Control method, device and equipment of power transmission tower lifting system, storage medium and program product

Abstract

The invention relates to a control method and device for a power transmission tower lifting system, equipment, a storage medium and a program product, and the method comprises the steps: obtaining the operation state information and the external interference information of the power transmission tower lifting system, and constructing a reference curve according to the operation state information and the external interference information; then inputting the operation state information, the external interference information and the reference curve into a preset simulation model for simulation to obtain a target tracking curve, and finally controlling the lifting of the power transmission tower according to the target tracking curve and the reference curve. According to the method, the target tracking curve and the reference curve are combined for control, and the system can sense the influence of external interference on the lifting driving force in real time. When the actually needed lifting driving force deviates from the reference curve due to external interference, the target tracking curve can control the lifting system to adjust the lifting driving force in time according to the deviation condition, and then lifting of the power transmission tower can be accurately controlled.

Description

Technical Field

[0001] The present application relates to the field of lifting control technology, and in particular to a control method, device, equipment, storage medium and program product for a transmission tower lifting system. Background Art

[0002] In the field of power transmission, transmission towers, as crucial infrastructure, are generally quite tall. With the continued expansion of power grids and technological advancements, the importance of tower installation, maintenance, and component replacement has become increasingly prominent. These tasks are not only crucial for ensuring stable grid operation but also directly impact the reliability and security of power supply. Therefore, precise control of tower elevation and elevation is particularly crucial in current power construction and maintenance efforts.

[0003] Currently, tower lifting often relies on extensive manpower and simple mechanical tools. The process is cumbersome, and each lift requires significant time and effort, severely impacting operational progress. Furthermore, towers are prone to shaking and tilting during the lifting process, significantly increasing safety risks for operators and potentially damaging the towers themselves, impacting their service life and performance. Traditional lifting methods present significant challenges, particularly in mountainous areas with rugged terrain and difficult roads, as well as in areas with complex topography.

[0004] Therefore, how to accurately control the lifting and lowering of transmission towers has become an urgent problem to be solved in the current power transmission field. Summary of the Invention

[0005] Based on this, it is necessary to provide a control method, device, equipment, storage medium and program product for a transmission tower lifting system that can accurately control the lifting of the transmission tower to address the above technical problems.

[0006] In a first aspect, the present application provides a control method for a transmission tower lifting system, the method comprising:

[0007] Obtaining operating status information and external interference information of the transmission tower lifting system, and constructing a reference curve based on the operating status information and external interference information; the reference curve is used to represent the change in the lifting driving force corresponding to the current operating state of the transmission tower lifting system;

[0008] The operating status information, external interference information and reference curve are input into the preset simulation model for simulation to obtain the target tracking curve; the target tracking curve is used to characterize the changes in the corresponding lifting driving force of the transmission tower lifting system in the simulation environment.

[0009] The lifting and lowering of the transmission tower is controlled according to the target tracking curve and the reference curve.

[0010] In one embodiment, the operating state information includes first state information, and the preset simulation model includes a first simulation sub-model and a second simulation sub-model. The operating state information, external interference information, and a reference curve are input into the preset simulation model for simulation to obtain a target tracking curve, including:

[0011] Inputting the first state information and the reference curve into a first simulation sub-model to obtain a first tracking curve; the first simulation sub-model is a simulation model corresponding to the PID controller; the first state information includes at least one of the current height of the transmission tower, the rope tension in the lifting system, and the drum speed;

[0012] The first tracking curve, external interference information and reference curve are input into the second simulation sub-model to obtain the second tracking curve, and the second tracking curve is determined as the target tracking curve; the second simulation sub-model is the simulation model corresponding to the backstepping controller.

[0013] In one embodiment, the operating state information further includes second state information, the preset simulation model further includes a third simulation sub-model, and the method further includes:

[0014] The second tracking curve, the first state information, the second state information and the reference curve are input into the third simulation sub-model to obtain the third tracking curve, and the third tracking curve is determined as the target tracking curve; the third simulation sub-model is the simulation model corresponding to the sliding mode controller; the second state information includes the angular velocity of the reel.

[0015] In one embodiment, inputting the first state information and the reference curve into the first simulation sub-model to obtain the first tracking curve includes:

[0016] Inputting the first state information into the first simulation sub-model to obtain an initial tracking curve;

[0017] Compare the initial tracking curve with the reference curve to obtain a comparison result;

[0018] A first tracking curve is determined according to the comparison result.

[0019] In one embodiment, determining a first tracking curve according to the comparison result includes:

[0020] If the comparison result indicates that the initial tracking curve meets the preset requirements, the initial tracking curve is determined as the first tracking curve;

[0021] If the comparison result indicates that the initial tracking curve does not meet the preset requirements, the parameters of the first simulation sub-model are adjusted until the initial tracking curve meets the preset requirements.

[0022] In one embodiment, controlling the raising and lowering of a transmission tower according to a target tracking curve and a reference curve includes:

[0023] Determine the error amount based on the target tracking curve and the reference curve;

[0024] Generate a target driving signal according to the error amount and the historical driving signal;

[0025] The lifting and lowering of the transmission tower is controlled according to the target driving signal.

[0026] In a second aspect, the present application further provides a control device for a transmission tower lifting system, the device comprising:

[0027] An acquisition module is used to obtain the operating status information and external interference information of the transmission tower lifting system, and to construct a reference curve based on the operating status information and external interference information; the reference curve is used to represent the change in the lifting driving force corresponding to the current operating state of the transmission tower lifting system;

[0028] The simulation module is used to input the operating status information, external interference information and reference curve into the preset simulation model for simulation to obtain the target tracking curve; the target tracking curve is used to represent the changes in the corresponding lifting driving force of the transmission tower lifting system in the simulation environment;

[0029] The control module is used to control the lifting and lowering of the transmission tower according to the target tracking curve and the reference curve.

