Automatic stereoscopic warehouse stacker operation control method and system

Abstract

The invention relates to the technical field of automatic control, in particular to an automatic stereoscopic warehouse stacking machine operation control method and system. The method comprises the following steps: firstly, analyzing cargo loading mass change of a stacking machine at each path monitoring point, and obtaining stacking offset sub-parameters; further analyzing the curvature curve of the transportation path to obtain the transportation complexity of the stacking machine at each path monitoring point; analyzing and acquiring a speed deviation index of the stacking machine at the current path monitoring point in combination with the change condition of the transportation speed at the path monitoring points of all historical paths; acquiring a speed adjusting parameter of the stacker at the current path monitoring point; and the transportation speed of the stacking machine is controlled according to the speed adjusting parameters. The operation stability of the stacking machine in the current transportation process is comprehensively evaluated by analyzing the stacking stability condition, the path complexity condition and the transportation speed change condition in the historical path of the stacking machine, the transportation speed of the stacking machine is further adjusted and controlled, and therefore the transportation stability of the stacking machine is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic control, and particularly relates to a method and system for controlling the operation of a stacker crane in an automated storage and retrieval system (AS / RS). Background Art

[0002] An automated storage and retrieval system (AS / RS) is an important part of a modern logistics system. By means of an efficient storage and retrieval mechanism, it improves the space utilization rate and operation efficiency of the warehouse. A stacker crane is the core of the conveying system in an automated storage and retrieval system. It realizes the automatic inbound and outbound of goods by receiving scheduling instructions. Therefore, the operation control of the stacker crane is crucial. During the operation control process of the stacker crane, the stacker crane needs to adjust the transportation speed according to different conveying tasks to maintain stability while running at high speed.

[0003] The traditional way to adjust the transportation speed is mainly the multi-segment speed control method, that is, the set transportation speed of the stacker crane is inconsistent in different sections. It accelerates appropriately under simple road conditions to improve the conveying efficiency; it decelerates appropriately under complex road conditions such as curves to ensure the smoothness of the conveying process. However, in practical applications, this method may cause the acceleration to change suddenly when the stacker crane switches between different speed segments, which will have a greater impact on the stacker crane and the goods it carries, affecting the equipment stability and service life, and even causing the goods to fall, resulting in poor running stability of the stacker crane. Summary of the Invention

[0004] In order to solve the technical problem that the existing technology has poor control over the transportation speed of the stacker crane in an automated storage and retrieval system, which leads to poor running stability of the stacker crane, the purpose of the present invention is to provide a method and system for controlling the operation of a stacker crane in an automated storage and retrieval system. The specific technical solutions adopted are as follows: The present invention proposes a method for controlling the operation of a stacker crane in an automated storage and retrieval system, the method comprising: In the current transportation task of the stacker crane in the automated storage and retrieval system, obtain the curvature curve of the transportation path of the stacker crane, and obtain the load mass and transportation speed of the stacker crane when passing through each path monitoring point on the transportation path; According to the change situation of the load mass at each path monitoring point, obtain the stack offset sub-parameter of the stacker crane at each path monitoring point; according to the position of each path monitoring point in the transportation path, combined with the change situation of the curvature curve, obtain the transportation complexity of the stacker crane at each path monitoring point; at the current path monitoring point, comprehensively consider the change situation of the transportation speed at all historical path monitoring points passed through, combined with the corresponding stack offset sub-parameter and the transportation complexity, to obtain the speed offset index of the stacker crane at the current path monitoring point; At the current path monitoring point, by synthesizing the stack offset sub-parameters at the path monitoring points of all historical paths, combining the stack-borne load information and the speed offset index, obtain the speed adjustment parameter of the stacker; control the transport speed of the stacker according to the speed adjustment parameter.

[0005] Further, the method for obtaining the stack offset sub-parameter includes: At each path monitoring point, according to the mass deviation of the carried load relative to the preset standard mass, obtain the stack instability parameter at each path monitoring point; the mass deviation is positively correlated with the stack instability parameter; According to the mass change rate of the carried load at each path monitoring point, obtain the stack instability weight at each path monitoring point; the mass change rate is negatively correlated with the stack instability weight; Weight the stack instability parameter with the stack instability weight, and use the weighted result as the stack offset sub-parameter at the corresponding path monitoring point.

[0006] Further, the method for obtaining the transport complexity includes: According to the monotonic change of the curvature curve, segment the curvature curve to obtain all curvature segments; According to the concentration characteristics of the curvature derivative in each curvature segment to which each path monitoring point belongs, and the concentration characteristics of the curvature in the adjacent next curvature segment, obtain the complexity parameter; Perform a negative correlation mapping on the spatial distance between the position of each path monitoring point and the position of the corresponding path monitoring point at the end of the curvature segment to which it belongs, and use the negative correlation mapping result as the complexity weight; Weight the complexity parameter with the complexity weight, and use the weighted result as the transport complexity at the corresponding path monitoring point.

