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

Abstract

The application relates to a control method, device and equipment of a power transmission tower lifting system, a storage medium and a program product. The method obtains operation state information and external interference information of the power transmission tower lifting system, constructs a reference curve according to the operation state information and the external interference information, inputs 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 controls the lifting of the power transmission tower according to the target tracking curve and the reference curve. In the above method, the system can realize real-time sensing of the influence of external interference on the lifting driving force by combining the target tracking curve and the reference curve. When the actual required lifting driving force deviates from the reference curve due to external interference, the target tracking curve can control the lifting system to timely adjust the lifting driving force according to the deviation, so that the lifting of the power transmission tower can be accurately controlled.

Description

Technical Field

[0001] This 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 power transmission tower lifting system. Background Technology

[0002] In the power transmission sector, transmission towers are crucial infrastructure, generally quite tall. With the continuous expansion of power grids and technological upgrades, the installation, maintenance, and component replacement of these towers have become increasingly important. These tasks are not only key to ensuring the stable operation of the power grid but also directly impact the reliability and security of power supply. Therefore, precise control of tower raising and lowering is particularly vital in current power construction and maintenance work.

[0003] Currently, the raising and lowering of steel towers often relies heavily on manpower and simple mechanical tools. The operation process is cumbersome, requiring a significant investment of time and effort for each raising and lowering operation, severely impacting work progress. Furthermore, steel towers are prone to swaying and tilting during raising and lowering, which not only significantly increases the safety risks faced by workers but can also damage the tower itself, affecting its lifespan and performance. Traditional raising and lowering methods face even greater challenges, especially in mountainous areas with significant terrain variations and rugged roads, as well as in regions with complex topography.

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

[0005] Therefore, it is necessary to provide a control method, device, equipment, storage medium, and program product for a power transmission tower lifting system that can accurately control the lifting and lowering of power transmission towers, addressing the aforementioned technical problems.

[0006] In a first aspect, this application provides a control method for a power transmission tower hoisting system, the method comprising:

[0007] The system acquires the operating status information and external interference information of the transmission tower lifting system, and constructs a reference curve based on the operating status information and external interference information; the reference curve is used to characterize the change of the lifting driving force of the transmission tower lifting system under the current operating status.

[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 change of the lifting driving force of the transmission tower lifting system in the simulation environment.

[0009] The raising and lowering of the transmission tower is controlled based on the target tracking curve and the reference curve.

[0010] In one embodiment, the operating status information includes first status information, and the preset simulation model includes a first simulation sub-model and a second simulation sub-model. 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, including:

[0011] The first state information and the reference curve are input into the first simulation sub-model to obtain the first tracking curve; the first simulation sub-model is the simulation model corresponding to the PID controller; the first state information includes at least one of the following: the current height of the transmission tower, the rope tension in the hoisting 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, which is then 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 running status information further includes second status 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 drum angular velocity.

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

[0016] The first state information is input into the first simulation sub-model to obtain the initial tracking curve;

[0017] The initial tracking curve and the reference curve are compared to obtain the comparison results;

[0018] The first tracking curve is determined based on the comparison results.

[0019] In one embodiment, determining a first tracking curve based on the comparison results includes:

[0020] If the comparison results indicate that the initial tracking curve meets the preset requirements, then the initial tracking curve will be determined as the first tracking curve.

[0021] If the comparison results indicate 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 the transmission tower based on 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 the target driving signal based on the error amount and historical driving signals;

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

[0026] Secondly, this application also provides a control device for a power transmission tower hoisting system, the device comprising:

[0027] The acquisition module is used to acquire 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 change of the lifting driving force of the transmission tower lifting system under the current operating status.

[0028] 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 the target tracking curve; the target tracking curve is used to characterize the change of lifting driving force of the transmission tower lifting system in the simulation environment;

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

[0030] Thirdly, this application also provides a computer device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0031] The system acquires the operating status information and external interference information of the transmission tower lifting system, and constructs a reference curve based on the operating status information and external interference information; the reference curve is used to characterize the change of the lifting driving force of the transmission tower lifting system under the current operating status.

[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 characterize the change of the lifting driving force of the transmission tower lifting system in the simulation environment;

[0033] The raising and lowering of the transmission tower is controlled based on the target tracking curve and the reference curve.

[0034] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0035] The system acquires the operating status information and external interference information of the transmission tower lifting system, and constructs a reference curve based on the operating status information and external interference information; the reference curve is used to characterize the change of the lifting driving force of the transmission tower lifting system under the current operating status.