[0030] In a third aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0031] Obtaining operating status information and external interference information of the transmission tower lifting system, and constructing a reference curve based on the operating status information and external interference information; the reference curve is used to represent the change in the lifting driving force corresponding to the current operating state of the transmission tower lifting system;

[0032] The operating status information, external interference information and reference curve are input into the preset simulation model for simulation to obtain the target tracking curve; the target tracking curve is used to represent the changes in the corresponding lifting driving force of the transmission tower lifting system in the simulation environment;

[0033] According to the target tracking curve and the reference curve, the lifting and lowering of the transmission tower is controlled.

[0034] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the following steps:

[0035] Obtaining operating status information and external interference information of the transmission tower lifting system, and constructing a reference curve based on the operating status information and external interference information; the reference curve is used to represent the change in the lifting driving force corresponding to the current operating state of the transmission tower lifting system;

[0036] The operating status information, external interference information and reference curve are input into the preset simulation model for simulation to obtain the target tracking curve; the target tracking curve is used to represent the changes in the corresponding lifting driving force of the transmission tower lifting system in the simulation environment;

[0037] According to the target tracking curve and the reference curve, the lifting and lowering of the transmission tower is controlled.

[0038] In a fifth aspect, the present application further provides a computer program product, the computer program product comprising a computer program, which, when executed by a processor, implements the following steps:

[0039] Obtaining operating status information and external interference information of the transmission tower lifting system, and constructing a reference curve based on the operating status information and external interference information; the reference curve is used to represent the change in the lifting driving force corresponding to the current operating state of the transmission tower lifting system;

[0040] The operating status information, external interference information and reference curve are input into the preset simulation model for simulation to obtain the target tracking curve; the target tracking curve is used to represent the changes in the corresponding lifting driving force of the transmission tower lifting system in the simulation environment;

[0041] According to the target tracking curve and the reference curve, the lifting and lowering of the transmission tower is controlled.

[0042] The control method, device, equipment, storage medium, and program product for the transmission tower lifting system described above obtain operating status information and external interference information of the transmission tower lifting system, construct a reference curve based on the operating status information and external interference information, then input the operating status information, external interference information, and reference curve into a preset simulation model for simulation to obtain a target tracking curve. Finally, the lifting of the transmission tower is controlled based on the target tracking curve and the reference curve. In the above method, by combining the target tracking curve and the reference curve for control, the system can perceive the impact of external interference on the lifting drive force in real time. When external interference causes the actual required lifting drive force to deviate from the reference curve, the target tracking curve controls the lifting system to promptly adjust the lifting drive force based on the deviation, avoiding dangerous situations such as loss of control during the lifting process, tower tilting, or even collapse caused by interference, ensuring the safety of operators and the surrounding environment, and thus accurately controlling the lifting of the transmission tower. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a diagram of an application environment of a control method for a transmission tower lifting system in one embodiment;

[0044] Figure 2 This is a flow chart of a control method for a transmission tower lifting system according to an embodiment;

[0045] Figure 3 This is a second flow chart of a control method for a transmission tower lifting system according to an embodiment;

[0046] Figure 4 Schematic diagram of the corresponding relationship between the reference signal and the PID signal in one embodiment;

[0047] Figure 5 This is a third flow chart of a control method for a transmission tower lifting system according to an embodiment;

[0048] Figure 6 Schematic diagram of the corresponding relationship between the reference signal and the backstepping signal in one embodiment;

[0049] Figure 7 FIG4 is a fourth flow chart of a control method for a transmission tower lifting system according to an embodiment;

[0050] Figure 8 Schematic diagram of the corresponding relationship between the reference signal and the adaptive robust signal in one embodiment;

[0051] Figure 9 Schematic diagram of the corresponding relationship between the PID signal, the backstepping signal and the adaptive robust signal in one embodiment;

[0052] Figure 10 FIG4 is a flow chart of a control method of a transmission tower lifting system according to an embodiment;

[0053] Figure 11 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0055] In the field of power transmission, transmission towers, as crucial infrastructure, are generally quite tall. With the continuous expansion of power grids and technological advancements, the importance of tower installation, maintenance, and component replacement has become increasingly prominent. These tasks are not only crucial for ensuring stable grid operation but also directly impact the reliability and safety of power supply. Therefore, precise control of tower raising and lowering is crucial in current power construction and maintenance work. Currently, tower raising and lowering often relies heavily on manual labor and simple mechanical tools. The operation process is cumbersome, and each lift requires significant time and effort, significantly impacting work progress. Furthermore, towers are prone to shaking and tilting during the raising and lowering process, significantly increasing safety risks for workers and potentially damaging the towers themselves, impacting their service life and performance. Traditional raising and lowering methods are particularly challenging in mountainous areas with rugged terrain and difficult roads, as well as in complex terrain. Therefore, precisely controlling the raising and lowering of transmission towers has become a pressing issue in the power transmission industry.

[0056] In view of this, the embodiments of the present application propose a control method, device, equipment, storage medium and program product for a transmission tower lifting system, which can accurately control the lifting of the transmission tower by combining the operating status information and external interference information of the transmission tower lifting system.

[0057] It should be noted that the beneficial effects or technical problems solved by the embodiments of the present application are not limited to this one, but may also include other implicit or related problems. For details, please refer to the description of the following embodiments.