[0007] Further, the method for obtaining the curvature segment includes: Derive the curvature curve to obtain the curvature derivative curve; in the curvature derivative curve, take the point where the curvature derivative is 0 and the curvature derivatives before and after are of different signs as the segmentation point of the curvature curve; use all segmentation points to obtain all curvature segments of the curvature curve.

[0008] Further, the method for obtaining the complexity parameter includes: In each curvature segment to which each path monitoring point belongs, normalize the mean value of the curvature derivatives of all curvatures as the first complexity parameter; in each curvature segment to which each path monitoring point belongs, take the mean value of all curvatures as the second complexity parameter; take the product of the first complexity parameter and the second complexity parameter as the complexity parameter.

[0009] Further, the method for obtaining the speed offset index includes: Taking the product of the rate of change of the transportation speed, the stacking offset sub-parameter, and the transportation complexity at the path monitoring point of each historical path as the offset sub-parameter at the path monitoring point of each historical path; comprehensively obtaining the first offset parameter based on the offset sub-parameters at the path monitoring points of all historical paths; Taking the variance of the transportation speed at the path monitoring points of all historical paths as the second offset parameter; Obtaining the speed offset index based on the first offset parameter and the second offset parameter, and both the first offset parameter and the second offset parameter are positively correlated with the speed offset index.

[0010] Further, the method for obtaining the speed adjustment parameter includes: Taking the product of the total number of carried items and the total mass of carried items of the stacker in the current transportation task as the inertial instability factor of the stacker; at the current path monitoring point, taking the product of the variance of the stacking offset sub-parameters at the path monitoring points of all historical paths and the inertial instability factor as the stacking offset index; Normalizing the product of the stacking offset index and the speed offset index, and taking the normalized result as the speed adjustment parameter.

[0011] Further, the method for controlling the transportation speed of the stacker according to the speed adjustment parameter includes: Using the Ziegler–Nichols method to obtain the initial P parameter of the PID controller; taking 1 minus the speed adjustment parameter as the parameter adjustment weight; weighting the initial P parameter with the parameter adjustment weight, and taking the weighted result as the corrected P parameter; and based on the corrected P parameter and the PID algorithm, adjusting the transportation speed of the stacker in real time.

[0012] Further, the method for obtaining the curvature curve includes: Obtaining the curvature value at each path monitoring point on the transportation path; using the serial number of the path monitoring point as the horizontal axis parameter and the curvature value as the vertical axis parameter to construct a two-dimensional coordinate system; mapping the curvature values corresponding to all path monitoring points into the two-dimensional coordinate system to fit the curvature curve.

[0013] The present invention also provides an operating control system for a stacker in an automated stereoscopic warehouse, the system includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the method for operating and controlling a stacker in an automated stereoscopic warehouse are implemented.

[0014] The present invention has the following beneficial effects: In the current transportation task of the stacker in the automated stereoscopic warehouse, the curvature curve of the transportation path of the stacker is obtained, and the load mass and transportation speed of the stacker when passing through each path monitoring point on the transportation path are obtained, providing data preparation for subsequent analysis; according to the change of the load mass at each path monitoring point, the stacker offset sub-parameter at each path monitoring point is obtained, and the stacker offset sub-parameter reflects the transportation stability of the stacker when passing through each path monitoring point from the side; according to the position of each path monitoring point in the transportation path and the change of the curvature curve, the transportation complexity of the stacker at each path monitoring point is obtained, and the transportation complexity evaluates the operation stability of the stacker from the perspective of path change; at the current path monitoring point, by comprehensively considering the change of the transportation speed at all the path monitoring points passed through in history, combining the corresponding stacker offset sub-parameters and transportation complexity, the speed offset index of the stacker at the current path monitoring point is obtained, and the speed offset index quantifies the operation stability of the stacker at the current transportation speed under the current path monitoring point; at the current path monitoring point, by comprehensively considering the stacker offset sub-parameters at all the path monitoring points passed through in history, combining the load information of the stacker and the speed offset index, the speed adjustment parameter of the stacker is obtained, and the speed adjustment parameter is used to control the smoothness of the change of the subsequent transportation speed to reduce the poor transportation stability caused by unreasonable transportation speed; finally, the transportation speed of the stacker is controlled according to the speed adjustment parameter. The present invention comprehensively evaluates the operation stability of the stacker in the current transportation process by analyzing the stacking stability, path complexity and transportation speed change in the historical path of the stacker, and further adjusts and controls the transportation speed of the stacker, thereby improving the transportation stability of the stacker. Description of the Drawings

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 It is a flowchart of a method for controlling the operation of a stacker in an automated stereoscopic warehouse provided by an embodiment of the present invention; Figure 2 It is a flowchart of a method for obtaining the transportation complexity provided by an embodiment of the present invention; Figure 3 It is a flowchart of a method for obtaining the speed offset index provided by an embodiment of the present invention. Detailed Embodiments

[0017] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation manner, structure, features and effects of an automated stereoscopic warehouse stacker crane operation control method and system proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0019] The following specifically describes the specific solution of an automated stereoscopic warehouse stacker crane operation control method and system provided by the present invention in conjunction with the accompanying drawings.