[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 characterize the change of the lifting driving force of the transmission tower lifting system in the simulation environment;

[0037] The raising and lowering of the transmission tower is controlled based on the target tracking curve and the reference curve.

[0038] Fifthly, this application also provides a computer program product, which includes a computer program that, when executed by a processor, performs the following steps:

[0039] The system acquires the operating status information and external interference information of the transmission tower lifting system, and constructs a reference curve based on the operating status information and external interference information; the reference curve is used to characterize the change of the lifting driving force of the transmission tower lifting system under the current operating status.

[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 characterize the change of the lifting driving force of the transmission tower lifting system in the simulation environment;

[0041] The raising and lowering of the transmission tower is controlled based on the target tracking curve and the reference curve.

[0042] The aforementioned control method, device, equipment, storage medium, and program product for a power transmission tower lifting system involve acquiring the operating status information and external interference information of the power transmission tower lifting system, constructing a reference curve based on these information, and then inputting 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 and lowering of the power transmission tower is controlled based on the target tracking curve and the reference curve. In this 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 during lifting, tower tilting, or even collapse caused by interference, ensuring the safety of operators and the surrounding environment, and thus enabling precise control of the lifting and lowering of the power transmission tower. Attached Figure Description

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

[0044] Figure 2 This is one of the flowcharts illustrating the control method for a power transmission tower lifting system in one embodiment;

[0045] Figure 3 This is a second flowchart illustrating the control method for a power transmission tower lifting system in one embodiment.

[0046] Figure 4 This is a schematic diagram illustrating the correspondence between the reference signal and the PID signal in one embodiment;

[0047] Figure 5 This is the third flowchart illustrating the control method for a power transmission tower lifting system in one embodiment;

[0048] Figure 6 This is a schematic diagram illustrating the correspondence between the reference signal and the backstepping signal in one embodiment;

[0049] Figure 7 This is the fourth flowchart illustrating the control method of the transmission tower lifting system in one embodiment;

[0050] Figure 8 This is a schematic diagram illustrating the correspondence between the reference signal and the adaptive robust signal in one embodiment;

[0051] Figure 9 This is a schematic diagram illustrating the correspondence between PID signals, backstepping signals, and adaptive robust signals in one embodiment.

[0052] Figure 10 This is a flowchart of the control method for a power transmission tower lifting system in one embodiment (Figure 4-5).

[0053] Figure 11 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0055] In the power transmission sector, transmission towers, as crucial infrastructure, are generally quite tall. With the continuous expansion of the power grid and technological upgrades, the installation, maintenance, and component replacement of these towers have become increasingly important. These tasks are not only key to ensuring the stable operation of the power grid but also directly impact the reliability and security of power supply. Therefore, precise control of tower raising and lowering is paramount in current power construction and maintenance work. Currently, tower raising and lowering often relies heavily on manpower and simple mechanical tools, resulting in cumbersome procedures and requiring significant time and effort for each operation, severely impacting work progress. Furthermore, towers are prone to swaying and tilting during raising and lowering, significantly increasing safety risks for workers and potentially damaging the towers themselves, thus affecting their lifespan and performance. Traditional raising and lowering methods face even greater challenges, especially in mountainous areas with significant terrain undulations and rugged roads, as well as in regions with complex topography. Therefore, how to precisely control the raising and lowering of transmission towers has become an urgent problem to be solved in the current power transmission sector.

[0056] In view of this, embodiments of this application propose a control method, device, equipment, storage medium, and program product for a power transmission tower lifting system. By combining the operating status information of the power transmission tower lifting system with external interference information, the lifting and lowering of the power transmission tower can be precisely controlled.

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

[0058] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0059] In some embodiments, the control method for the transmission tower lifting system provided in this application can be applied to, for example... Figure 1The application environment shown includes a control device 101 and a power transmission tower lifting system (hereinafter referred to as the lifting system) 102. The lifting system 102 includes a servo winch system 1021, multiple pulley blocks 1022, and a power 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 blocks 1022, and the multiple pulley blocks 1022 are also connected to the power transmission tower 1023. The control device 101 is used to acquire the operating status information and external interference information of the power transmission tower lifting system, and then outputs control signals based on the operating status information and external interference information to control the lifting and lowering of the power transmission tower. The servo winch system 1021 controls the lifting and lowering of the power transmission tower 1023 by controlling the rotation of the multiple pulley blocks 1022. The control device 101 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices.