[0058] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0059] In some embodiments, the control method of the transmission tower lifting system provided in the embodiment of the present application can be applied to Figure 1The application environment shown in FIG. This application environment includes a control device 101 and a transmission tower lifting system (hereinafter referred to as the lifting system) 102. The lifting system 102 includes a servo winch system 1021, multiple pulley sets 1022, and a transmission tower 1023. The control device 101 is connected to the lifting system 102. The servo winch system 1021 is connected to the multiple pulley sets 1022, which are further connected to the transmission tower 1023. The control device 101 is used to obtain operating status information and external interference information of the transmission tower lifting system. Then, based on the operating status information and external interference information of the transmission tower lifting system, it outputs a control signal to control the lifting of the transmission tower. The servo winch system 1021 controls the rotation of the multiple pulley sets 1022 to control the lifting of the transmission tower 1023. The control device 101 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, Internet of Things devices, and portable wearable devices.

[0060] Those skilled in the art will understand that Figure 1 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the application environment to which the solution of the present application is applied. The specific application environment may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0061] In some embodiments, as Figure 2 As shown, a control method for a transmission tower lifting system is provided, and the method is applied to Figure 1 The control device in the example is used to illustrate the process, which includes the following steps:

[0062] S201, obtaining operating status information and external interference information of a transmission tower lifting system, and constructing a reference curve according to the operating status information and the external interference information.

[0063] The reference curve represents the change in the lifting drive force corresponding to the current operating state of the transmission tower lifting system. The operating state information includes at least one of the current height of the transmission tower, the rope tension in the lifting system, the drum speed, and the drum angular velocity. External interference information includes wind resistance, mechanical vibration, and friction between lifting system components.

[0064] In an embodiment of the present application, the control device can obtain the operating status information and external interference information of the transmission tower lifting system over a period of time through a monitoring system. For example, the current height of the transmission tower can be obtained by using a rangefinder; the rope tension in the lifting system can be obtained by using a tension sensor; the drum speed and drum angular velocity can be obtained by using a speed sensor; the wind speed and wind direction can be measured by an anemometer and a wind vane, and then the wind speed and wind direction can be input into a preset wind resistance calculation formula to calculate the current wind resistance; mechanical vibration can be obtained by using an acceleration sensor; and the friction between the lifting system components can be indirectly measured by using a pressure sensor and a torque sensor. After obtaining the operating status information and external interference information of the transmission tower lifting system, the operating status information and external interference information can be input into a preset mathematical model to calculate the change in the lifting driving force corresponding to the current operating state and plotted as a reference curve. The preset mathematical model can be constructed based on the physical principles of the transmission tower lifting system and historical data, and the preset mathematical model is used to describe the relationship between the lifting driving force and the operating status information and external interference information.

[0065] S202 , inputting the operation status information, external interference information and reference curve into a preset simulation model for simulation to obtain a target tracking curve.

[0066] The target tracking curve is used to represent the change in the lifting driving force corresponding to the transmission tower lifting system in a simulation environment. The preset simulation model includes at least one of a first simulation model corresponding to a PID controller, a second simulation model corresponding to a backstepping controller, and a third simulation model corresponding to a sliding mode controller.

[0067] In an embodiment of the present application, a preset simulation model can be pre-constructed based on at least one of a PID controller, a backstepping controller, and a sliding mode controller. After the control device obtains the operating status information, external interference information, and a reference curve of the transmission tower lifting system over a period of time based on the above steps, the operating status information and external interference information can be input into the preset simulation model for simulation to obtain the curve output by the PID controller, the curve output by the backstepping controller, and the curve output by the sliding mode controller. The curve output by the PID controller, the curve output by the backstepping controller, and the curve output by the sliding mode controller are then compared and analyzed with the reference curve, and a target tracking curve is determined from the curve output by the PID controller, the curve output by the backstepping controller, and the curve output by the sliding mode controller.

[0068] S203, controlling the lifting and lowering of the transmission tower according to the target tracking curve and the reference curve.

[0069] In an embodiment of the present application, after the control device obtains the target tracking curve and the reference curve based on the above steps, it can perform error analysis on the target tracking curve and the reference curve, determine the control amount based on the error analysis results, and finally control the lifting and lowering of the transmission tower according to the control amount.

[0070] The control method for a transmission tower lifting system provided in an embodiment of the present application obtains operating status information and external interference information of the transmission tower lifting system, constructs a reference curve based on the operating status information and external interference information, then inputs the operating status information, external interference information, and reference curve into a preset simulation model for simulation to obtain a target tracking curve, and finally controls the lifting of the transmission tower based on the target tracking curve and the reference curve. In the above method, by combining the target tracking curve and the reference curve for control, the system can perceive the impact of external interference on the lifting driving force in real time. When external interference causes the actual required lifting driving force to deviate from the reference curve, the target tracking curve will control the lifting system to adjust the lifting driving force in a timely manner according to the deviation, avoiding dangerous situations such as loss of control of the lifting process, tilting of the tower, or even collapse due to interference, ensuring the safety of operators and the surrounding environment, and thus accurately controlling the lifting of the transmission tower.

[0071] In some embodiments, the above-mentioned operating state information includes first state information, and the preset simulation model includes a first simulation sub-model and a second simulation sub-model. On this basis, a specific implementation method for obtaining a target tracking curve is also provided, such as Figure 3 As shown, the above S202 of “inputting the operating status information, external interference information and the reference curve into a preset simulation model for simulation to obtain a target tracking curve” includes:

[0072] S301: Input first state information and a reference curve into a first simulation sub-model to obtain a first tracking curve.