[0020] Please refer to Figure 1 , which shows a flowchart of an automated stereoscopic warehouse stacker crane operation control method provided by an embodiment of the present invention, specifically including: Step S1, in the current transportation task of the automated stereoscopic warehouse stacker crane, obtain the curvature curve of the stacker crane transportation path, and obtain the load mass and transportation speed of the stacker crane when passing through each path monitoring point on the transportation path.

[0021] In an embodiment of the present invention, specifically obtain all transportation paths of each stacker crane through the control system of the automated stereoscopic warehouse, and then obtain the curvature curve of each transportation path; address recognition plates are equally spaced on each transportation path, for example, one is set every 1.5 m, and each address recognition plate can be regarded as a path monitoring point in the transportation path. An encoder is installed on the stacker crane to measure the position of the stacker crane in real time; when the stacker crane passes through the address recognition plate, the system automatically calculates and records the current position coordinates of the stacker crane, and then obtains the transportation speed of the stacker crane when passing through each path monitoring point through the motor shaft speed. At the same time, the weight sensor on the load platform of the stacker crane automatically records the load mass on the load platform; by analyzing the operation of the stacker crane, the transportation speed of the stacker crane can be adjusted in real time subsequently, so as to improve the operation stability of the stacker crane.

[0022] It should be noted that the current transportation task of the stacker crane refers to a complete transportation process corresponding to the outbound or inbound of the stacker crane after loading the goods. The specific transportation duration, transportation speed and transportation route are all planned and scheduled by the control system of the automated stereoscopic warehouse. The methods of obtaining the position coordinates through the encoder and obtaining the transportation speed through the motor shaft speed are all existing technologies and will not be elaborated herein.

[0023] It should be noted that the transportation path of the current transportation task may also include the transportation of the stacker close to the ground and the lifting and lowering transportation to the corresponding warehouse position. The embodiment of the present invention takes into account that the stacker generally performs uniform linear motion when lifting and falling, and the operation is relatively stable, so only the complex road conditions involved in the ground transportation of the stacker are analyzed and adjusted.

[0024] Preferably, in one embodiment of the present invention, considering that the transportation path may have complex situations such as bends, the curvature information at each path monitoring point can be calculated to obtain the curvature curve of the transportation path. Different curvatures correspond to different path complexities, so that the transportation complexity of the stacker can be obtained in combination with the curvature later. Therefore, the method for obtaining the curvature curve includes: Obtain the curvature value at each path monitoring point on the transport path; construct a two-dimensional coordinate system with the sequence number of the path monitoring point as the horizontal axis parameter and the curvature value as the vertical axis parameter; map the curvature values ​​corresponding to all path monitoring points to the two-dimensional coordinate system to fit the curvature curve.

[0025] It should be noted that the acquisition of curvature and the fitting of curvature curves are both existing technologies well known to those skilled in the art and will not be elaborated herein.

[0026] Step S2, according to the change of the load mass at each path monitoring point, obtain the stacking offset sub-parameter of the stacker at each path monitoring point; according to the position of each path monitoring point in the transportation path, combined with the change of the curvature curve, obtain the transportation complexity of the stacker at each path monitoring point; at the current path monitoring point, comprehensively consider the change of the transportation speed at the path monitoring points of all historical routes, combined with the corresponding stacking offset sub-parameter and transportation complexity, and obtain the speed offset index of the stacker at the current path monitoring point.

[0027] Considering that when the goods on the stacker's loading platform are stacked more, higher or irregularly, the stability during transportation is worse, and the center of gravity of the goods is more likely to shift due to the influence of acceleration and deceleration, inertia and complex road conditions, which in turn causes the mass of the load on the loading platform to change. The more drastic the change, the greater the possibility of stacking offset of the stacker, which indirectly indicates that the current transportation stability of the stacker is worse. Therefore, the embodiment of the present invention first obtains the stacking offset sub-parameter of the stacker at each path monitoring point according to the change of the load mass at each path monitoring point; the stacking offset sub-parameter indirectly reflects the transportation stability of the stacker when passing through each path monitoring point. The larger the stacking offset sub-parameter, the worse the transportation stability.

[0028] Preferably, in an embodiment of the present invention, considering that the mass of the goods loaded by the stacker at the start of the current transportation task is usually a standard fixed value, the greater the difference between the load mass collected at each path monitoring point during transportation and the standard fixed value, the worse the stacking stability; also considering that the smaller the mass change rate of the load mass, the greater the possibility that the current change in the load mass is caused by the offset of the stacking center of gravity, and the higher the confidence level for evaluating the stacking stability; therefore, the method for obtaining the stacking offset sub-parameter includes: At each path monitoring point, according to the mass deviation of the load mass relative to the preset standard mass, obtain the stacking instability parameter at each path monitoring point; the mass deviation is positively correlated with the stacking instability parameter; According to the mass change rate of the load mass at each path monitoring point, obtain the stacking instability weight at each path monitoring point; the mass change rate is negatively correlated with the stacking instability weight; Use the stacking instability weight to weight the stacking instability parameter, and take the weighted result as the stacking offset sub-parameter at the corresponding path monitoring point.