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

[0061] In some embodiments, such as Figure 2 As shown, a control method for a power transmission tower hoisting system is provided, which is applied to... Figure 1 Taking the control equipment in the example, the explanation includes the following steps:

[0062] S201: Obtain the operating status information and external interference information of the power transmission tower lifting system, and construct a reference curve based on the operating status information and external interference information.

[0063] The reference curve characterizes the change in lifting driving force of the transmission tower hoisting system under its current operating conditions. Operating status information includes at least one of the following: the current height of the transmission tower, rope tension in the hoisting system, drum rotation speed, and drum angular velocity. External disturbance information includes wind resistance, mechanical vibration, and friction between components of the hoisting system.

[0064] In this embodiment, the control device can acquire 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, it can acquire the current height of the transmission tower using a rangefinder; acquire the rope tension in the lifting system using a tension sensor; acquire the drum rotation speed and drum angular velocity using a speed sensor; measure wind speed and direction using an anemometer and wind vane, and then input the wind speed and direction into a preset wind resistance calculation formula to calculate the current wind resistance; acquire mechanical vibration using an accelerometer; and indirectly measure the frictional force between the lifting system components 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 plot it as a reference curve. The preset mathematical model can be constructed based on the physical principles and historical data of the transmission tower lifting system, and it is used to describe the relationship between the lifting driving force and the operating status information and external interference information.

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

[0066] The target tracking curve is used to characterize the change in lifting driving force of the transmission tower hoisting system under the simulation environment. The preset simulation model includes at least one of the following: 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 this embodiment, a preset simulation model can be constructed in advance 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 reference curve of the power 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 curves output by the PID controller, the backstepping controller, and the sliding mode controller. Then, the curves output by the PID controller, the backstepping controller, and the sliding mode controller are compared and analyzed with the reference curve to determine the target tracking curve.

[0068] S203 controls the raising and lowering of the transmission tower based on the target tracking curve and the reference curve.

[0069] In this embodiment of the 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 quantity based on the error analysis results, and finally control the raising and lowering of the transmission tower according to the control quantity.

[0070] The control method for a power transmission tower lifting system provided in this application acquires the operating status information and external interference information of the power transmission tower lifting system, constructs a reference curve based on the operating status information and external interference information, and 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. Finally, the lifting and lowering of the power transmission tower is controlled according to 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 during the lifting process, tower tilting, or even collapse caused by interference, ensuring the safety of operators and the surrounding environment, and thus enabling precise control of the lifting and lowering of the power transmission tower.

[0071] In some embodiments, the aforementioned operating status information includes first status information, and the preset simulation model includes a first simulation sub-model and a second simulation sub-model. Based on this, a specific implementation method for obtaining the target tracking curve is also provided, such as... Figure 3 As shown, the phrase "inputting the operating status information, external interference information, and reference curve into the preset simulation model for simulation to obtain the target tracking curve" in S202 above includes:

[0072] S301, input the first state information and reference curve into the first simulation sub-model to obtain the first tracking curve.

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

[0074] In this embodiment, 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 power transmission tower lifting system over a period of time based on the above steps, the first state information in the operating status information can be input into the first simulation sub-model for simulation to obtain the first tracking curve.

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

[0076] S3011, input the first state information into the first simulation sub-model to obtain the initial tracking curve.

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

[0078] S3012 compares the initial tracking curve with the reference curve to obtain the comparison results.

[0079] The comparison results include whether the initial tracking curve meets the preset requirements, or whether the initial tracking curve does not meet the preset requirements. The preset requirements can be determined based on the reference curve.

[0080] In this embodiment, after obtaining the initial tracking curve, the control device 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. Further, it can be determined whether the error value of each point is less than a preset error threshold. If the error value of all points is less than the preset error threshold, it indicates that the initial tracking curve meets the preset requirements. If the error value of any point 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 according to actual accuracy requirements.

[0081] S3013, determine the first tracking curve based on the comparison results.

[0082] In this embodiment of the 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 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.

[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; see [link to relevant documentation] for details. Figure 6 As shown in the figure, the vertical axis represents the driving force, and the horizontal axis represents time.

[0085] In this embodiment, a second simulation sub-model can be pre-constructed based on the 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 the second tracking curve, and the second tracking curve can be determined as the target tracking curve.

