] The human-machine interface module 250 is used to input the location of the planning node and set the initial PID parameters, and is also used to display the planned trajectory and the actual trajectory in the Cartesian space and the difference between the two.

[0111] Figure 6 The diagram shows a data interaction process between a real-time system 320 and a non-real-time system 310 .

[0112] 1) The parameter training module 230 of the non-real-time system 310 sends initial PID parameters to the trajectory control module 240 of the real-time system 320, and the trajectory planning module 210 of the non-real-time system 310 sends a planned trajectory to the trajectory control module 240 of the real-time system 320. The trajectory control module 240 of the real-time system 320 controls the movement of the tower crane according to the initial PID parameters and the planned trajectory, and obtains the movement position of each axis of the tower crane, i.e., the pre-motion trajectory, through the position acquisition module 220, and uploads it to the parameter training module 230 of the non-real-time system 310.

[0113] 2) The parameter training module 230 of the non-real-time system 310 sends the process PID parameters to the trajectory control module 240 of the real-time system 320, and the trajectory planning module 210 of the non-real-time system 310 sends the planned trajectory to the trajectory control module 240 of the real-time system 320. The trajectory control module 240 of the real-time system 320 controls the tower crane to move to the nth last planned trajectory point according to the process PID parameters and the planned trajectory, and obtains the movement position of each axis of the tower crane through the position acquisition module 220, that is, the actual trajectory from the first planned trajectory point to the nth last planned trajectory point, and uploads it to the human-machine interface module 250 of the non-real-time system 310.

[0114] 3) The parameter training module 230 of the non-real-time system 310 sends the deceleration PID parameters to the trajectory control module 240 of the real-time system 320, and the trajectory planning module 210 of the non-real-time system 310 sends the planned trajectory to the trajectory control module 240 of the real-time system 320. The trajectory control module 240 of the real-time system 320 controls the tower crane to move from the nth last planned trajectory point to the target point according to the deceleration PID parameters and the planned trajectory, and obtains the movement position of each axis of the tower crane, that is, the actual trajectory from the nth last planned trajectory point to the target point through the position acquisition module 220, and uploads it to the human-machine interface module 250 of the non-real-time system 310.

[0115] It should be emphasized that: in the above process, the real-time system 320 uploads the current PID parameters to the non-real-time system 310 to facilitate the non-real-time system to check.

[0116] In summary, a control system embodiment 2 of a tower crane implements various functional modules based on a heterogeneous system composed of a real-time system and a non-real-time system. The non-real-time system improves the computing power to complete the trajectory planning and parameter training modules. The real-time system provides real-time resources for the trajectory control module to achieve the real-time nature of trajectory control, and divides the PID parameters output by the parameter training module into process PID parameters and deceleration PID parameters, which not only drives the tower crane hook to the target position but also makes the speed of reaching the target position 0, thereby achieving higher-precision motion control of the tower crane.

[0117] Combine the following Figure 7 An embodiment of a tower crane control method is introduced.

[0118] A tower crane control method embodiment uses a tower crane control system embodiment 2 device to control the tower crane. Figure 7 A flow chart of an embodiment of a tower crane control method is shown, which includes steps S710 to S750.

[0119] S710: Obtain the planned trajectory of the tower crane hook according to the input path key points through the planning module 210.

[0120] In some embodiments, a specific implementation of this step includes:

[0121] 1) Obtain the planned trajectory of the tower crane hook in Cartesian space through trajectory interpolation based on the key points in the tower crane hook movement;

[0122] 2) According to the inverse kinematics process, the coordinates of the tower crane hook in the tower crane axis space are obtained, that is, the axis space of each axis is made into a planned trajectory of the tower crane motor.

[0123] S720: Set initial PID parameters, drive the tower crane hook to move toward the target point through the trajectory control module 240, and obtain the pre-motion trajectory through the position acquisition module 220.

[0124] The initial PID parameters are set based on past experience. The pre-motion trajectory is the trajectory of each axis in the tower crane axis space.

[0125] S730: The parameter training module 230 adjusts the PID parameters using the planned trajectory and the pre-motion trajectory to obtain adjusted PID parameters.

[0126] Among them, the adjusted PID parameters include process PID parameters and deceleration PID parameters; the process PID parameters are used to control the hook to move from the first planned trajectory point to the nth to last planned trajectory point, and the deceleration PID parameters are used to control the hook to move from the nth to last planned trajectory point to the target point and make the speed of the hook 0 when it reaches the target point.

[0127] Among them, according to the trajectory fitting degree between the pre-motion trajectory and the planned trajectory of the tower crane hook, the initial PID parameters are automatically adjusted to obtain the adjusted PID parameters of the control system.