[0029] As an example, the calculation formula for the stacking offset sub-parameter is: ; where is the stacking offset sub-parameter of the stacker at the th path monitoring point; is the load mass collected by the stacker at the th path monitoring point; is the preset standard mass; is the mass change rate of the load mass of the stacker at the th path monitoring point; is the preset normal constant; is the stacking instability parameter of the stacker at the th path monitoring point; is the stacking instability weight of the stacker at the th path monitoring point.

[0030] Among them, the method for obtaining the mass change rate is: taking the serial number of each path monitoring point as the horizontal axis parameter and the corresponding load mass as the vertical axis parameter, constructing data points and mapping them to a two-dimensional coordinate system, fitting the load mass change curve corresponding to the load mass collected at all path monitoring points passed through based on the least squares method, and taking the derivative at each path monitoring point on the load mass change curve as the corresponding mass change rate; in other examples, the mass change rate can also be directly calculated using the calculation formula of the data change rate, and both the derivative method and it are well-known techniques in the art and will not be elaborated here.

[0031] It should be noted that in the calculation formula of the stacking offset sub-parameter, the preset standard mass is the total mass of the goods loaded by the stacker at the transportation starting point in the current transportation task, which is a standard fixed value; while the load mass is collected by the weight sensor and may change; the preset normal constant is specifically taken as 0.01 to avoid the denominator being 0 without affecting the calculation result and ensure the fraction is meaningful. The implementer can also set it by himself or use other negatively correlated mapping means, such as taking the mass change rate as the exponential function with the natural constant e as the base. The x in

[0032] Considering that in the current transportation task, the stacker travels back and forth between different shelves in the stereoscopic warehouse and may pass through multiple curved corner areas. When passing through these areas, it is necessary to appropriately change the speed to ensure the stability of the goods on the stacker's loading platform; also considering that when the stacker travels through a curve, when approaching the curve, the curvature of the path usually increases first and then decreases, and the transportation complexity at this time is relatively high. At the same time, to avoid the stacker getting out of control due to centripetal force, the speed is usually appropriately reduced; then when approaching to leave the curve, the path curvature usually gradually decreases, and the transportation complexity at this time is relatively low, and the speed will be appropriately increased to improve the transportation efficiency; therefore, in different curve conditions, the transportation complexity of the stacker is not the same. Therefore, in the embodiment of the present invention, according to the position of each path monitoring point in the transportation path and in combination with the change of the curvature curve, the transportation complexity of the stacker at each path monitoring point is obtained; the transportation complexity evaluates the running stability of the stacker from the perspective of path change.

[0033] It should be noted that the curved corner area targeted in the embodiment of the present invention is a U-shaped running path.

[0034] Preferably, in an embodiment of the present invention, the method for obtaining the transportation complexity includes: Please refer to Figure 2 , which shows a flowchart of a method for obtaining the transportation complexity provided by an embodiment of the present invention, specifically including: Step S201, segment the curvature curve according to the monotonic change of the curvature curve to obtain all curvature segments.

[0035] Considering that the curvature at different positions in the transportation path is not the same, and the path complexity is also not the same. Therefore, in an embodiment of the present invention, the curvature curve is first segmented according to the monotonic change of the curvature curve to obtain all curvature segments; among them, the monotonic change of the curvature curve can be roughly divided into three situations, including monotonically increasing, monotonically decreasing, and monotonically unchanged; also considering that the derivative can reflect the monotonic change of the curvature; therefore, in a preferred embodiment of the present invention, the method for obtaining the curvature segments includes: Derive the curvature curve to obtain the curvature derivative curve; in the curvature derivative curve, take the points corresponding to the curvature values where the curvature derivative is 0 and the curvature derivatives before and after are of different signs as the segmentation points of the curvature curve; use all the segmentation points to obtain all the curvature segments of the curvature curve.

[0036] When the curvature derivative is 0 and the curvature derivatives before and after are one positive and one negative, it indicates that the change trend of the curvature changes; through the above segmentation method, the curvature segments can be roughly divided into three categories. One is the curvature segment corresponding to the straight-line section when about to enter or having exited the curve, which is also the curvature segment with a monotonically unchanged curvature; one is the curvature segment corresponding to the first half of the curve, which is also the curvature segment with a monotonically increasing curvature when initially entering the curve; one is the curvature segment corresponding to the second half of the curve, which is also the curvature segment with a monotonically decreasing curvature when about to leave the curve; among them, according to common sense analysis, the path complexity of the first half of the curve is the largest, the path complexity of the second half of the curve is the second largest, and the path complexity of the straight-line section is the smallest, and the corresponding transportation complexity is also like this.