[0086] Optional, in Figure 3 Based on this, the above-mentioned operational status information also includes second status 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 the third tracking curve, and determine the third tracking curve as the target tracking curve.

[0088] The operating status information includes second-state information, and the preset simulation model includes a third-state sub-model. The third-state sub-model is the simulation model corresponding to the sliding mode controller (adaptive robust controller); the second-state information includes the drum angular velocity. The third tracking curve represents the relationship between the reference signal and the adaptive robust signal; see [link to documentation] for details. Figure 8 As shown in the figure, the vertical axis represents driving force, and the horizontal axis represents 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 diaphragm controller can be found in [reference needed]. Figure 9 As shown in the figure, the vertical axis represents the driving force, and the horizontal axis represents time.

[0089] In this embodiment, 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 the 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 raising and lowering of transmission towers is also provided, such as... Figure 10 As shown, the "controlling the raising and lowering of the transmission tower according to the target tracking curve and the reference curve" in S203 above includes:

[0091] S401, determine the error amount based on the target tracking curve and the reference curve.

[0092] In this embodiment of the application, after the control device obtains the target tracking curve and the reference curve, it can compare the target tracking curve and the reference curve. Specifically, it can compare each point on the target tracking curve with the corresponding point on the reference curve to determine the error value of each point. Furthermore, it can determine the error amount based on the error value of each point. Specifically, it can construct an error matrix or error vector based on the error value of each point, and then determine the error amount based on the error matrix or error vector.

[0093] S402 generates the target drive signal based on the error amount and historical drive signals.

[0094] Among them, the historical drive signal is the drive signal of the previous drive of the lifting system. The target drive signal is the drive signal of the current drive of the lifting system.

[0095] In this embodiment of the application, after the control device obtains the error amount based on the above steps, it can acquire the previous drive signal from the historical drive signals, and then sum the previous drive signal with the drive signal corresponding to the error amount to obtain the target drive signal.

[0096] S403 controls the raising and lowering of the power transmission tower based on the target drive signal.

[0097] In this embodiment, 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 and lowering of the transmission tower. In summary, a control method for a transmission tower lifting system is also provided, comprising:

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

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

[0100] S503 compares the initial tracking curve with the reference curve to obtain the comparison results.

[0101] S504, if the comparison result indicates that the initial tracking curve meets the preset requirements, then the initial tracking curve is determined as the first tracking curve.

[0102] S505, if the comparison results indicate that the initial tracking curve does not meet the preset requirements, then adjust the parameters of the first simulation sub-model until the initial tracking curve meets the preset requirements.

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

[0104] 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 the third tracking curve, which is then designated 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 characterize the change in the lifting driving force of the transmission tower lifting system under the simulation environment.

[0105] S508 determines the error amount based on the target tracking curve and the reference curve.

[0106] S509 generates the target drive signal based on the error amount and historical drive signals.

[0107] S510 controls the raising and lowering of the power transmission tower based on the target drive signal.

[0108] In this embodiment, a separate PID control experiment is first conducted to obtain the tracking curve. Then, the tracking curve is obtained by switching to a backstepping controller. Finally, an adaptive backstepping sliding mode controller is used for the experiment. A horizontal comparison of the three figures shows that external interference has a certain impact on the system's tracking performance, with severe waveform distortion appearing in some areas. It can be seen that in the presence of external interference, the performance of the PID controller is inferior to that of the nonlinear controller, and there is a certain amplitude and phase difference between the given reference signal and the actual feedback value. Among these two nonlinear controllers, the adaptive backstepping sliding mode controller shows a slightly improved control effect compared to simple single backstepping control. That is, the adaptive parameters, the estimated interference force, and the designed sliding mode have a certain effect on improving system performance.

[0109] The process of constructing a pre-defined simulation model is as follows:

[0110] (1) A PID controller is a common feedback controller. It processes the error signal through three parts: proportional (P), integral (I), and derivative (D), thereby generating a control output. Proportional (P): Outputs the control quantity proportionally to the current error value (the difference between the setpoint and the actual feedback value). The larger the proportional coefficient, the faster the system responds to the error, but it may lead to increased overshoot and decreased stability. Integral (I): Integrates the error, its function being to eliminate the steady-state error of the system. As time accumulates, the integral term gradually increases, forcing the system output closer to the setpoint until the error is zero. However, excessively strong integral action may lead to a slower system response and increased overshoot. Derivative (D): Outputs the control quantity based on the rate of change of the error. It can predict the trend of error change and provide control action in advance, thereby improving the dynamic performance of the system, such as reducing overshoot and shortening the settling time. However, the derivative is more sensitive to noise and easily amplifies high-frequency noise.