[0073] The operating state information includes first state information, and the preset simulation model includes a first simulation sub-model and a second simulation sub-model. The first simulation sub-model is a simulation model corresponding to the PID controller; the first state information includes at least one of the current height of the transmission tower, the rope tension in the lifting system, and the drum speed. The first tracking curve represents the relationship between the reference signal and the PID signal. For details, see Figure 4 As shown, the vertical axis in the figure represents driving force and the horizontal axis represents time.

[0074] In this embodiment of the present application, a first simulation sub-model can be pre-constructed based on a PID controller. After the control device obtains the operating status information and reference curve of the transmission tower lifting system over a period of time based on the above steps, first status information in the operating status information can be input into the first simulation sub-model for simulation to obtain a first tracking curve.

[0075] Specifically, such as Figure 5 As shown, the above-mentioned S301 of “inputting the first state information and the reference curve into the first simulation sub-model to obtain the first tracking curve” includes:

[0076] S3011: Input the first state information into the first simulation sub-model to obtain an initial tracking curve.

[0077] In an embodiment of the present application, the control device may input the first state information into the first simulation sub-model to obtain an initial tracking curve.

[0078] S3012: Compare the initial tracking curve with the reference curve to obtain a comparison result.

[0079] The comparison result includes whether the initial tracking curve meets the preset requirement or whether the initial tracking curve does not meet the preset requirement. The preset requirement can be determined based on the reference curve.

[0080] In an embodiment of the present application, after the control device obtains an initial tracking curve, it can compare the initial tracking curve with a reference curve. Specifically, it can compare each point on the initial tracking curve with the corresponding point on the reference curve to determine the error value of each point, and further determine whether the error values ​​of each point are less than a preset error threshold. If the error values ​​of all points are less than the preset error threshold, it indicates that the initial tracking curve meets the preset requirements. If there is a point with an error value that is not less than the preset error threshold, it indicates that the initial tracking curve does not meet the preset requirements. The preset error threshold can be determined based on actual accuracy requirements.

[0081] S3013: Determine a first tracking curve according to the comparison result.

[0082] In an embodiment of the present application, the control device obtains a comparison result based on the above steps. If the comparison result indicates that the initial tracking curve meets the preset requirements, the initial tracking curve is determined as the first tracking curve. If the comparison result indicates that the initial tracking curve does not meet the preset requirements, the parameters of the first simulation sub-model are adjusted until the initial tracking curve meets the preset requirements.

[0083] S302 : Input the first tracking curve, external interference information, and the reference curve into the second simulation sub-model to obtain a second tracking curve, and determine the second tracking curve as the target tracking curve.

[0084] The second simulation sub-model is the simulation model corresponding to the backstepping controller. The second tracking curve represents the relationship between the reference signal and the backstepping signal. Figure 6 As shown, the vertical axis in the figure represents driving force and the horizontal axis represents time.

[0085] In this embodiment of the present application, a second simulation sub-model can be pre-constructed based on a backstepping controller. After the control device obtains the first tracking curve based on the above steps, the first tracking curve and external interference information can be input into the second simulation sub-model for simulation to obtain a second tracking curve, which is then determined as the target tracking curve.

[0086] Optional, in Figure 3 On the basis of, the above-mentioned running state information also includes the second state information, and the preset simulation model also includes a third simulation sub-model, such as Figure 7 As shown, the above method for obtaining the target tracking curve also includes:

[0087] S303 : Input the second tracking curve, the first state information, the second state information, and the reference curve into the third simulation sub-model to obtain a third tracking curve, and determine the third tracking curve as the target tracking curve.

[0088] The operating state information also includes the second state information, and the preset simulation model also includes a third simulation sub-model. The third simulation sub-model is a simulation model corresponding to the sliding mode controller (adaptive robust controller); the second state information includes the angular velocity of the reel. The third tracking curve represents the relationship between the reference signal and the adaptive robust signal. For details, see Figure 8 As shown in the figure, the vertical axis represents the driving force and the horizontal axis represents the time. The relationship between the control signal output by the PID controller, the backstepping control signal output by the backstepping controller simulation model and the adaptive robust control signal output by the sliding membrane controller can be seen in Figure 9 As shown, the vertical axis in the figure represents driving force and the horizontal axis represents time.

[0089] In this embodiment of the present application, a third simulation sub-model can be pre-constructed based on the sliding mode controller. After the control device obtains the second tracking curve based on the above steps, the second tracking curve, the first state information, the second state information, and the reference curve can be input into the third simulation sub-model to obtain a third tracking curve, and the third tracking curve can be determined as the target tracking curve.

[0090] In some embodiments, a specific implementation method for controlling the lifting of a transmission tower is also provided, such as Figure 10 As shown, the above-mentioned "controlling the lifting and lowering of the transmission tower according to the target tracking curve and the reference curve" in S203 includes:

[0091] S401, determining an error amount according to the target tracking curve and the reference curve.

[0092] In an embodiment of the present application, after the control device obtains the target tracking curve and the reference curve, the target tracking curve and the reference curve can be compared. Specifically, each point on the target tracking curve can be compared with the corresponding point on the reference curve to determine the error value of each point, and the error amount can be further determined based on the error value of each point. Specifically, an error matrix or error vector can be constructed based on the error value of each point, and then the error amount can be determined based on the error matrix or error vector.

[0093] S402 : Generate a target driving signal according to the error amount and the historical driving signal.

[0094] The historical driving signal is the driving signal used to drive the lifting system last time, and the target driving signal is the driving signal used to drive the lifting system currently.

[0095] In an embodiment of the present application, after the control device obtains the error amount based on the above steps, it can obtain the previous drive signal in the historical drive signal, and then sum the previous drive signal and the drive signal of the corresponding size of the error amount to obtain the target drive signal.