[0037] Step S202, obtain the complexity parameter according to the concentration characteristics of the curvature derivative in the curvature segment to which each path monitoring point belongs, and the concentration characteristics of the curvature in the next adjacent curvature segment.

[0038] Considering that the larger the curvature derivative in the curvature segment to which the path monitoring point belongs, the greater the possibility that the curvature is monotonically increasing, then the greater the possibility that the path monitoring point is located in the first half of the curve and the greater the transportation complexity; also considering that when the curvature in the next adjacent curvature segment is also larger, it further indicates that the possibility that the path monitoring point is located in the first half of the curve is greater and the transportation complexity is greater.

[0039] In a preferred embodiment of the present invention, the method for obtaining the complexity parameter includes: In the curvature segment to which each path monitoring point belongs, normalize the mean value of the curvature derivatives of all curvatures as the first complexity parameter; in the curvature segment to which each path monitoring point belongs, take the mean value of all curvatures as the second complexity parameter; take the product of the first complexity parameter and the second complexity parameter as the complexity parameter.

[0040] The calculation formula of the complexity parameter is: ; where is the complexity parameter of the stacker at the th path monitoring point; is the S-shaped function; is the mean value of the curvature derivatives in the curvature segment to which the stacker at the th path monitoring point belongs; is the mean value of the curvatures in the next adjacent curvature segment of the curvature segment to which the stacker at the th path monitoring point belongs.

[0041] In the calculation formula of the complexity parameter, specifically, the function normalizes the average value of the curvature derivative in the curvature segment to which the path monitoring point belongs to obtain the first complexity parameter; the larger the average value of the curvature derivative and the larger it is, the larger the normalized value, the greater the possibility of being in the first half of the curve, and the greater the complexity parameter; on the contrary, the smaller the average value of the curvature derivative and the smaller it is, the smaller the normalized value, the greater the possibility of being in the second half of the curve, and the smaller the complexity parameter; at the same time, the larger the curvature value in the adjacent next curvature segment, the larger the second complexity parameter, which further indicates that the path monitoring point is more likely to be in the first half of the curve or about to enter the first half of the curve, and the greater the complexity parameter; then multiply and combine the first complexity parameter and the second complexity parameter to obtain the complexity parameter; in other examples, basic mathematical operations such as addition or weighted summation or positive correlation mapping means can also be used to combine the two, which will not be elaborated here.

[0042] Step S203: Perform a negative correlation mapping on the spatial distance between the position of each path monitoring point and the position of the corresponding path monitoring point at the end of the curvature segment to which it belongs, and use the negative correlation mapping result as the complexity weight.

[0043] Considering that whether the path monitoring point is located on a curve or a straight line, when it is about to enter the next section, such as when entering the first half of the curve from a straight line section, entering the second half of the curve from the first half of the curve, or entering a straight line section from the second half of the curve, the stacker needs to change speed appropriately. Then, the closer to the junction point between different sections, the greater the transportation complexity.

[0044] Therefore, as an example, after adding the preset non-zero normal constant 1 to the spatial distance between the position of each path monitoring point and the position of the corresponding path monitoring point at the end of the curvature segment to which it belongs, perform a reciprocal operation to obtain the complexity weight; the complexity weight evaluates the confidence level of transportation complexity from the perspective of the position of each path monitoring point.

[0045] In other examples, the implementer can also use the difference in serial numbers between path monitoring points to approximately replace the spatial distance, or use the spatial distance as the x in the exponential function with the natural constant e as the base to achieve negative correlation mapping, or other negative correlation mapping means can also be used, which will not be elaborated here.

[0046] Step S204: Weight the complexity parameter with the complexity weight, and use the weighted result as the transportation complexity at the corresponding path monitoring point.

[0047] As an example, multiply and combine the complexity weight and the complexity parameter to obtain the weighted result, which is the transportation complexity at the corresponding path monitoring point.

[0048] So far, the transportation complexity at each path monitoring point passed by the stacker crane has been obtained.

[0049] Considering that the goods on the load platform of the stacker crane are usually affected by inertia, that is, when the speed changes faster, the goods are more likely to tilt and fall due to inertia; and considering that when the stacking offset of the goods on the load platform of the stacker crane is more serious and the current transportation complexity is greater, if the change in the transportation speed is still large, the operating stability of the stacker crane will be lower at the corresponding path monitoring point; Therefore, in the embodiment of the present invention, at the current path monitoring point, by comprehensively considering the change in the transportation speed at the path monitoring points of all historical paths passed, and combining the corresponding stacking offset sub-parameters and transportation complexity, the speed offset index of the stacker crane at the current path monitoring point is obtained; The speed offset index combines the stacking offset and path complexity at the path monitoring points of all historical paths from the perspective of transportation speed, and analyzes and quantifies the operating stability of the stacker crane at the current transportation speed under the current path monitoring point.