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

[0112] In practice, adjusting the values ​​of proportional coefficient Kp, integral coefficient Ki, and derivative coefficient Kd can alter the performance of the PID controller, thus affecting the formation of the tracking curve. For example, increasing Kp makes the curve respond quickly when an error occurs, but may lead to overshoot; increasing Ki can reduce steady-state error, but may slow down the system response; increasing Kd can improve the dynamic performance of the system, but the influence of noise must be considered. The changing trends of the tracking curves obtained in experiments (such as rise time, overshoot, steady-state error, etc.) 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 parameters of the PID controller can be optimized to achieve better control performance. The PID controller, connected to other parts of the system, obtains reference and feedback signals, calculates the control quantity and generates the drive signal according to the PID control principle, and its control effect can be intuitively reflected by the tracking curve, which is closely related to the mathematical formula of PID control.

[0113] (2) After completing the individual PID control experiment and obtaining its tracking curve, the experiment will be switched to the backstepping controller to compare the performance of different control methods in dealing with external disturbances. When further optimization of the control effect is required, especially when higher system performance requirements are needed (such as smaller following error, better anti-interference capability, etc.), the experiment will be switched to the adaptive backstepping sliding mode controller. This switching is to systematically evaluate and compare the performance of different control strategies in the servo winch system.

[0114] A backstepping controller is a type of controller used in experiments following PID control experiments. Its connection to the overall system is likely similar to that of a PID controller; it is connected to a real-time control system, monitoring system, servo winch system, etc., receiving reference and feedback signals and outputting 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 progressively designs virtual control laws, and then designs actual control laws for each subsystem through a "backward" approach. For a system of the form x1 = x2 + f1(x1), For a second-order, nonlinear system (where x1 and x2 are system states, u is the control input, and f1 and f2 are nonlinear functions), the first step is to define a virtual control variable α1 such that x1 can track the desired trajectory x1d, i.e., design... Where k1 is a positive constant, the solution is... The second step is to define the error z2 = x2 - α1, then differentiate z2, and design a control law u such that z2 converges quickly to zero. Through a series of derivations and calculations, the final expression of the control law can be obtained. In the design process of the backstepping controller, system and external disturbances can be considered, and appropriate methods (such as introducing 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 of backstepping control involves a series of mathematical formula derivations, including the calculation of derivatives of state variables and the derivation of expressions for virtual and actual control laws. These formulas embody the principles and methods of backstepping control. Through the analysis and mathematical calculations of the system model, control law formulas that can achieve system stability and tracking control are obtained. For example, in the second-order system example above, the expression of the control law obtained 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, the desired trajectory, and the system's nonlinear function to achieve effective system control. Corresponding to the tracking curve obtained from the experiment in the figure, different control law formulas (i.e., different controller designs) lead to different tracking performances. By comparing the tracking curves, the advantages of the backstepping controller over the PID controller in dealing with external disturbances can be intuitively seen.

[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 should be similar to the previous two controllers, connected to the real-time control system, monitoring system, servo winch system, etc. It receives reference and feedback signals and outputs control signals to drive the servo winch. However, its internal control algorithm and structure are different.

[0118] Backstepping control section: Similar to the backstepping controller mentioned earlier, the complex nonlinear system is decomposed into multiple subsystems. Starting from the outermost layer, the control law is designed step-by-step by defining virtual control variables. For example, for a nonlinear system, a virtual control law is designed for the first subsystem, enabling it to track the desired trajectory. Then, an error variable is defined, and a 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 recursive, building the entire control system by continuously "bounced back."

[0119] Sliding mode control: The core idea of ​​sliding mode control is to design a sliding surface (usually a function of the system state) such that the system state reaches the sliding surface in a finite time and moves along the sliding surface to the equilibrium point. For example, for a second-order system, the sliding surface can be designed as follows: (where ∈ represents the tracking error, and c is a positive constant). Then, by designing the control law u, such that... This ensures that the system state can reach the sliding surface within a finite time and remain in motion on it, thereby achieving robust control of the system, that is, it has a strong ability to suppress changes in system parameters and external disturbances.

