Loading control method and system of loading machine based on error margin

Abstract

The invention discloses a loading control method and system for a loader based on error margin, and the method comprises the steps: collecting the calibration error and operation error of a sensor, and constructing an error margin model; on the basis of the error margin model, the loading margin is calculated, and the margin space of a loading path is expanded; planning a control path of the loader bucket based on a self-adaptive PID control algorithm, and outputting an actual moving distance of the loader bucket; the position of the loader bucket is monitored in real time through a laser radar, and fine adjustment control or repeated filling operation is triggered. According to the method, modeling and tolerance analysis are carried out on sensor errors in a control strategy, the robustness and reliability of loading actions are improved by establishing an error margin model and introducing a margin compensation strategy in path planning and control output, it is ensured that under the condition that the sensor errors exist, it can still be ensured that a loader completely loads materials into a loaded vehicle, and the loading efficiency is improved. The loading precision of the loader is improved, and the material loss is effectively reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of engineering machinery automation control, and in particular relates to a loading control method and system of a loader based on error margin. Background Art

[0002] The statements herein merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] When loading materials, loaders often rely on angle sensors, position sensors, and distance sensors to obtain information about the current working device status. However, these sensors often have systematic and random errors, such as zero offset, range offset, and temperature drift. These errors can lead to inaccurate position estimation of the loader bucket, resulting in deviations during material delivery, ultimately causing incomplete loading or material spillage.

[0004] The inventors found that the traditional loading control strategy may have the following problems:

[0005] (1) Sensor error superposition: System errors such as sensor zero bias and temperature drift are superimposed on random errors, resulting in bucket position estimation errors, causing incomplete loading or material spillage;

[0006] (2) Lack of error compensation mechanism: Traditional control strategies cannot dynamically adjust path planning within the error boundary and have poor fault tolerance;

[0007] (3) Frequent manual intervention: Traditional loading control relies on operator experience to correct errors, resulting in low operating efficiency and insufficient stability. Summary of the Invention

[0008] The purpose of the present invention is to overcome the deficiencies in the above-mentioned prior art and to provide a loading control method and system for a loader based on an error margin. In the control strategy, sensor errors are modeled and tolerance analyzed. By establishing an error margin model and introducing a margin compensation strategy in path planning and control output, the robustness and reliability of the loading action are improved, ensuring that even in the presence of sensor errors, the loader can still load the materials completely into the loaded vehicle, ensuring that the loading task can be accurately completed within the maximum and minimum errors, thereby improving the loading accuracy of the loader and effectively reducing material loss.

[0009] In order to achieve the above object, the present invention is implemented through the following technical solutions:

[0010] On the one hand, the technical solution of the present invention provides a loading control method of a loader based on an error margin, comprising:

[0011] Collect the calibration error and operating error of the sensor and build an error margin model;

[0012] Calculating the loading margin based on the error margin model and expanding the margin space of the loading path;

[0013] Plan the loader bucket control path based on the adaptive PID control algorithm and output the actual moving distance of the loader bucket;

[0014] Use LiDAR to monitor the loader bucket position in real time, triggering fine-tuning control or repeated filling operations.

[0015] In at least one embodiment, the sensor includes a position sensor and a distance sensor.

[0016] In at least one embodiment, the construction of the error margin model is specifically as follows: the comprehensive error of the sensor is calculated based on the collected calibration error and operation error, and the comprehensive error data is statistically modeled, the maximum and minimum values ​​of the comprehensive error data are obtained and the total error is calculated, and the error margin model is constructed according to the total error.

[0017] In at least one embodiment, the total error E=D+Z, where D is the comprehensive error of the distance sensor and Z is the comprehensive error of the position sensor.

[0018] In at least one embodiment, an error margin model is constructed based on the total error, specifically expressed as:

[0019] Error margin Where a is the value of the comprehensive error of the distance sensor.

[0020] In at least one embodiment, based on the calculated error margin A, margin error tolerance space is added in the front-back, left-right, and top-bottom directions of the target loading point, thereby expanding the margin space of the loading path.

[0021] In at least one embodiment, the loader bucket control path is planned based on the adaptive PID control algorithm, specifically: confirm the loading target point, and use its coordinates as the set value input value PID controller, combine the real-time sensor feedback and the error margin model to calculate the actual movement distance of the loader bucket, and the calculation formula is: y3=y1+y2, where y2 is the control movement distance output by the PID controller, and y1 is the additional movement distance of the bucket, whose value is equal to the error margin A.

[0022] In at least one embodiment, the parameters of the adaptive PID algorithm are dynamically adjusted based on material weight, loader model, and environmental parameters.

[0023] In at least one embodiment, the real-time monitoring of the loader bucket position using a laser radar is specifically as follows:

[0024] A lidar is set on the loader bucket to monitor the measured distance in real time. If the distance is less than the set safety threshold, the filling task is interrupted and the fine-tuning control task is executed.