[0096] S403: Control the lifting and lowering of the transmission tower according to the target driving signal.

[0097] In the embodiment of the present application, after the control device obtains the target drive signal based on the above steps, it can input the target drive signal to the servo winch system in the lifting system to control the lifting of the transmission tower. In combination with all the above embodiments, a control method for the transmission tower lifting system is also provided, which includes:

[0098] S501: Acquire operating status information and external interference information of the transmission tower lifting system, and construct a reference curve based on the operating status information and external interference information. The reference curve is used to represent the change of the lifting driving force corresponding to the current operating state of the transmission tower lifting system.

[0099] S502: Input first state information into a first simulation sub-model to obtain an initial tracking curve. The first simulation sub-model is a simulation model corresponding to the PID controller. The first state information includes at least one of the current height of the transmission tower, the rope tension in the lifting system, and the drum speed.

[0100] S503: Compare the initial tracking curve with the reference curve to obtain a comparison result.

[0101] S504: If the comparison result indicates that the initial tracking curve meets the preset requirement, the initial tracking curve is determined as the first tracking curve.

[0102] S505: If the comparison result indicates that the initial tracking curve does not meet the preset requirements, the parameters of the first simulation sub-model are adjusted until the initial tracking curve meets the preset requirements.

[0103] S506: Input the first tracking curve, the external interference information, and the reference curve into the second simulation sub-model to obtain a second tracking curve. The second simulation sub-model is a simulation model corresponding to the backstepping controller.

[0104] At step S507, the second tracking curve, the first state information, the second state information, and the reference curve are input into the third simulation sub-model to obtain a third tracking curve, which is then determined as the target tracking curve. The third simulation sub-model is the simulation model corresponding to the sliding mode controller. The target tracking curve is used to represent changes in the lifting driving force of the transmission tower lifting system under a simulation environment.

[0105] S508: Determine the error amount according to the target tracking curve and the reference curve.

[0106] S509 , generating a target driving signal according to the error amount and the historical driving signal.

[0107] S510: Control the lifting and lowering of the transmission tower according to the target driving signal.

[0108] In the embodiment of the present application, a separate PID control experiment is first carried out to obtain a tracking curve, then the backstepping controller is switched to obtain a tracking curve, and finally an adaptive backstepping sliding mode controller is used to conduct an experiment. According to the horizontal comparison of the three figures, it can be seen that external interference has a certain influence on the tracking performance of the system, and the waveform has been severely distorted in some areas. It can be seen that if there is external interference, the performance of the PID controller is not as good as that of the nonlinear controller, and there is a certain amplitude phase difference between the given reference signal and the actual feedback value. Among these two nonlinear controllers, compared with the simple single backstepping control, the control effect of the adaptive backstepping sliding mode is slightly improved, that is, the adaptive parameters, the estimated interference force and the designed sliding mode have a certain effect on the improvement of system performance.

[0109] The process of building a preset simulation model is as follows:

[0110] (1) The PID controller is a common feedback controller that processes the error signal through three steps: proportional (P), integral (I), and differential (D) to generate a control output. Proportional step (P): Outputs the control quantity proportional to the current error value (the difference between the set value and the actual feedback value). The larger the proportional coefficient, the faster the system responds to the error, but it may cause the system's overshoot to increase and the stability to deteriorate. Integral step (I): Integrates the error to eliminate the system's steady-state error. As time accumulates, the integral term will gradually increase, forcing the system's output to approach the set value until the error is zero. However, if the integral action is too strong, the system's response speed will slow down and the overshoot will increase. Differential step (D): Outputs the control quantity based on the rate of change of the error. It can predict the error change trend and give control action in advance, thereby improving the system's dynamic performance, such as reducing overshoot and shortening the adjustment time. However, the differential step is sensitive to noise and tends to amplify high-frequency noise.

[0111] PID controllers are typically connected to a real-time control system (possibly via devices such as the AD PCI-1716 or DA ACL-6126). The monitoring system (Simulink model) sets a reference signal (such as the desired tower height or speed) and simultaneously obtains actual feedback signals (such as rope tension and drum speed from the servo winch system) through sensors and other devices. Based on the difference (error signal) between the reference signal and the actual feedback signal, the PID controller calculates the control variable according to the aforementioned P, I, and D operation rules and converts it into a drive signal suitable for the servo winch system (such as 4-20 mA), thereby controlling the operation of the servo winch. During PID control experiments, by continuously collecting the reference signal and the actual feedback signal and calculating the difference between them, a series of error data is generated over time. Plotting this error data on a time axis forms a tracking curve. This curve reflects how well the actual output tracks the reference input under PID control.

[0112] In practice, adjusting the values ​​of the proportional coefficient Kp, integral coefficient Ki, and differential coefficient Kd can alter the performance of the PID controller, thereby affecting the formation of the tracking curve. For example, increasing Kp will make the curve respond faster to errors, but may cause overshoot; increasing Ki can reduce steady-state error, but may slow the system response; and increasing Kd can improve the system's dynamic performance, but the effects of noise should be considered. The trends in the tracking curves obtained in experiments (such as rise time, overshoot, and steady-state error) are directly related to the adjustment of the coefficients in the formula and the PID control principle. By analyzing the tracking curves under different coefficients, the PID controller parameters can be optimized to achieve better control results. The PID controller connects to other components in the system to obtain reference and feedback signals. According to the PID control principle, it calculates the control variable and generates the drive signal. Its control effect can be intuitively reflected in the tracking curve, which is closely related to the mathematical formula of PID control.

