Adaptive adjustment method for a host device
By adaptively adjusting the communication rate and sampling frequency, and combining filtering algorithms to optimize data transmission parameters, the problem of data errors and loss caused by frequency interference in industrial control products is solved, achieving more efficient data transmission and system stability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HONEYWELL ENVIRONMENTAL & COMBUSTION CONTROLS (TIANJIN) CO LTD
- Filing Date
- 2025-01-20
- Publication Date
- 2026-07-21
Smart Images
Figure CN122437784A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of data communication, and more specifically, to an adaptive adjustment method for a master control device, an electronic device, and a computer-readable storage medium. Background Technology
[0002] The current operating environment of industrial control products is filled with interference signals of various frequencies. When acquiring large fluctuations in data such as room temperature, indoor pressure, and inverter operating temperature via communication, these interference signals can cause a series of communication problems, including electromagnetic interference, co-channel interference, and frequency deviation interference. Due to the intervention of these interferences, data is prone to errors or even loss during transmission, ultimately leading to product control failure.
[0003] Therefore, it is currently necessary to adaptively adjust the communication rate and sampling frequency to reduce interference during data transmission, thereby ensuring accurate data transmission and stable product control. Summary of the Invention
[0004] According to one aspect of this application, an adaptive adjustment method for a master control device is provided, the method comprising the following steps: a) the master control device receives sampled data based on a first communication rate and a first sampling frequency, and calculates the sampled data to generate a first data failure rate; b) in response to a situation where the first data failure rate is greater than a preset failure rate threshold and the first sampling frequency has not been adjusted, the master control device adjusts the first sampling frequency to generate a second sampling frequency; c) the master control device receives the sampled data based on the first communication rate and the second sampling frequency, and calculates the sampled data to generate a second data failure rate, and in response to a situation where the second data failure rate is greater than the preset failure rate threshold and the first sampling frequency has been adjusted, the master control device adjusts the first communication rate to generate a second communication rate; and d) the master control device receives the sampled data based on the second communication rate and the second sampling frequency, and calculates the sampled data to generate a third data failure rate.
[0005] The adaptive adjustment method, for example or additionally, further includes adjusting the first sampling frequency to generate the second sampling frequency by using a binary search method to adjust the first sampling frequency to generate the second sampling frequency, while ensuring that the second sampling frequency is within a preset sampling frequency extreme range.
[0006] The adaptive adjustment method, as an example or additionally, further includes the master control device adjusting the first communication rate to generate the second communication rate by: adjusting the first communication rate based on the difference between the second data failure rate and the first data failure rate to generate the second communication rate, while ensuring that the second communication rate is within a preset communication rate extreme range.
[0007] The adaptive adjustment method, for example or additionally, includes adjusting the first communication rate based on the difference between the second data failure rate and the first data failure rate to generate the second communication rate, comprising: adjusting the first communication rate using an adjustment coefficient corresponding to the difference to generate the second communication rate.
[0008] The adaptive adjustment method, for example or additionally, step c) further includes: after the master control device adjusts the first communication rate to generate the second communication rate, the master control device restarts the serial drive.
[0009] The adaptive adjustment method, for example or additionally, records the current data failure rate and the current communication rate and current sampling frequency corresponding to the current data failure rate after each data failure rate is generated, in order to form a historical database.
[0010] The adaptive adjustment method, for example or additionally, further includes the following steps: e) selecting a communication rate and sampling frequency corresponding to the lowest data failure rate from the historical database in response to any of the following conditions, and stopping the execution of steps a)-d): the second communication rate is outside the preset communication rate extreme range, and the second sampling frequency is outside the preset sampling frequency extreme range.
[0011] The adaptive adjustment method, for example or additionally, further includes the following step: f) smoothing the sampled data based on a filtering algorithm.
[0012] In the aforementioned adaptive adjustment method, for example or additionally, the data failure rate is the percentage of sampled data that exhibits anomalies.
[0013] An electronic device is also provided, comprising a memory and a processor, the memory storing program instructions, wherein the processor, when executing the program instructions, performs the adaptive adjustment method according to one aspect of this application.
[0014] The electronic device, for example or additionally, includes a microcontroller unit, in which the processor is disposed.