[0025] On the other hand, the technical solution of the present invention further provides a loading control system for a loader based on an error margin, comprising:

[0026] The error modeling module is configured to: collect the calibration error and operation error of the sensor and build an error envelope model;

[0027] A margin compensation module is configured to: calculate the loading margin based on the error envelope model and expand the margin space of the loading path;

[0028] The control path planning module is configured to: plan a control path of the loader bucket based on an adaptive PID control algorithm and output an actual movement distance of the loader bucket;

[0029] The redundancy detection module is configured to use a lidar to monitor the position of the loader bucket in real time and trigger fine-tuning control or repeated loading operations.

[0030] The beneficial effects of the technical solution of the present invention are as follows:

[0031] 1) The loading control method proposed in the present invention models sensor errors and performs tolerance analysis in the control strategy. By establishing an error margin model and introducing a margin compensation strategy in path planning and control output, the robustness and reliability of the loading action are improved. This ensures that even under the condition of sensor errors, the loader can still load the materials completely into the loaded vehicle, and ensures that the loading task can be accurately completed within the maximum and minimum errors, thereby improving the loading accuracy of the loader and effectively reducing material loss.

[0032] 2) The loading control method proposed in the present invention adopts an adaptive PID control algorithm, adjusts the control parameters in real time, and automatically corrects and outputs the control quantity, which can effectively improve the operating efficiency of the loader, reduce the degree of manual intervention, avoid the impact of human factors on loading efficiency and stability, and reduce energy consumption through automatic optimization to improve economy.

[0033] 3) The loading control method proposed in the present invention can enable the loader to adapt to different operating environments and loaded vehicles by controlling the loading margin space, effectively improving the system robustness. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0035] Figure 1Schematic diagram of a loading control method for a loader based on an error margin disclosed in Example 1 of the present invention.

[0036] Figure 2 This is a schematic diagram of the loader bucket structure disclosed in Example 1 of the present invention;

[0037] Figure 3 This is a schematic diagram of the loaded vehicle disclosed in Example 1 of the present invention;

[0038] Figure 4 Schematic diagram of the relative positional relationship between the loader bucket and the loaded vehicle disclosed in Example 1 of the present invention;

[0039] Figure 5 This is a block diagram of the loader bucket control system disclosed in Example 1 of the present invention. DETAILED DESCRIPTION

[0040] It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used in the present invention have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0041] As introduced in the background technology, the purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and provide a loading control method and system for a loader based on error margin, modeling and tolerance analysis of sensor errors in the control strategy, establishing an error boundary model, and introducing a margin compensation strategy in path planning and control output to improve the robustness and reliability of the loading action, ensuring that under the condition of sensor errors, the loader can still load the materials completely into the loaded vehicle, ensuring that the loading task can still be accurately completed within the maximum and minimum errors, thereby improving the loading accuracy of the loader and effectively reducing material loss.

[0042] Example 1

[0043] In a typical embodiment of the present invention, Figure 1 As shown, this embodiment discloses a loading control method of a loader based on an error margin, and the specific steps include:

[0044] Step 1: Collect the calibration error and operating error of the sensor and build an error margin model;

[0045] Step 2: Calculate the loading margin based on the error margin model and expand the margin space of the loading path;

[0046] Step 3: Plan the loader bucket control path based on the adaptive PID control algorithm and output the actual movement distance of the loader bucket;

[0047] Step 4: Use LiDAR to monitor the loader bucket position in real time, triggering fine-tuning control or repeating the loading operation.

[0048] The above control method is described in detail below in conjunction with specific implementation methods.

[0049] Step 1: Collect the calibration error and operating error of the sensor and build an error margin model.

[0050] In this step, the calibration error and operation error of the position sensor and distance sensor are collected, wherein the position sensor and distance sensor are both set as follows: Figure 2 On the bucket of the loader shown, the calibration error of the sensor is obtained through the instructions of the position sensor and the distance sensor, and the operating error of the sensor is obtained through a large number of repeated experiments. The calibration error and operating error of the sensor can be stored in the database in advance, and when collecting the calibration error and operating error of the sensor, they can be directly extracted from the database. Because the error of the sensor does not strictly follow the law of the calibration error in the instructions in actual operation, and the measured operating error has a certain degree of randomness, it is biased to take only either side of the two as the actual error for analysis. Therefore, in this embodiment, a comprehensive error is used for analysis. Specifically, assuming that the calibration error is ε cal , the measured operating error is processed and calculated to obtain the standard deviation of the operating error, which is defined as σ run , then the comprehensive error ε total The modulus value is expressed as:

[0051]

[0052] Then, the comprehensive error is expressed as:

[0053]

[0054] like Figure 3 As shown in the figure, for the distance sensor, assuming the actual length of the loaded vehicle is L, after accounting for the distance sensor's integrated error d, the distance sensor measures the length of the loaded vehicle as L±d. Because this error is relatively small compared to the length of the loaded vehicle, when the distance sensor measures the loader length as Ld, there is ample room for loading, preventing spillage or collision with the front edge, and these issues can be disregarded. However, when the distance sensor measures the loader length as L+d, a space of length d is left after subtracting the length L of the loaded vehicle. Loading material into this space could result in spillage.