[0113] (2) After completing the individual PID control experiments and obtaining their tracking curves, in order to compare the performance of different control methods in dealing with external interference, we will switch to the backstepping controller for experiments. When the control effect needs to be further optimized, especially when higher system performance requirements are required (such as smaller following error, better anti-interference ability, etc.), we will switch to the adaptive backstepping sliding mode controller for experiments. This switching is to systematically evaluate and compare the performance of different control strategies in the servo winch system.

[0114] The backstepping controller is a controller used in experiments after the PID control experiment. Its connection to the entire system is similar to that of the PID controller. It also connects to the monitoring system and the servo winch system through a real-time control system, receives reference and feedback signals, and outputs corresponding control signals to drive the servo winch.

[0115] Backstepping Control is a recursive design method that decomposes a complex nonlinear system into several subsystems. Starting from the outermost system, it gradually designs a virtual control law, and then designs the actual control law for each subsystem by "backstepping". For a system of the form x1=x2+f1(x1), The first step is to define a virtual control quantity α1 so that x1 can track the desired trajectory x1d. Where k1 is a positive constant, solve The second step is to define the error z2 = x2 - α1, then take the derivative of z2 and design the control law u so that z2 converges quickly to zero. Through a series of derivations and calculations, the final control law expression is obtained. The backstepping controller design process can take system and external disturbances into account. Appropriate methods (such as the introduction of robust terms) can be used to suppress the impact of disturbances on system performance, thereby improving the system's tracking performance and stability.

[0116] The design process of backstepping control involves the derivation of a series of mathematical formulas, including the calculation of state variable derivatives and the derivation of expressions for virtual and actual control laws. These formulas embody the principles and methods of backstepping control. Through analysis of the system model and mathematical operations, control law formulas that achieve system stability and tracking control are derived. For example, in the aforementioned second-order system example, the control law expression derived through formula derivation is the mathematical embodiment of the backstepping control principle. It determines the control input based on factors such as the system state, desired trajectory, and the system's nonlinear functions to achieve effective control of the system. Corresponding to the experimental tracking curves shown in the figure, different control law formulas (i.e., different controller designs) lead to different tracking performance. By comparing the tracking curves, we can intuitively see the advantages of backstepping controllers over PID controllers in dealing with external disturbances.

[0117] (3) The adaptive reflective sliding mode controller is a control device used for further experiments after completing the PID control and backstepping controller experiments. Its connection to the entire system is similar to that of the previous two controllers, connecting to the monitoring system, servo winch system, etc. through a real-time control system. It receives reference and feedback signals and outputs control signals to drive the servo winch. The only difference is its internal control algorithm and structure.

[0118] Backstepping control: Similar to the backstepping controller mentioned above, this decomposes a complex nonlinear system into multiple subsystems. Starting from the outermost layer, the control law is gradually designed by defining virtual control variables. For example, for a nonlinear system, a virtual control law is first designed for the first subsystem to enable it to track the desired trajectory. Then, an error variable is defined, and the control law is designed for the next subsystem, and so on, until the actual control law for the entire system is designed. This process is carried out recursively, building the entire control system through continuous "rebounding".

[0119] Sliding mode control part: The core idea of ​​sliding mode control is to design a sliding surface (usually a function of the system state) and make the system state reach the sliding surface within a finite time and move to the equilibrium point along the sliding surface. For example, for a second-order system, the sliding surface can be designed as (where ∈ is the tracking error and c is a positive constant). Then, by designing the control law u, This can ensure that the system state can reach the sliding surface within a limited time and keep moving on it, thereby achieving robust control of the system, that is, it has a strong ability to suppress system parameter changes and external interference.

[0120] Adaptive Part: Because the system contains unknown parameters and disturbances, adaptive mechanisms are introduced to estimate these unknown quantities. By designing appropriate adaptive laws, estimates of the unknown parameters and disturbances are updated in real time and used in the design of the control law. For example, by defining a parameter estimation error, an adaptive law can be designed based on Lyapunov stability theory to ensure that the parameter estimation error converges to a small neighborhood near zero. This allows the controller to continuously adjust its parameters over time to adapt to system changes and external disturbances, thereby improving control performance.

[0121] The adaptive reflective sliding mode controller combines the advantages of backstepping, sliding mode, and adaptive control. It constructs the control law through backstepping design, achieves robustness using the sliding mode surface, and employs an adaptive mechanism to estimate unknowns and adjust control parameters. This allows for better tracking control in the presence of external disturbances, improving system performance, as demonstrated in comparisons with tracking curves from other controllers.

[0122] The process of building a preset simulation model is as follows:

[0123] First, for a given strict feedback nonlinear system, its mathematical model is as described above:

[0124]

[0125] Among them, x i is the system state variable, u is the control input, f i is a known nonlinear function, Δ i represents the nonlinear term caused by uncertain time-varying parameters, d i (t) is an unknown time-varying bounded disturbance, and the control direction is unknown.

[0126] Secondly, dead zone design and parameter estimation

[0127] 1. Construction of dead zone function

[0128] Define the dead zone function z i for:

[0129]

[0130] in, It is an estimate of the equilibrium point based on the system dynamics and expected performance. It is determined by analyzing the prior knowledge of the system and the operating data. i (xi ) is a carefully designed continuous function, usually selected according to the nonlinear characteristics of the system and the control objectives. For example, it can be a polynomial function related to the state variable. Its role is to make a smooth transition of the control input near the dead zone boundary to avoid drastic changes in control. ∈ i is the dead zone width, and its determination needs to comprehensively consider the accuracy requirements and anti-interference ability of the system. i It can improve the control accuracy, but may increase the system's sensitivity to noise and small disturbances; a larger ∈ i This enhances the robustness of the system, but reduces the control accuracy. In practical applications, a lot of simulations and experiments are needed to adjust the appropriate i value.