[0050] Preferably, in an embodiment of the present invention, the method for obtaining the speed offset index includes: Please refer to Figure 3 , which shows a flowchart of a method for obtaining a speed offset index provided by an embodiment of the present invention, specifically including: Step S301, taking the product of the speed change rate, stacking offset sub-parameter, and transportation complexity of the transportation speed at the path monitoring point of each historical path as the offset sub-parameter at the path monitoring point of each historical path; By comprehensively considering the offset sub-parameters at the path monitoring points of all historical paths, the first offset parameter is obtained.

[0051] Considering that under the current path monitoring point, the larger the stacking offset sub-parameters at the path monitoring points of all historical paths and the higher the transportation complexity, it indicates that the stability of the goods at the path monitoring point of this historical path is worse. If the speed change rate of the transportation speed at the path monitoring point of this historical path is also larger at this time, it indicates that the setting of the transportation speed at the path monitoring point of this historical path is unreasonable; Also considering that if the transportation speeds at the path monitoring points of all historical paths are all set unreasonably, it indicates that under the long-term cumulative influence, the operating stability of the current path monitoring point is lower, and the possibility that the current transportation speed is set unreasonably is also greater.

[0052] The first offset parameter comprehensively considers the transportation conditions at the path monitoring points of all historical paths and comprehensively evaluates the unreasonableness of the transportation speed at the current path monitoring point. The larger the first offset parameter, the greater the unreasonableness of the current transportation speed, and the worse the operating stability of the stacker crane.

[0053] As an example, the calculation formula for the first offset parameter is: ; where is the first offset parameter; is the serial number of the path monitoring point along the route; is the total number of path monitoring points along the route, and is also the sequence number of the current path monitoring point; For stacker The rate of change of transport speed at each path monitoring point; For stacker The transport complexity of the transport speed at each path monitoring point; For stacker The stacking offset sub-parameters at each path monitoring point; For stacker The offset sub-parameter at each path monitoring point.

[0054] In other examples, implementers may also combine the speed change rate of the transport speed at the path monitoring point of each historical route, the stacking offset sub-parameter and the transport complexity through basic mathematical operations such as addition or weighted summation or positive correlation mapping, which are not described here.

[0055] Step S302: taking the variance of the transport speed at the path monitoring points of all historical routes as the second offset parameter.

[0056] Considering that the more dramatic the change of the transport speed at the path monitoring points of all historical paths, the lower the operational stability of the stacker, and the variance can reflect the dramatic change of the data, an embodiment of the present invention uses the variance of the transport speed at the path monitoring points of all historical paths as the second offset parameter. The second offset parameter comprehensively considers the changes in the transport speed at the path monitoring points of all paths, and evaluates the unreasonableness of the setting of the transport speed at the current path monitoring point. The larger the second offset parameter, the greater the transport unreasonableness of the current transport speed, and the worse the operational stability of the stacker.

[0057] It should be noted that in other examples, implementers may also use other discrete parameter measurement methods such as standard deviation to measure the severity of changes in transportation speed, which will not be elaborated here.

[0058] Step S303: obtaining a speed offset index according to the first offset parameter and the second offset parameter, wherein the first offset parameter and the second offset parameter are both positively correlated with the speed offset index.

[0059] As an example, the product of the first offset parameter and the second offset parameter is used as the speed offset index; the larger the speed offset index is, the more unreasonable the setting of the transport speed at the current path monitoring point is. In other examples, the implementer can also combine the two by using basic mathematical operations such as addition or weighted summation or positive correlation mapping, which will not be described here.

[0060] Step S3: At the current path monitoring point, comprehensively consider the stacking offset sub-parameters at the path monitoring points of all historical paths, and combine the load information on the stacking machine and the speed offset index to obtain the speed adjustment parameter of the stacking machine; control the transportation speed of the stacking machine according to the speed adjustment parameter.

[0061] Considering that the greater the variation difference between the stacking offset sub-parameters at the path monitoring points of different historical paths, it indicates that at the current path monitoring point, the stacking machine is more likely to have stacking offset under the current stacking method and transportation method, and the running stability of the stacking machine is worse; at the same time, if the speed offset index is also larger, it indicates that the running stability of the current stacking machine is worse; therefore, in the embodiment of the present invention, at the current path monitoring point, comprehensively consider the stacking offset sub-parameters at the path monitoring points of all historical paths, and combine the load information on the stacking machine and the speed offset index to obtain the speed adjustment parameter of the stacking machine. The speed adjustment parameter reflects the running stability of the stacking machine at the current path monitoring point. The larger the speed adjustment parameter, the worse the running stability, and subsequent adjustments to the transportation speed should pay more attention to avoiding large changes to ensure running stability.

[0062] Preferably, in an embodiment of the present invention, the method for obtaining the speed adjustment parameter includes: Take the product of the total number of loads and the total mass of the loads in the current transportation task of the stacking machine as the inertial instability factor of the stacking machine; at the current path monitoring point, take the product of the variance of the stacking offset sub-parameters at the path monitoring points of all historical paths and the inertial instability factor as the speed offset index; after normalizing the product of the speed offset index and the speed offset index, take the normalized result as the speed adjustment parameter.