[0015] A computer-readable storage medium is also provided, the computer-readable storage medium storing instructions that, when executed by a processor, implement the adaptive adjustment method according to one aspect of this application. Attached Figure Description
[0016] This application will be more fully understood by referring to the following detailed description of specific embodiments in conjunction with the accompanying drawings, wherein the same reference numerals in the drawings refer to the same elements, wherein:
[0017] Figure 1 This is the overall communication flow based on some examples from this application;
[0018] Figure 2 This is a flowchart of an adaptive adjustment method based on some specific examples of this application; and
[0019] Figure 3 A flowchart of the adaptive adjustment method 300 according to this application is shown schematically. Detailed Implementation
[0020] The following are some embodiments of this application, intended to provide a basic understanding of the application. They are not intended to identify key or decisive elements of the application or to limit the scope of protection sought.
[0021] For purposes of brevity and illustrativeness, the principles of this application are described herein primarily with reference to exemplary embodiments thereof. However, those skilled in the art will readily recognize that the same principles are equivalently applicable to all types of adaptive adjustment methods for master control devices, electronic devices, and computer-readable storage media in which these same principles can be implemented, and that any such variations do not depart from the true spirit and scope of this patent application.
[0022] Furthermore, reference is made in the accompanying drawings, which illustrate specific exemplary embodiments. Electrical, mechanical, logical, and structural modifications may be made to these embodiments without departing from the spirit and scope of this application. Moreover, while features of this application are disclosed in conjunction with only one of several embodiments, such features may be combined with one or more other features of other embodiments if desired and / or advantageous for any given or identifiable function. Therefore, the following description should not be construed as limiting, and the scope of this application is defined by the appended claims and their equivalents.
[0023] Terms such as "possessing" and "comprising" indicate that, in addition to the units (modules) and steps directly and explicitly stated in the specification and claims, the technical solution of this application does not exclude the presence of other units (modules) and steps not directly or explicitly stated. Terms such as "first" and "second" do not indicate the order of the units in terms of time, space, size, etc., but are merely used to distinguish the units. Furthermore, the steps in this document are not limited to being performed in the order they are written; a step written later may be performed simultaneously with or before a step written earlier.
[0024] Figure 1 This is based on some examples of the overall communication flow in this application, such as Figure 1 As shown, the main control device 100 includes a microcontroller unit (MCU) 120, which communicates serially with the external device 110. In some embodiments, the main control device 100 acquires data collected by the external device 110 and performs failure rate analysis on this data.
[0025] Figure 2 This is a flow of adaptive adjustment methods based on some specific examples of this application. Figure 2 The method shown can be derived from Figure 1 The main control device shown executes the commands. For example... Figure 2As shown, in step S201, the process begins. In step S202, the main control device communicates serially with external devices (such as temperature and humidity sensors, pressure sensors, illuminance sensors, wind speed sensors, air quality sensors, etc.). In some embodiments, a default communication rate (e.g., 300kHz) and sampling frequency (e.g., 1Hz) can be used during initialization. Then, in step S203, the MCU of the main control device can be used to set a global variable (Auto_Freq_Sign). The initial value of this global variable is set to 0. This global variable serves as a key indicator in the entire adjustment process, used to indicate the current adjustment status of the main control device. Specifically, the value of Auto_Freq_Sign is used to determine whether the sampling frequency has been adjusted. When the value of Auto_Freq_Sign is 0, it indicates that no adjustment operation based on the sampling frequency has been performed. When the value of Auto_Freq_Sign is 1, it indicates that the adjustment operation based on the sampling frequency has been performed. Simultaneously, based on the characteristics of the external devices, the extreme ranges (i.e., maximum and minimum values) of the communication rate and the sampling frequency are set. It should be noted that these extreme value ranges are set to ensure that the operating parameters of the main control device and external devices are always within a safe and effective range during subsequent adjustments, so as to avoid equipment damage or communication abnormalities caused by improper parameter settings. Then, in step S204, the main control device continuously collects sampling data from external devices at the initialized default sampling frequency and communication rate. After a specific period of time (e.g., 3 minutes), when the sampling