[0131] 2. Adaptive parameter estimation

[0132] Design an adaptive parameter estimation law to estimate the unknown parameters. Let θ be the unknown parameter vector and use the following adaptive law:

[0133]

[0134] Where Γ is the adaptive gain matrix, which determines the convergence speed and stability of the parameter estimation. A larger Γ value may make the parameter estimation converge faster, but it may also cause the system to become unstable during the estimation process. Therefore, it is necessary to select an appropriate Γ value based on the dynamic characteristics and degree of uncertainty of the system. i (z i ) is a function related to the dead zone function, and its design purpose is to adjust the update rate of the parameter estimation according to the output of the dead zone function. i When it is larger, it indicates that the system deviates far from the equilibrium point, and the update speed of parameter estimation needs to be accelerated. i When it is small, it means that the system is close to the equilibrium point, and the parameter estimation can be appropriately slowed down to avoid over-adjustment. i is a known regression function, which is based on the structure of the system and the known nonlinear function f i Constructed to extract information related to unknown parameters in order to make accurate parameter estimation.

[0135] Finally, control law design and implementation

[0136] Based on the dead zone function and adaptive parameter estimation, the control law u is designed as:

[0137]

[0138] Among them, k z is the feedback gain, which is used to adjust the response strength of the control input to the system state deviation.z value, the system can return to the desired equilibrium point faster, but too large k z This may cause the system to overshoot or even become unstable. Therefore, it is necessary to make a reasonable choice based on the dynamic characteristics and control requirements of the system. and They are f i and Δ i The estimated values ​​of are obtained through adaptive parameter estimation and known system structure information. In the actual implementation process, it is necessary to use numerical calculation methods and computer control systems to calculate the control law u in real time and apply it to the system's actuators.

[0139] In addition, stability analysis and verification

[0140] 1. Lyapunov function construction

[0141] Construct a suitable Lyapunov function V, for example:

[0142]

[0143] Among them, V i Contains the state variable x i and adaptive parameter estimation Related items, such as parameter estimation error:

[0144]

[0145] 2. Derivative Calculation and Boundedness Proof

[0146] Calculate the derivative of the Lyapunov function V along the trajectory of the system Through The analysis and appropriate scaling of the inequality show that under the action of the designed controller and adaptive law, Is negative semidefinite or satisfies certain stability conditions. This requires detailed derivation and analysis using the system's dynamic equations, control laws, and adaptive laws. In the derivation process, the influence of uncertain time-varying parameters and unknown disturbances must be fully considered, and their boundedness conditions must be utilized. By proving From the stability of the closed-loop system, we can conclude that all signals in the closed-loop system are bounded.

[0147] The method described in the embodiment of the present application proposes a robust adaptive design method with a dead zone in the presence of external interference. The algorithm can ensure that the system meets the set LZ interference suppression performance index. For a class of strict feedback nonlinear systems with unknown time-varying control direction, uncertain time-varying parameters and unknown time-varying bounded interference, a robust control method with a dead zone correction algorithm is proposed. This method does not require prior knowledge of the upper and lower bounds of the unknown time-varying control coefficients and upper bound information of uncertain parameters and external interference. The algorithm ensures the boundedness of all signals in the closed-loop system, and at the same time makes the tracking error converge to any small neighborhood of zero. The control strategy in this embodiment can further improve the control accuracy of the servo system, has good control performance, and effectively suppresses the interference caused by system model parameters and the outside world. Therefore, the control strategy controls multiple pulley groups to balance and adjust the lifting tower method. It is practical, effective and feasible.

[0148] The methods described in the above steps are all described in the above embodiments. Please refer to the above description for details and will not be repeated here.

[0149] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0150] Based on the same inventive concept, embodiments of the present application also provide a control device for a transmission tower lifting system, which is used to implement the aforementioned control method for a transmission tower lifting system. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the control device for a transmission tower lifting system provided below can be found in the aforementioned limitations of the control method for a transmission tower lifting system, and will not be further elaborated here.

[0151] In some embodiments, a control device for a transmission tower lifting system is provided, comprising:

[0152] The acquisition module is used to obtain the operating status information and external interference information of the transmission tower lifting system, and to construct a reference curve based on the operating status information and external interference information; the reference curve is used to characterize the changes in the lifting driving force corresponding to the current operating state of the transmission tower lifting system.

[0153] The simulation module is used to input operating status information, external interference information and reference curves into a preset simulation model for simulation to obtain a target tracking curve; the target tracking curve is used to characterize the changes in the corresponding lifting driving force of the transmission tower lifting system in a simulation environment.

[0154] The control module is used to control the lifting and lowering of the transmission tower according to the target tracking curve and the reference curve.

[0155] In some embodiments, the simulation module includes:

[0156] The first simulation unit is used to input the first state information and the reference curve into the first simulation sub-model to obtain a first tracking curve; the first simulation sub-model is a simulation model corresponding to the PID controller; the first state information includes at least one of the current height of the transmission tower, the rope tension in the lifting system, and the drum speed.

[0157] The second simulation unit is used to input the first tracking curve, external interference information and reference curve into the second simulation sub-model to obtain the second tracking curve, and determine the second tracking curve as the target tracking curve; the second simulation sub-model is the simulation model corresponding to the backstepping controller.