[0055] At the same time, the position sensor installed at the loader bucket can feedback the position reached by the loader bucket. Figure 4Taking the established coordinate system as an example, assuming the bucket's actual position is (m, 0), with the direction from the bucket to the front of the loaded vehicle as the positive direction, and considering the position sensor's integrated error d2, the bucket's position measured by the position sensor is (m±d2, 0). When the bucket's measured position is (m+d2, 0), it indicates that the loader bucket's measured position is closer to the loaded vehicle than its actual position. Considering the distance sensor's error d, to eliminate this error, the bucket must be moved forward by d2+d. When the bucket's measured position is (m-d2, 0), it indicates that the loader bucket's measured position is farther from the loaded vehicle than its actual position. To eliminate this error, the bucket must be moved forward by d-d2.

[0056] Based on the above logic, after collecting the sensor error data in this step, the sensor's comprehensive error is calculated. Since a sensor has multiple calibration errors, a sensor will have multiple comprehensive errors. Therefore, the comprehensive error is statistically modeled to obtain the maximum and minimum values ​​of the comprehensive error.

[0057] Assume that the distance sensor comprehensive error is D and the position sensor comprehensive error is Considering the cooperation between the two sensors, the errors of the two sensors must be considered when loading the vehicle. Considering that the errors of the position sensor can be positive or negative (because the positive direction is specified), when calculating the error margin, the positive and negative of the position sensor errors must be analyzed. When the position error is negative, the bucket position measurement value is farther away from the loaded vehicle than the actual value. At this time, the errors of the two sensors are offset. When the position error is positive, the bucket position measurement value is closer to the loaded vehicle than the actual value. At this time, the superposition of the two sensor errors will cause a greater error. From this, we can obtain the error coordinate formula in this coordinate system:

[0058] Total error E = D + Z;

[0059] After obtaining the total error, an error margin model is constructed based on the total error to ensure that the loader completes the task safely and completely when loading. The error margin model is specifically expressed as:

[0060] Error margin

[0061] Step 2: Calculate the loading margin based on the error margin model and expand the margin space of the loading path.

[0062] In this step, we first need to determine the positive or negative error of the position sensor on the bucket. Then, we need to obtain the loading margin based on the error margin model calculated in step 1. We also need to add a certain margin fault tolerance space in the three-dimensional directions of front, back, left, right, and top and bottom of the target loading point to expand the margin space of the loading path.

[0063] That is, the additional moving distance y1 of the loader bucket is determined according to the error margin A, and the calculation formula is:

[0064]

[0065] The size of the margin is automatically adjusted based on the error margin to ensure that the goal of "filling without spilling" can still be met under the most unfavorable error conditions. In this embodiment, the error margin is determined based on the maximum and minimum values ​​of the comprehensive error.

[0066] Step 3: Plan the loader bucket control path based on the adaptive PID control algorithm and output the actual moving distance of the loader bucket.

[0067] To control the loader's automated loading process and ensure the bucket lands near the center, an adaptive PID control algorithm is employed. Because materials, loaded vehicles, and loader models vary, an adaptive PID control algorithm is employed to adjust control parameters in real time, achieving optimal control results. During the control process, the target point to which the loader bucket is directed is first determined. The coordinates of this position are used as the setpoint. The position sensor continuously feeds back measured values, which, combined with a constructed error margin model, achieves calibrated, safe, and consistent control.

[0068] like Figure 5 As shown in the figure, the determined target point coordinates are used as the set value x(t), and the position sensor is used to collect the position x′(t) of the loader bucket. The set value minus the actual value fed back is used to obtain the control error. The control error is used as the input to the adaptive PID controller. The adaptive PID controller calculates the control quantity u. After u is input to the loader, the loader will output an action. At the same time, the established error margin model is used to calculate the sensor error information and also output an action for compensation. y1+y2 is the action output by the loader after compensation.

[0069] That is, the actual moving distance of the bucket is determined by the moving distance y2 output by the adaptive PID controller and the additional moving distance y1 of the bucket calculated by the error margin model. The calculation formula is:

[0070] y3=y1+y2。

[0071] Step 4: Use LiDAR to monitor the loader bucket position in real time, triggering fine-tuning control or repeating the loading operation.