data collection is completed, the main control device can analyze the collected sampling data and determine whether there are large jumps or losses (for example, in temperature sensor data acquisition, if the temperature values collected in two consecutive samples show a jump far exceeding the normal range, this may mean that there is a data jump; if data should have been collected at a certain moment but no feedback was received, it is determined to be data loss). The main control device then calculates the data loss rate. The data loss rate refers to the ratio between the amount of abnormal data and the total amount of data transmitted during data transmission. It reflects the degree to which data becomes abnormal due to various interference factors or other problems during the transmission from external devices to the main control device. For example, if a total of 1000 data points are transmitted over a period of time, and 10 of these data points are found to have problems such as continuity anomalies, fluctuations exceeding reasonable ranges, or abnormal correlation with historical data, then the data loss rate is 10 ÷ 1000 = 0.01, or 1%.Then, in step S205, the data failure rate calculated in step S204 is compared with a preset failure rate threshold. In this embodiment, the failure rate threshold can be preset to 1 / 32. If the calculated data failure rate is less than or equal to 1 / 32, it means that the current communication rate and sampling frequency can adapt well to the communication environment and meet the accuracy requirements of data transmission. At this time, we can directly proceed to step S215 and end this adaptive adjustment process. When the calculated data failure rate is greater than 1 / 32, we proceed to step S206. If the global variable Auto_Freq_Sign is equal to 0, it indicates that no adjustment operation has been performed on the sampling frequency. Then we proceed to step S207, using the binary search algorithm, to adjust the sampling frequency to 1 / 2 of the initial default sampling frequency (for example, if the initial default sampling frequency is 1 Hz, it will become 0.5 Hz after adjustment). At the same time, Auto_Freq_Sign is set to 1 to indicate that the sampling frequency has been adjusted.
[0026] Then, in step S209, it is determined whether the current sampling frequency adjusted by the bisection method is within the extreme range of the sampling frequency (i.e., between the maximum and minimum values). If the current sampling frequency is outside the extreme range, proceed to step S215 to end the current adaptive adjustment process. If the current sampling frequency adjusted by the bisection method is within the extreme range of the sampling frequency, return to step S204. The main control device continuously collects new sampling data from external devices using the current sampling frequency adjusted by the bisection method and the initial default communication rate. After a specific time period, the data failure rate of the collected new sampling data is calculated, and then proceed to step S205 for judgment. If the calculated data failure rate is less than the failure rate threshold, it indicates that the sampling frequency adjusted by the bisection method and the initial default communication rate can adapt well to the communication environment and meet the accuracy requirements of data transmission. At this time, it can also directly proceed to step S215 to end the current adaptive adjustment process.
[0027] If the calculated failure rate after adjustment is still greater than the failure rate threshold, and since we proceed to step S206, the global variable Auto_Freq_Sign will necessarily be 1, then we proceed to step S208. Here, we need to compare the current calculated failure rate with the previously calculated failure rate. If the current calculated failure rate is greater than the previous one, it indicates that the adjusted sampling frequency and initial default communication rate have failed to effectively improve communication quality, or even worsen it. In this case, we proceed to step S210, setting the communication rate to 1.X times (e.g., 1.2 times) of the initial default communication rate. In some embodiments, the value of X can correspond to the difference between the two calculated failure rate values. Then, we proceed to step S212, resetting Auto_Freq_Sign to 0. This indicates that the sampling frequency processed by the binary search method has not been adjusted again. Using the global variable Auto_Freq_Sign helps avoid unnecessary repeated adjustments (such as continuously adjusting the sampling frequency or continuously adjusting the communication rate), thereby improving adjustment efficiency. Then, proceed to step S213, where it needs to be determined whether the communication rate adjusted by 1.X times is within the extreme range of the communication rate, i.e., less than the maximum communication rate. If not, proceed directly to step S215 to end this adaptive adjustment process. If yes, proceed to step S214 to restart the serial drive of the main control device. As the output frequency of the serial clock pin of the main control device's MCU increases, the main control device and the external device can synchronize their communication rates. Then return to step S204 and repeat the process of steps S204-S208. In some embodiments, after each calculation of the data failure rate, the current data failure rate and the corresponding communication rate and sampling frequency can be recorded to form a historical database.