[0158] In some embodiments, the simulation module includes:

[0159] The third simulation unit is used to input the second tracking curve, the first state information, the second state information and the reference curve into the third simulation sub-model to obtain the third tracking curve, and determine the third tracking curve as the target tracking curve; the third simulation sub-model is the simulation model corresponding to the sliding mode controller; the second state information includes the angular velocity of the drum.

[0160] In some embodiments, the first simulation unit includes:

[0161] The simulation subunit is used to input the first state information into the first simulation sub-model to obtain an initial tracking curve.

[0162] The comparison subunit is used to compare the initial tracking curve with the reference curve to obtain a comparison result.

[0163] The determining subunit is configured to determine a first tracking curve according to the comparison result.

[0164] In some embodiments, the above-mentioned determination subunit is specifically used to determine the initial tracking curve as the first tracking curve if the comparison result indicates that the initial tracking curve meets the preset requirements; if the comparison result indicates that the initial tracking curve does not meet the preset requirements, adjust the parameters of the first simulation sub-model until the initial tracking curve meets the preset requirements.

[0165] In some embodiments, the control module includes:

[0166] The determination unit is used to determine the error amount according to the target tracking curve and the reference curve.

[0167] The generating unit is used to generate a target driving signal according to the error amount and the historical driving signal.

[0168] The control unit is used to control the lifting and lowering of the transmission tower according to the target driving signal.

[0169] Each module in the control device for the transmission tower lifting system can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each module.

[0170] In some embodiments, a computer device is provided. The computer device can be a terminal or a server. The internal structure diagram thereof can be as follows: Figure 11As shown, the computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via wired or wireless communication, and the wireless communication can be achieved via Wi-Fi, a mobile cellular network, NFC (near-field communication), or other technologies. When executed by the processor, the computer program implements a control method for a transmission tower lifting system. The display unit of the computer device is used to form a visually visible image, and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0171] Those skilled in the art will understand that Figure 11 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0172] In some embodiments, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps of the control method of the transmission tower lifting system described in any of the above embodiments are implemented.

[0173] In some embodiments, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the control method of the transmission tower lifting system described in any of the above embodiments are implemented.

[0174] In some embodiments, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps of the method for controlling a transmission tower lifting system described in any of the above embodiments.

[0175] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0176] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0177] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A control method for a transmission tower lifting system, characterized in that: The method comprises: Acquiring operating status information and external interference information of the transmission tower lifting system, and constructing a reference curve based on the operating status information and the external interference information; the reference curve is used to represent changes in the lifting driving force corresponding to the current operating state of the transmission tower lifting system; Inputting the operating state information, the external interference information and the reference curve into a preset simulation model for simulation to obtain a target tracking curve; the target tracking curve is used to characterize the change in the corresponding lifting driving force of the transmission tower lifting system under the simulation environment; The lifting and lowering of the transmission tower is controlled according to the target tracking curve and the reference curve.

2. The method according to claim 1, characterized in that The operating state information includes first state information, the preset simulation model includes a first simulation sub-model and a second simulation sub-model, and the operating state information, the external interference information, and the reference curve are input into the preset simulation model for simulation to obtain a target tracking curve, including: Inputting the first state information and the reference curve into the first simulation sub-model to obtain a first tracking curve; the first simulation sub-model is a simulation model corresponding to the PID controller; the first state information includes at least one of the current height of the transmission tower, the rope tension in the lifting system, and the drum speed; The first tracking curve, the external interference information and the reference curve are input into the second simulation sub-model to obtain a second tracking curve, and the second tracking curve is determined as the target tracking curve; the second simulation sub-model is a simulation model corresponding to the backstepping controller.

3. The method according to claim 2, characterized in that The operating state information further includes second state information, the preset simulation model further includes a third simulation sub-model, and the method further includes: The second tracking curve, the first state information, the second state information and the reference curve are input into the third simulation sub-model to obtain a third tracking curve, and the third tracking curve is determined as the target tracking curve; the third simulation sub-model is a simulation model corresponding to the sliding mode controller; the second state information includes the angular velocity of the drum.

4. The method according to claim 2, characterized in that The step of inputting the first state information and the reference curve into the first simulation sub-model to obtain a first tracking curve includes: Inputting the first state information into the first simulation sub-model to obtain an initial tracking curve; Comparing the initial tracking curve with the reference curve to obtain a comparison result; The first tracking curve is determined according to the comparison result.

5. The method according to claim 4, characterized in that Determining the first tracking curve according to the comparison result includes: If the comparison result indicates that the initial tracking curve meets the preset requirement, determining the initial tracking curve as the first tracking curve; If the comparison result indicates that the initial tracking curve does not meet the preset requirements, the parameters of the first simulation sub-model are adjusted until the initial tracking curve meets the preset requirements.

6. The method according to any one of claims 1 to 5, characterized in that The step of controlling the lifting of the transmission tower according to the target tracking curve and the reference curve includes: determining an error amount according to the target tracking curve and the reference curve; generating a target driving signal according to the error amount and the historical driving signal; The lifting and lowering of the transmission tower is controlled according to the target driving signal.

7. A control device for a transmission tower lifting system, characterized in that: The device comprises: an acquisition module, configured to acquire operating status information and external interference information of the transmission tower lifting system, and construct a reference curve based on the operating status information and the external interference information; the reference curve is used to represent changes in the lifting driving force corresponding to the current operating state of the transmission tower lifting system; A simulation module is configured to input the operating status information, the external interference information, and the reference curve into a preset simulation model for simulation to obtain a target tracking curve; the target tracking curve is configured to represent changes in the corresponding lifting driving force of the transmission tower lifting system under a simulation environment; The control module is used to control the lifting and lowering of the transmission tower according to the target tracking curve and the reference curve.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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