[0063] The calculation formula for the speed adjustment parameter is: ; where is the speed adjustment parameter of the stacking machine at the current path monitoring point; is the total mass of the loads in the current transportation task of the stacking machine; is the total number of loads in the current transportation task of the stacking machine; is the inertial instability factor of the stacking machine in the current transportation task; is the variance of the stacking offset sub-parameters at the path monitoring points of all historical paths at the current path monitoring point; is the speed offset index of the stacking machine at the current path monitoring point; is the standard normalization function.

[0064] In the calculation formula of the speed adjustment parameter, linear normalization is specifically used for normalization, and other normalization means can also be adopted, which will not be elaborated here; the greater the total number of carried objects and the total mass of the carried objects, the greater the inertial instability factor of the stacker crane, and the more likely it is to fall due to inertia during speed change, resulting in unstable stacking and the worse the running stability of the stacker crane; the greater the variance of the stacking offset sub-parameters at the path monitoring points of all historical paths, the more likely it is to have stacking offset at the current path monitoring point, and the worse the running stability of the stacker crane; the greater the speed offset index, the more unreasonable the current transportation speed of the stacker crane, and the worse the running stability of the stacker crane.

[0065] After obtaining the speed adjustment parameter of the stacker crane at the current path monitoring point, the transportation speed of the stacker crane can be controlled according to the speed adjustment parameter.

[0066] Preferably, in an embodiment of the present invention, considering that the PID control method is a commonly used control method and is overly stable, the transportation speed can be further adjusted in real time based on the PID control algorithm; the method for controlling the transportation speed of the stacker crane according to the speed adjustment parameter includes: Using the Ziegler–Nichols method to obtain the initial P parameter of the PID controller; subtracting the speed adjustment parameter from the constant 1 as the parameter adjustment weight; weighting the initial P parameter with the parameter adjustment weight, and taking the weighted result as the corrected P parameter; adjusting the transportation speed of the stacker crane in real time based on the corrected P parameter and the PID algorithm.

[0067] It should be noted that the initial P parameter refers to the proportional gain parameter in the PID control algorithm. The difference obtained by subtracting the speed adjustment parameter from the constant 1 is used as the parameter adjustment weight of the proportional gain parameter. When the speed adjustment parameter is larger, the running stability of the stacker crane at the current path monitoring point is worse, and the subsequent transportation speed change should be appropriately smoothed. By adjusting the initial P parameter, that is, the proportional gain parameter, the adjustment process can be made smoother and more stable; at the same time, the integral gain parameter I and the derivative gain parameter D of the PID controller are obtained by using the Ziegler–Nichols method, and then the corrected P parameter, the integral gain parameter I and the derivative gain parameter D are comprehensively used to adjust the transportation speed of the stacker crane in real time to improve the running stability while improving the transportation efficiency.

[0068] It should be noted that the Ziegler–Nichols method and the PID algorithm are both well-known existing technologies to those skilled in the art and will not be elaborated here.

[0069] The present invention also provides an operating control system for an automated storage and retrieval machine (AS / RS) stacker. The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of an operating control method for an AS / RS stacker described in steps S1 to S3 are implemented.

[0070] In summary, in the current transportation task of the AS / RS stacker of the present invention, the curvature curve of the stacker's transportation path is obtained, and the load mass and transportation speed of the stacker are obtained when it passes through each path monitoring point on the transportation path. Then, the stack offset sub-parameters of the stacker at each path monitoring point are analyzed and obtained; further, the transportation complexity of the stacker at each path monitoring point is analyzed and obtained; furthermore, in combination with the changes in the transportation speeds at the path monitoring points of all historical paths passed through, the speed offset index of the stacker at the current path monitoring point is analyzed and obtained; and then, the speed adjustment parameter of the stacker is obtained at the current path monitoring point; the transportation speed of the stacker is controlled according to the speed adjustment parameter. The present invention comprehensively evaluates the running stability of the stacker in the current transportation process by analyzing the stack stability, path complexity, and changes in transportation speed in the historical paths of the stacker, and further adjusts and controls the transportation speed of the stacker, thereby improving the transportation stability of the stacker.

[0071] It should be noted that the above sequence of embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0072] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and the key point of each embodiment is to illustrate the differences from other embodiments.

Claims

1. An operating control method for a stacker crane in an automated stereoscopic warehouse, characterized in that, The method includes: In the current transportation task of the stacker crane in the automated stereoscopic warehouse, obtain the curvature curve of the transportation path of the stacker crane, and obtain the load mass and transportation speed when the stacker crane passes through each path monitoring point on the transportation path; According to the change of the load mass at each path monitoring point, obtain the stack offset sub-parameter of the stacker crane at each path monitoring point; according to the position of each path monitoring point in the transportation path, combined with the change of the curvature curve, obtain the transportation complexity of the stacker crane at each path monitoring point; at the current path monitoring point, comprehensively consider the change of the transportation speed at all the path monitoring points passed through in history, combined with the corresponding stack offset sub-parameter and the transportation complexity, obtain the speed offset index of the stacker crane at the current path monitoring point; At the current path monitoring point, comprehensively consider the stack offset sub-parameters at all the path monitoring points passed through in history, combined with the load information of the stacker crane and the speed offset index, obtain the speed adjustment parameter of the stacker crane; control the transportation speed of the stacker crane according to the speed adjustment parameter.