[0128] Among them, the trajectory fitting degree is the coordinate fitting degree between the planned trajectory of the tower crane hook and the pre-motion trajectory in the tower crane axis space. Because the planned trajectory points and the pre-motion trajectory points are discrete points and it is difficult to correspond one to one, in some embodiments, the axis space coordinates of one axis of the tower crane are used as independent variables, and the axis space coordinates of the other axes of the tower crane are used as dependent variables to calculate the coordinate fitting degree between the dependent variables of the pre-motion trajectory and the planned trajectory in the tower crane axis space. The specific method is as follows:

[0129] 1) The coordinate of the tower crane axis x1 is taken as the independent variable, and the coordinates of the other two axes x2 and x3 are taken as the dependent variables. The axis x1 is any axis of the tower crane.

[0130] 2) Using each planned trajectory point to fit the coordinates of the two axes x2 and x3 with respect to the coordinates of the axis x1 in the tower crane axis space coordinates, the fitting analytical expressions f1 and f2 are obtained;

[0131] 3) Input the coordinates of axis x1 in the pre-motion trajectory into the fitting coordinates of axes x2 and x3 calculated using f1 and f2 respectively;

[0132] 4) Using the fitting coordinates of axes x2 and x3 and the coordinates of the two axes x2 and x3 of each planned trajectory point, the coordinate fitting degree of the planned trajectory and the pre-motion trajectory in the tower crane axis space is calculated according to the fitting degree formula.

[0133] Among them, when automatically adjusting the initial PID parameters, the convergence targets of the adjustment are set to include at least: the mean of the position deviation is lower than the first threshold, the amplitude of the position deviation is lower than the second threshold, the time for the position deviation to converge to the third threshold is less than the fourth threshold, wherein the second threshold is greater than the first threshold, the first threshold is greater than the third threshold, and the position deviation is the deviation between the simulated trajectory of the tower crane hook calculated during the automatic adjustment process and the planned trajectory.

[0134] S740: The trajectory control module 240 uses the planned trajectory and process PID parameters to control the hook to move from the first planned trajectory point to the nth last planned trajectory point.

[0135] In the movement process of this step, the position acquisition module 220 acquires the position of each axis of the tower crane in real time, so as to obtain the three-dimensional movement trajectory of the tower crane hook.

[0136] S750: The trajectory control module 240 uses the planned trajectory and the deceleration PID parameters to control the hook to move from the nth last planned trajectory point to the target point and make the speed of the hook 0 when it reaches the target point.

[0137] In the movement process of this step, the position acquisition module 220 is also used to obtain the positions of the axes of the tower crane in real time, so as to obtain the three-dimensional movement trajectory of the tower crane hook.

[0138] The embodiment of the present invention further provides a computing device, Figure 8 Detailed introduction.

[0139] The computing device 800 includes a processor 810 , a memory 820 , a communication interface 830 , and a bus 840 .

[0140] It should be understood that the communication interface 830 in the computing device 800 shown in this figure can be used to communicate with other devices.

[0141] The processor 810 may be connected to a memory 820. The memory 820 may be used to store the program code and data. Therefore, the memory 820 may be a storage unit inside the processor 810, or an external storage unit independent of the processor 810, or a component including a storage unit inside the processor 810 and an external storage unit independent of the processor 810.

[0142] Optionally, the computing device 800 may further include a bus 840. The memory 820 and the communication interface 830 may be connected to the processor 810 via the bus 840. The bus 840 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus 840 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the figure is represented by only one line, but it does not mean that there is only one bus or one type of bus.

[0143] It should be understood that in the embodiment of the present invention, the processor 810 may adopt a central processing unit (CPU). The processor may also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. Alternatively, the processor 810 may adopt one or more integrated circuits to execute relevant programs to implement the technical solutions provided by the controller embodiments of the present invention.

[0144] The memory 820 may include a read-only memory and a random access memory, and provides instructions and data to the processor 810. A portion of the processor 810 may also include a nonvolatile random access memory. For example, the processor 810 may also store information on the device type.

[0145] When the computing device 800 is running, the processor 810 executes the computer execution instructions in the memory 820 to implement the technical solutions provided by the various controller embodiments of the present invention.

[0146] It should be understood that the computing device 800 according to an embodiment of the present invention can correspond to the corresponding subjects in the methods according to the various embodiments of the present invention, and the above-mentioned and other operations and / or functions of each module in the computing device 800 are respectively for implementing the corresponding processes of each method of the present embodiment. For the sake of brevity, they will not be repeated here.

[0147] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0148] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0149] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0150] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0151] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0152] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0153] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, it is used to implement the technical solutions provided by the various controller embodiments of the present invention.

[0154] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include, an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0155] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0156] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0157] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0158] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may also include more other equivalent embodiments without departing from the concept of the present invention, all of which belong to the scope of protection of the present invention.