[0120] Adaptive Component: Due to the presence of unknown parameters and disturbances in the system, an adaptive mechanism is introduced to estimate these unknowns. By designing a suitable adaptive law, the estimates of unknown parameters and disturbances are updated in real time, and these estimates are used in the design of the control law. For example, a parameter estimation error can be defined, and then an adaptive law can be designed based on Lyapunov stability theory, allowing the parameter estimation error to converge to a small neighborhood near zero. In this way, over time, the controller can continuously adjust its parameters to adapt to changes in the system and external disturbances, thereby improving control performance.

[0121] The adaptive reflective sliding mode controller combines the advantages of backstepping control, sliding mode control, and adaptive control. It constructs the control law through backstepping design, achieves robustness using a sliding surface, and estimates unknowns and adjusts control parameters using an adaptive mechanism. This allows for better tracking control of the system even under external disturbances, improving system performance, as evidenced by comparisons of tracking curves with other controllers.

[0122] The process of constructing a pre-defined simulation model is as follows:

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

[0124]

[0125] Where, x i Here, u is the system state variable, f is the control input, and f is the system state variable. i Given a known nonlinear function, Δ i d represents the nonlinear term introduced by the uncertain time-varying parameters. i (t) represents 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-time functions

[0128] Define the dead-time function z i for:

[0129]

[0130] in, It is an estimate of the equilibrium point based on system dynamics and expected performance. It is determined through analysis of prior knowledge of the system and operational data. ρ i (xi ) is a carefully designed continuous function, typically chosen based on the system's nonlinear characteristics and control objectives. For example, it could be a polynomial function related to the state variables, its purpose being to smoothly transition the control input near the dead zone boundary, avoiding drastic changes in control. ∈ i This is the dead zone width, and its determination requires comprehensive consideration of the system's accuracy requirements and anti-interference capabilities. Smaller ∈ i It can improve control accuracy, but may increase the system's sensitivity to noise and small disturbances; larger ∈ i This enhances the system's robustness but reduces control precision. In practical applications, extensive simulations and experiments are needed to fine-tune the appropriate ∈ [the system's parameters]. i value.

[0131] 2. Adaptive parameter estimation

[0132] We design an adaptive parameter estimation law to estimate the unknown parameters. Let θ be the vector of unknown parameters, and adopt the following adaptive law:

[0133]

[0134] Here, Γ is the adaptive gain matrix, which determines the convergence speed and stability of parameter estimation. A larger Γ value may lead to faster convergence, but it may also cause instability in the system during the estimation process. Therefore, an appropriate Γ value needs to be selected based on the dynamic characteristics and degree of uncertainty of the system. τ i (z i ) is a function related to the dead-zone function, designed to adjust the update rate of parameter estimates based on the output of the dead-zone function. When z i When z is large, it indicates that the system deviates far from the equilibrium point, and in this case, it is necessary to speed up the update speed of parameter estimation; when z i When the value is small, it indicates that the system is close to the equilibrium point, and the parameter estimation can appropriately slow down the update rate to avoid over-adjustment. φ i It is a known regression function, based on the system structure and the known nonlinear function f. i It is constructed to extract information related to unknown parameters in order to make accurate parameter estimation.

[0135] Finally, the design and implementation of the control law.

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

[0137]

[0138] Where, k z This is the feedback gain, and its function is to adjust the response strength of the control input to system state deviations. By appropriately increasing k...z A value of k can allow the system to return to the desired equilibrium point more quickly, but an excessively large k... z This could lead to system overshoot or even instability. Therefore, a reasonable selection needs to be made based on the system's dynamic characteristics and control requirements. and They are f i and Δ i The estimated values ​​are obtained through adaptive parameter estimation and known system structure information. In practical implementation, numerical calculation methods and computer control systems are needed 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. Construction of Lyapunov functions

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

[0142]

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

[0144]

[0145] 2. Derivative calculation and boundedness proof

[0146] Calculate the derivative of the Lyapunov function V along the system trajectory. Through the Through analysis and appropriate inequality scaling, it is proven that under the action of the designed controller and adaptive law, It is either negative semi-definite or satisfies certain stability conditions. This requires detailed derivation and analysis using the system's dynamic equations, control laws, and adaptive laws. During the derivation, the effects of uncertain time-varying parameters and unknown disturbances must be fully considered, and their boundedness conditions must be utilized. This is proven through... Based on 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 this application proposes a robust adaptive design method with a dead zone in the presence of external interference. This algorithm ensures that the system meets the set LZ interference suppression performance index. For a class of strictly 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, nor information on the upper bounds of uncertain parameters and external interference. The algorithm guarantees the boundedness of all signals in the closed-loop system, while ensuring that the tracking error converges to any small neighborhood of zero. The control strategy in this embodiment can further improve the control accuracy of the servo system, exhibiting good control performance and effectively suppressing interference from system model parameters and external factors. Therefore, this control strategy for controlling multiple pulley groups to balance and adjust the lifting tower is practically effective and feasible.