[0028] If, in step S208, the calculated failure rate is less than the previous failure rate, this indicates that the adjusted sampling frequency and initial default communication rate have effectively improved communication quality. At this point, proceed to step S211, setting the communication rate to 0.X times (e.g., 0.8 times) of the initial default communication rate. Similarly, in some embodiments, the value of X can correspond to the difference between the two calculated failure rate values. Then, proceed to step S212, resetting Auto_Freq_Sign to 0. Then, proceed to step S213, determining whether the communication rate adjusted by 0.8 times is within the extreme range of the communication rate, i.e., greater than the minimum communication rate. If not, proceed directly to step S215, ending the adaptive adjustment process. If yes, proceed to step S214, restarting the serial drive of the main control device. As the output frequency of the serial clock pin of the main control device's MCU decreases, the main control device and the external device can synchronize their communication rates. Then, return to step S204, and repeat the process from steps S204 to S208. In some embodiments, after each calculation of the data failure rate, the current data failure rate, as well as the communication rate and sampling frequency corresponding to the current data failure rate, can be recorded to form a historical database.
[0029] If, after multiple iterations of adjustment, the calculated failure rate is still greater than the failure rate threshold, and the communication rate and sampling frequency no longer meet the adjustment conditions (i.e., outside the extreme range), then proceed directly to step S215 to end the current adaptive adjustment process.
[0030] In other embodiments, if, after multiple iterations of adjustment, the calculated data failure rate is still greater than the failure rate threshold, and the communication rate and sampling frequency no longer meet the adjustment conditions, before ending the adaptive adjustment process, the parameter combination with the lowest data failure rate (i.e., the sampling frequency and communication rate corresponding to the lowest data failure rate) can be found from the database formed by previously recorded data, and the sampling frequency and communication rate of the main control device can be adjusted to the above-mentioned sampling frequency and communication rate. Using this set of sampling frequencies and communication rates can minimize the data transmission failure rate.
[0031] Furthermore, in some embodiments, after determining the optimal sampling frequency and communication rate, in order to further reduce the impact of interference, a low-pass filtering algorithm can be used to process the data. By weighting the data, noise interference can be removed, making the output data smoother and more accurate.
[0032] Specifically, when the failure rate is low, it means that the data transmission is relatively stable and there is little interference. In this case, the newly acquired data can be given a higher weight, making the data changes more sensitive. This is because in a stable environment, the newly acquired data can better reflect the real changes in physical quantities. By giving it a higher weight, these subtle changes can be captured in a timely manner. Conversely, if the failure rate is high, it means that the data is subject to greater interference. In this case, the newly acquired data should be given a lower weight, making the output data relatively smooth. By relying more on the previously relatively reliable filtered output values, abnormal fluctuations caused by interference can be effectively smoothed, making the output data closer to the true value.
[0033] The following is an example of a low-pass filter implementation method, with the formula: Y(n) = aX(n) + (1-a)Y(n-1). Here, Y(n) represents the current filter output value, which is the final data result after filtering; Y(n-1) represents the previous filter output value, which contains information from previous data processing; a is a weight value, whose magnitude is dynamically adjusted according to the failure rate; X(n) represents the current peripheral sampling value, which is the original acquired data. To reduce the impact of interference, the higher the failure rate, the smaller the value of a. For example, when the failure rate is greater than 1 / 16 and less than 1 / 10, 'a' is 0.1-0.2. Within this failure rate range, the data is subject to severe interference, so newly acquired data is given a lower weight to ensure the stability of the output data. When the failure rate is greater than 1 / 20 and less than 1 / 16, 'a' is 0.2-0.4. At this time, the interference of the data is relatively reduced, and the weight of newly acquired data can be appropriately increased to better reflect the trend of data changes while ensuring data stability. When the failure rate is greater than 1 / 32 and less than 1 / 20, 'a' is 0.4-0.6. Within this range, the data transmission is relatively stable, and the reliability of newly acquired data is high, so it is given a higher weight to capture data changes more promptly.
[0034] When the failure rate falls within the three intervals mentioned above, based on the principle that two points determine a straight line, we obtain the formula Y(a) = kx + b. Substituting the failure rate as x into this formula yields the corresponding weight value Y(a). This linear interpolation method allows for more accurate determination of the weight value based on the failure rate, making the filtering algorithm more flexible and intelligent.