2. The operation control method of a stacker in an automated stereoscopic warehouse according to claim 1, characterized in that The method for obtaining the stack offset sub-parameter includes: At each path monitoring point, according to the mass deviation of the load mass relative to the preset standard mass, obtain the stack instability parameter at each path monitoring point; the mass deviation is positively correlated with the stack instability parameter; According to the mass change rate of the load mass at each path monitoring point, obtain the stack instability weight at each path monitoring point; the mass change rate is negatively correlated with the stack instability weight; Use the stack instability weight to weight the stack instability parameter, and take the weighted result as the stack offset sub-parameter at the corresponding path monitoring point.

3. The operation control method of a stacker in an automated stereoscopic warehouse according to claim 1, wherein, The method for obtaining the transportation complexity includes: According to the monotonic change of the curvature curve, segment the curvature curve to obtain all curvature segments; According to the concentration characteristics of the curvature derivative in the curvature segment to which each path monitoring point belongs, and the concentration characteristics of the curvature in the adjacent next curvature segment, obtain the complexity parameter; Perform a negative correlation mapping on the spatial distance between the position of each path monitoring point and the position of the corresponding path monitoring point at the end of the curvature segment to which it belongs, and take the negative correlation mapping result as the complexity weight; Use the complexity weight to weight the complexity parameter, and take the weighted result as the transportation complexity at the corresponding path monitoring point.

4. The operation control method of a stacker in an automated stereoscopic warehouse according to claim 3, wherein The method for obtaining the curvature segment includes: Derive the curvature curve to obtain the curvature derivative curve; in the curvature derivative curve, take the point where the curvature derivative is 0 and the curvature derivatives before and after are of different signs as the segmentation point of the curvature curve; use all the segmentation points to obtain all the curvature segments of the curvature curve.

5. The operation control method of a stacker in an automated stereoscopic warehouse according to claim 3, characterized in that, The method for obtaining the complexity parameter includes: In the curvature segment to which each path monitoring point belongs, normalize the mean value of the curvature derivatives of all curvatures as the first complexity parameter; in the curvature segment to which each path monitoring point belongs, take the mean value of all curvatures as the second complexity parameter; take the product of the first complexity parameter and the second complexity parameter as the complexity parameter.

6. The operation control method of a stacker in an automated stereoscopic warehouse according to claim 1, characterized in that, The method for obtaining the speed offset index includes: Take the product of the rate of change of the transport speed, the stacking offset sub-parameter, and the transport complexity at the path monitoring point of each historical path as the offset sub-parameter at the path monitoring point of each historical path; comprehensively obtain the first offset parameter from the offset sub-parameters at the path monitoring points of all historical paths. Take the variance of the transport speed at the path monitoring points of all historical paths as the second offset parameter. Obtain a speed offset index based on the first offset parameter and the second offset parameter, and both the first offset parameter and the second offset parameter are positively correlated with the speed offset index.

7. The operation control method of a stacker in an automated stereoscopic warehouse according to claim 1, characterized in that The method for obtaining the speed adjustment parameter includes: Take the product of the total number of loads and the total mass of the loads in the current transport task of the stacker as the inertial instability factor of the stacker; at the current path monitoring point, take the product of the variance of the stacking offset sub-parameters at the path monitoring points of all historical paths and the inertial instability factor as the stacking offset index. After normalizing the product of the stacking offset index and the speed offset index, take the normalized result as the speed adjustment parameter.

8. The operation control method of a stacker crane in an automated stereoscopic warehouse according to claim 1, characterized in that, The method for controlling the transport speed of the stacker according to the speed adjustment parameter includes: Use the Ziegler–Nichols method to obtain the initial P parameter of the PID controller; take 1 minus the speed adjustment parameter as the parameter adjustment weight; weight the initial P parameter with the parameter adjustment weight, and take the weighted result as the corrected P parameter; based on the corrected P parameter and the PID algorithm, adjust the transport speed of the stacker in real time.

9. The operation control method of a stacker in an automated stereoscopic warehouse according to claim 1, wherein The method for obtaining the curvature curve includes: Obtain the curvature value at each path monitoring point on the transport path; construct a two-dimensional coordinate system with the serial number of the path monitoring point as the horizontal axis parameter and the curvature value as the vertical axis parameter; map the curvature values corresponding to all path monitoring points into the two-dimensional coordinate system to fit the curvature curve.

10. An operating control system for a stacker crane in an automated stereoscopic warehouse, characterized in that, The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the method for controlling the operation of a stacker in an automated stereoscopic warehouse according to any one of claims 1 to 9.

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