[0148] The methods described in each of the above steps have been described in the foregoing embodiments. For details, please refer to the foregoing descriptions. They will not be repeated here.

[0149] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

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

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

[0152] The acquisition module is used to acquire the 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 characterize the change of the lifting driving force of the transmission tower lifting system under the current operating status.

[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 the target tracking curve. The target tracking curve is used to characterize the change of lifting driving force of the transmission tower lifting system in the simulation environment.

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

[0155] In some embodiments, the simulation module described above 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 the first tracking curve; the first simulation sub-model is the 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 hoisting 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 to 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 described above 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 to 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 drum angular velocity.

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

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

[0162] The comparison sub-unit is used to compare the initial tracking curve with the reference curve to obtain the comparison result.

[0163] The sub-unit is determined to identify the first tracking curve based on the comparison results.

[0164] In some embodiments, the aforementioned determining sub-unit 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; and to adjust the parameters of the first simulation sub-model until the initial tracking curve meets the preset requirements if the comparison result indicates that the initial tracking curve does not meet the preset requirements.

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

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

[0167] The generation unit is used to generate the target driving signal based on the error amount and historical driving signals.

[0168] The control unit is used to control the raising and lowering of the power transmission tower according to the target drive signal.

[0169] The various modules in the control device of the aforementioned power transmission tower lifting system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device 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, which may be a terminal or a server, and its internal structure diagram may be as follows. Figure 11As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and 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 also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a control method for a power transmission tower lifting system. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

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

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

[0173] In some embodiments, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the control method for the transmission tower lifting system described in any of the above embodiments.

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

[0175] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can 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 can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0176] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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 embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A control method for a power transmission tower lifting system, characterized in that, The method includes: The system acquires the operating status information and external interference information of the power transmission tower lifting system, and constructs a reference curve based on the operating status information and the external interference information; the reference curve is used to characterize the change of the lifting driving force of the power transmission tower lifting system under the current operating status. The operating status information, the external interference information, and the reference curve are input into a preset simulation model for simulation to obtain the target tracking curve; the target tracking curve is used to characterize the change of the lifting driving force of the power transmission tower lifting system in the simulation environment; The raising and lowering of the transmission tower is controlled based on the target tracking curve and the reference curve; The operating status information includes first status information, and the preset simulation model includes a first simulation sub-model and a second simulation sub-model. The step of inputting the operating status information, the external interference information, and the reference curve into the preset simulation model for simulation to obtain the target tracking curve includes: The first state information is input into the first simulation sub-model to obtain an initial tracking curve; the initial tracking curve is compared with the reference curve to obtain a comparison result; the first tracking curve is determined based on the comparison result; the first simulation sub-model is the 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 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.

2. The method according to claim 1, characterized in that, The operating status information also includes second status information, the preset simulation model also 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 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 drum angular velocity.

3. The method according to claim 1, characterized in that, Determining the first tracking curve based on the comparison result includes: If the comparison result indicates that the initial tracking curve meets the preset requirements, then 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.

4. The method according to any one of claims 1-3, characterized in that, The step of controlling the raising and lowering of the transmission tower based on the target tracking curve and the reference curve includes: The error amount is determined based on the target tracking curve and the reference curve; Based on the error amount and historical driving signals, a target driving signal is generated; The raising and lowering of the power transmission tower is controlled according to the target drive signal.

5. A control device for a power transmission tower lifting system, characterized in that, For implementing the control method of the power transmission tower hoisting system as described in claim 1, the device comprises: The acquisition module is used to acquire the operating status information and external interference information of the power 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 characterize the change of the lifting driving force of the power transmission tower lifting system under the current operating status; The simulation module is used to input the operating status information, the external interference information, and the reference curve into a preset simulation model for simulation to obtain the target tracking curve; the target tracking curve is used to characterize the change of the lifting driving force of the power transmission tower lifting system in the simulation environment; The control module is used to control the raising and lowering of the transmission tower based on the target tracking curve and the reference curve.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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