[0035] However, when the failure rate is greater than 1 / 10, using a smaller weight (a) yields poor results. This is because a too-small weight value leads to insensitivity to data, and it takes a long time for data changes to be reflected. In this case, other optimization measures need to be considered comprehensively to further improve the quality of data transmission.
[0036] When the failure rate is less than 1 / 32, the data can be considered to be subject to relatively small interference, and the impact of the interference can be disregarded.
[0037] Once the optimal parameter adjustment and filtering algorithm have been implemented, the adaptive adjustment process ends.
[0038] Figure 3 A flowchart of the adaptive adjustment method 300 according to this application is schematically shown. Figure 3 As shown, the adaptive adjustment method 300 may include: in S310: the master control device receives sampled data based on a first communication rate (e.g., initializing the default communication rate) and a first sampling frequency (e.g., initializing the default sampling frequency), and calculates the sampled data to generate a first data failure rate (i.e., the proportion of sampled data that is abnormal).
[0039] The adaptive adjustment method 300 may further include, in S320: when the master control device responds to the case that the first data failure rate is greater than a preset failure rate threshold (e.g., 1 / 32) and the first sampling frequency has not been adjusted (i.e., the global variable Auto_Freq_Sign is 0), adjusting the first sampling frequency to generate a second sampling frequency; optionally, the first sampling frequency may be adjusted using a binary search method to generate the second sampling frequency, while ensuring that the second sampling frequency is within the preset sampling frequency extreme range.
[0040] The adaptive adjustment method 300 may further include, in step S330: the master control device receives sampled data based on a first communication rate and a second sampling frequency, and calculates the sampled data to generate a second data failure rate. In response to a situation where the second data failure rate is greater than a preset failure rate threshold and the first sampling frequency has been adjusted (i.e., the global variable Auto_Freq_Sign is 1), the master control device adjusts the first communication rate to generate the second communication rate. In some embodiments, the first communication rate can be adjusted to generate the second communication rate based on the difference between the second and first data failure rates (for example, when the second data failure rate is greater than the first data failure rate, the second communication rate is set to 1.X times the first communication rate, and when the second data failure rate is less than the first data failure rate, the second communication rate is set to 0.X times the first communication rate), while ensuring that the second communication rate is within the preset communication rate extreme range. In some examples, the value of X may correspond to the difference between the second and first data failure rates. Optionally, after the master control device adjusts the first communication rate to generate the second communication rate, the master control device may restart the serial drive.
[0041] The adaptive adjustment method 300 may further include, in step S340: the master control device receives sampled data based on a second communication rate and a second sampling frequency, and calculates the sampled data to generate a third data failure rate. Furthermore, after each generation of the data failure rate, the current data failure rate, the corresponding current communication rate, and the current sampling frequency can be recorded to form a historical database.
[0042] In some other embodiments, the adaptive adjustment method 300 may further include the following steps after step S340: selecting a communication rate and sampling frequency corresponding to the lowest data failure rate from a historical database in response to any of the following conditions, and stopping the execution of steps S310-S340: the second communication rate is outside the preset communication rate extreme range, and the second sampling frequency is outside the preset sampling frequency extreme range.
[0043] In some other embodiments, the adaptive adjustment method 300 may also include additional steps after step S340: smoothing the sampled data based on a filtering algorithm.
[0044] According to another aspect of this application, an electronic device is also provided. The electronic device includes a memory and a processor, the memory storing program instructions that, when executed by the processor, implement the adaptive adjustment method according to any of the foregoing embodiments. The electronic device may, in example or additionally, include an MCU, in which the processor is disposed.
[0045] According to another aspect of this application, a computer-readable storage medium for storing instructions is also provided, wherein a processor or processing module executes an adaptive adjustment method according to any embodiment of this application when running the instructions.
[0046] The computer-readable storage medium, memory, storage unit, storage module, etc., referred to in this application include various types of computer-readable storage media, which can be any available medium accessible by a general-purpose or special-purpose computer. For example, a computer-readable medium may include RAM, ROM, EPROM, E2PROM, registers, hard disk, removable disk, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other temporary or non-temporary medium capable of carrying or storing desired program code units in the form of instructions or data structures, accessible by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor. Combinations of the above should also be included within the scope of protection of computer-readable media. An exemplary storage medium is coupled to a processor so that the processor can read and write information from / to the storage medium. In an alternative, the storage medium may be integrated into the processor. The processor and storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In an alternative, the processor and storage medium may reside as discrete components in the user terminal.