Claims

1. A control system for a tower crane, characterized in that: include: Parameter training module and trajectory control module; The parameter training module is used to automatically adjust the initial PID parameters according to the trajectory fit between the pre-motion trajectory and the planned trajectory of the tower crane hook, and obtain the adjusted PID parameters of the control system, wherein the pre-motion trajectory is the motion trajectory obtained when the hook is controlled to move toward the target point according to the initial PID parameters and the planned trajectory, and the adjusted convergence target includes at least: the mean value of the position deviation is lower than the first threshold, the amplitude of the position deviation is lower than the second threshold, and the time for the position deviation to converge to the third threshold is less than the fourth threshold, wherein the second threshold is greater than the first threshold, and the first threshold is greater than the third threshold, and the position deviation is the deviation between the simulated trajectory of the hook and the planned trajectory in the tower crane axis space during the automatic adjustment process; The trajectory control module is used to control the hook to move toward the target point according to the adjusted PID parameters and the planned trajectory.

2. The system according to claim 1, characterized in that: The adjusted PID parameters include process PID parameters and deceleration PID parameters; The process PID parameters are used to control the hook to move from the first planned trajectory point to the nth last planned trajectory point, and the deceleration PID parameters are used to control the hook to move from the nth last planned trajectory point to the target point and make the speed of the hook 0 when it reaches the target point.

3. The system according to claim 1, characterized in that: The trajectory fitting degree is the coordinate fitting degree between the planned trajectory and the pre-motion trajectory in the tower crane axis space.

4. The system according to claim 3, characterized in that: The process of obtaining the coordinate fitting degree includes: taking the axis space coordinate of one axis of the tower crane as an independent variable and the axis space coordinates of other axes of the tower crane as dependent variables, and calculating the fitting degree between the dependent variables of the pre-motion trajectory and the planned trajectory.

5. The system according to any one of claims 1 to 4, characterized in that: Also includes: The position acquisition module is used to acquire the actual position of each axis of the tower crane during the movement of the hook through the encoder of the tower crane.

6. The system according to claim 5, characterized in that: Also includes: A human-machine interface module and a trajectory planning module, wherein the human-machine interface module is used to set the initial PID parameters and display the actual position, and the trajectory planning module is used to generate the planned trajectory; When generating the pre-motion trajectory, the human-machine interface module transmits the initial PID parameters to the trajectory control module, the trajectory planning module transmits the planned trajectory to the trajectory control module, and the position acquisition module transmits the actual position to the parameter training module; When adjusting the initial PID parameters, the human-machine interface module transmits the initial PID parameters to the parameter training module, and the trajectory planning module transmits the planned trajectory to the trajectory control module; When the hook is subjected to trajectory control, the parameter training module transmits the adjusted PID parameters to the trajectory control module, the trajectory planning module transmits the planned trajectory to the trajectory control module, and the position acquisition module transmits the actual position to the human-machine interface module.

7. The system according to claim 6, characterized in that: Also includes: Real-time systems, non-real-time systems and virtual PLC controllers; The parameter training module, the trajectory planning module and the human-machine interface module are deployed on a non-real-time system, the trajectory control module and the position acquisition module are deployed on the virtual PLC controller, and the virtual PLC controller runs on a real-time system; The real-time system and the non-real-time system exchange data via a virtual bus, and the virtual bus includes a bus abstracted based on a shared memory address.

8. A tower crane control method, characterized in that: include: Setting the initial PID parameters of the control system of the tower crane, controlling the hook to move toward the target point according to the initial PID parameters and the planned trajectory of the tower crane hook, and acquiring the axis space coordinates of each axis of the tower crane through an encoder to obtain a pre-motion trajectory of the hook; According to the trajectory fit between the pre-motion trajectory and the planned trajectory, the initial PID parameters are automatically adjusted to obtain the adjusted PID parameters of the control system, and the convergence targets of the adjustment include at least: the mean value of the position deviation is lower than the first threshold, the amplitude of the position deviation is lower than the second threshold, and the time for the position deviation to converge to the third threshold is less than the fourth threshold, wherein the second threshold is greater than the first threshold, and the first threshold is greater than the third threshold, and the position deviation is the deviation between the simulated trajectory of the hook and the planned trajectory in the tower crane axis space during the automatic adjustment process; According to the adjusted PID parameters and the planned trajectory, the hook is controlled to move toward the target point.

9. The method according to claim 8, characterized in that: The adjusted PID parameters include process PID parameters and deceleration PID parameters; The process PID parameters are used to control the hook to move from the first planned trajectory point to the nth last planned trajectory point, and the deceleration PID parameters are used to control the hook to move from the nth last planned trajectory point to the target point and make the speed of the hook 0 when it reaches the target point.

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