[0072] In this step, a laser radar is installed on the loader bucket, which monitors the distance between the loader bucket and the four sides of the vehicle being loaded in real time. If the distance measured by the laser radar is less than the set safety threshold, the filling task is interrupted, the current filling work of the bucket is ended, and the fine-tuning control task is executed instead.

[0073] During the loading process, lidar is used to monitor the bucket position in real time to determine whether it is close to the boundary of the loaded vehicle due to error. If it is detected to be close to the risk boundary, fine-tuning control is performed. If it is still close to the risk boundary after fine-tuning control, a repeated loading operation is performed to make the loader bucket return along the original route to prevent further collisions and losses. When the bucket is away from the loaded vehicle, it is readjusted and the status task is re-initiated to ensure the integrity of the loading.

[0074] The loading control method proposed in this embodiment models sensor errors and performs tolerance analysis in the control strategy. By establishing an error margin model and introducing a margin compensation strategy in path planning and control output, the robustness and reliability of the loading action are improved. This ensures that even in the presence of sensor errors, the loader can still load the materials completely into the loaded vehicle, and ensures that the loading task can be accurately completed within the maximum and minimum errors.

[0075] Example 2

[0076] In a typical embodiment of the present invention, this embodiment discloses a loading control system for a loader based on an error margin, comprising:

[0077] The error modeling module is configured to: collect the calibration error and operation error of the sensor and build an error margin model;

[0078] A margin compensation module is configured to: calculate the loading margin based on the error margin model and expand the margin space of the loading path;

[0079] The control path planning module is configured to: plan a control path of the loader bucket based on an adaptive PID control algorithm and output an actual movement distance of the loader bucket;

[0080] The redundancy detection module is configured to use a lidar to monitor the position of the loader bucket in real time and trigger fine-tuning control or repeated loading operations.

[0081] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A loading control method for a loader based on an error margin, characterized in that: include: Collect the calibration error and operating error of the sensor and build an error margin model; Calculating the loading margin based on the error margin model and expanding the margin space of the loading path; Plan the loader bucket control path based on the adaptive PID control algorithm and output the actual moving distance of the loader bucket; Use LiDAR to monitor the loader bucket position in real time, triggering fine-tuning control or repeated filling operations.

2. The method for controlling loading of a loader based on an error margin as claimed in claim 1, wherein: The sensors include a position sensor and a distance sensor.

3. The method for controlling loading of a loader based on an error margin as claimed in claim 1, wherein: The error margin model is constructed by calculating the comprehensive error of the sensor based on the collected calibration error and operation error, performing statistical modeling on the comprehensive error data, obtaining the maximum and minimum values ​​of the comprehensive error data and calculating the total error, and constructing the error margin model based on the total error.

4. The method for controlling loading of a loader based on an error margin as claimed in claim 2, wherein: In the same coordinate system, the total error E=D+Z, where D is the comprehensive error of the distance sensor and Z is the comprehensive error of the position sensor.

5. The method for controlling loading of a loader based on an error margin as claimed in claim 4, characterized in that: The error margin model is constructed based on the total error, which is specifically expressed as: Error margin Where a is the value of the comprehensive error of the distance sensor.

6. The method for controlling loading of a loader based on an error margin as claimed in claim 4, characterized in that: Based on the calculated error margin A, margin tolerance space is added in the front, back, left, right, and up and down directions of the target loading point to expand the margin space of the loading path.

7. The method for controlling loading of a loader based on an error margin as claimed in claim 1, wherein: The loader bucket control path is planned based on the adaptive PID control algorithm. Specifically, the loading target point is confirmed and its coordinates are used as the set value input to the PID controller. The actual movement distance of the loader bucket is calculated by combining real-time sensor feedback and the error margin model. The calculation formula is: y3=y1+y2, where y2 is the control movement distance output by the PID controller and y1 is the additional movement distance of the bucket, whose value is equal to the error margin A.

8. The method for controlling loading of a loader based on an error margin as claimed in claim 1, wherein: The parameters of the adaptive PID algorithm are dynamically adjusted according to the material weight, the loading vehicle model and the environmental parameters.

9. The method for controlling loading of a loader based on an error margin as claimed in claim 1, wherein: The real-time monitoring of the loader bucket position by using a laser radar is as follows: A lidar is set on the loader bucket to monitor the measured distance in real time. If the distance is less than the set safety threshold, the filling task is interrupted and the fine-tuning control task is executed.

10. A loading control system for a loader based on an error margin, characterized in that: include: The error modeling module is configured to: collect the calibration error and operation error of the sensor and build an error margin model; A margin compensation module is configured to: calculate the loading margin based on the error margin model and expand the margin space of the loading path; The control path planning module is configured to: plan a control path of the loader bucket based on an adaptive PID control algorithm and output an actual movement distance of the loader bucket; The redundancy detection module is configured to use a lidar to monitor the position of the loader bucket in real time and trigger fine-tuning control or repeated loading operations.

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