[0047] In summary, the embodiments of this application propose a strategy for dynamically adjusting the sampling frequency and communication rate based on the data loss rate, reducing anomalies and data loss during data transmission and improving data integrity and accuracy. Simultaneously, while maintaining data quality, this application improves the system's response speed by optimizing communication parameters, enabling the main control device to acquire data from external devices more promptly. Furthermore, this application can automatically adapt to different communication environments and interference conditions, enhancing the robustness and stability of the main control device.
[0048] The foregoing primarily describes the adaptive adjustment method for a master control device, the electronic device, and the computer-readable storage medium of this application. Although only some specific embodiments of this application have been described, those skilled in the art should understand that this application can be implemented in many other forms without departing from its spirit and scope. Therefore, the examples and embodiments shown are considered illustrative rather than restrictive, and this application may cover various modifications and substitutions without departing from the spirit and scope of this application as defined by the appended claims.
Claims
1. An adaptive adjustment method for a master control device, characterized in that, The method includes the following steps: a) The main control device receives sampled data based on a first communication rate and a first sampling frequency, and calculates the sampled data to generate a first data failure rate; b) In response to the situation where the first data failure rate is greater than a preset failure rate threshold and the first sampling frequency has not been adjusted, the main control device adjusts the first sampling frequency to generate a second sampling frequency. c) The master control device receives the sampled data based on the first communication rate and the second sampling frequency, and calculates the sampled data to generate a second data failure rate. In response to the second data failure rate being greater than the preset failure rate threshold and the first sampling frequency being adjusted, the master control device adjusts the first communication rate to generate the second communication rate. as well as d) The master control device receives the sampled data based on the second communication rate and the second sampling frequency, and calculates the sampled data to generate a third data failure rate.
2. The adaptive adjustment method according to claim 1, characterized in that, The step of adjusting the first sampling frequency to generate the second sampling frequency further includes: adjusting the first sampling frequency using a binary search method to generate the second sampling frequency, while ensuring that the second sampling frequency is within a preset extreme value range of the sampling frequency.
3. The adaptive adjustment method according to claim 1, characterized in that, The main control device adjusting the first communication rate to generate the second communication rate further includes: adjusting the first communication rate to generate the second communication rate based on the difference between the second data failure rate and the first data failure rate, while ensuring that the second communication rate is within a preset communication rate extreme value range.
4. The adaptive adjustment method according to claim 3, characterized in that, The step of adjusting the first communication rate based on the difference between the second data failure rate and the first data failure rate to generate the second communication rate includes: adjusting the first communication rate using an adjustment coefficient corresponding to the difference to generate the second communication rate.
5. The adaptive adjustment method according to claim 4, characterized in that, Step c) further includes: after the master control device adjusts the first communication rate to generate the second communication rate, the master control device restarts the serial driver.
6. The adaptive adjustment method according to claim 1, characterized in that, After each data failure rate is generated, the current data failure rate, the current communication rate and the current sampling frequency corresponding to the current data failure rate are recorded to form a historical database.
7. The adaptive adjustment method according to claim 6, characterized in that, The method further includes the following steps: e) Select a communication rate and sampling frequency corresponding to the lowest data failure rate from the historical database in response to any of the following conditions, and stop the execution of steps a)-d): the second communication rate is outside the preset communication rate extreme range, and the second sampling frequency is outside the preset sampling frequency extreme range.
8. The adaptive adjustment method according to claim 7, characterized in that, The method further includes the following steps: f) Smooth the sampled data based on a filtering algorithm.
9. The adaptive adjustment method according to claim 1, characterized in that, The data failure rate is the percentage of sampled data that is abnormal.
10. An electronic device, characterized in that, The electronic device includes: A memory, wherein program instructions are stored; A processor that, when executing the program instructions, implements the adaptive adjustment method according to any one of claims 1 to 9.
11. The electronic device according to claim 10, characterized in that, The electronic device includes a microcontroller unit, and the processor is disposed in the microcontroller unit.
12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed by a processor, perform the adaptive adjustment method according to any one of claims 1-9.