Industrial System Control Method, Device, and Non-Volatile Storage Medium

Abstract

The present invention discloses an industrial system control method, device and non-volatile storage medium. Among them, the method includes: determining a current measurement value and a historical measurement value of a target process index, where the target process index is any one of a plurality of process indexes corresponding to the operation of the industrial system, and the current measurement value is the measurement value closest to the current time point at the acquisition time point; determining amplitude characteristic data of the target process index according to the current measurement value and the historical measurement value; optimizing the controller parameters of the target controller according to the amplitude characteristic data, where the target controller is a controller for controlling the working state of the industrial system; and controlling the working state of the industrial system according to the optimized controller parameters. The present invention solves the technical problem that the rapid stability of the industrial system cannot be achieved due to the inability to determine the oscillation characteristics of the target index in the prior art when the oscillation period is constantly changing.

Description

Technical Field

[0001] The present invention relates to the field of automation, and in particular, to an industrial system control method, device, and non-volatile storage medium. Background Art

[0002] The stable operation of various industrial systems depends on the stable control of key process indicators. Production disturbances can cause the indicators to deviate, and generally, control means such as PID and MPC can be used for correction. However, if the disturbance is periodic, or due to unreasonable control parameter settings, the disturbance excites the control output to oscillate up and down, then the process indicators will also show periodic fluctuations. Currently, the existing technology is relatively effective for detecting oscillations with a predetermined period, but the oscillation period of process indicators is often variable, and the existing technology cannot achieve wide-spectrum coverage.

[0003] In response to the above problems, no effective solution has been proposed yet. Summary of the Invention

[0004] Embodiments of the present invention provide an industrial system control method, device, and non-volatile storage medium to at least solve the technical problem that the rapid stability of the industrial system cannot be achieved because the existing technology cannot determine the oscillation characteristics of the target indicator when the oscillation period is constantly changing.

[0005] According to an aspect of an embodiment of the present invention, an industrial system control method is provided, including: determining a current measurement value and a historical measurement value of a target process indicator, where the target process indicator is any one of multiple process indicators corresponding to the operation of the industrial system, and the current measurement value is the measurement value closest to the current time point at the acquisition time point; determining amplitude characteristic data of the target process indicator based on the current measurement value and the historical measurement value; optimizing the controller parameters of the target controller based on the amplitude characteristic data, where the target controller is a controller for controlling the working state of the industrial system; and controlling the working state of the industrial system based on the optimized controller parameters.

[0006] Optionally, determining amplitude characteristic data of the target process indicator based on the current measurement value and the historical measurement value includes: determining a reference value based on the current measurement value or the historical measurement value; determining a preset number of historical measurement values, where the preset number is the number of historical measurement values used to determine the amplitude characteristic data of the target process indicator; sequentially reading the historical measurement values until the preset number of historical measurement values is read, and after each reading of the historical measurement value, calculating the difference between the current measurement value and the historical measurement value, and the absolute value of the difference between the differences; and determining the amplitude characteristic data of the target process indicator based on the differences and the absolute values of the differences.

[0007] Optionally, determining a reference value based on a current measurement value or a historical measurement value includes: using the current measurement value as the reference value; and using the average value of historical measurement values as the reference value.

[0008] Optionally, determining amplitude characteristic data of a target process index based on a difference value and an absolute value of the difference value includes: after calculating the difference value between the current measurement value and the historical measurement value each time, calculating an accumulated difference value of the current measurement value and the historical measurement value, where the accumulated difference value is equal to the sum of the differences between the current measurement values and the historical measurement values in each instance; and after calculating the absolute value of the difference value between the current measurement value and the historical measurement value each time, calculating an accumulated absolute value of the difference value of the current measurement value and the historical measurement value, where the accumulated absolute value of the difference value is equal to the sum of the differences between the measurement values and the historical measurement values in each instance; determining the amplitude characteristic data of the target process index based on the accumulated difference value and the accumulated absolute value of the difference value.

[0009] Optionally, determining amplitude characteristic data of a target process index based on the accumulated difference value and the accumulated absolute value of the difference value includes: after obtaining the accumulated value of the accumulated difference value and the accumulated absolute value of the difference value each time, calculating the average amplitude of the target process index based on the absolute value of the accumulated difference value, the accumulated absolute value of the difference value, and the accumulated number of historical measurement values that have been read currently; determining the maximum average amplitude from the calculated multiple average amplitudes, and using the maximum average amplitude as the amplitude characteristic data of the target process index.

[0010] Optionally, determining amplitude characteristic data of a target process index based on the accumulated difference value and the accumulated absolute value of the difference value includes: after reading a preset number of historical measurement values, calculating the average amplitude of the target process index based on the absolute value of the accumulated difference value calculated when reading the historical measurement values this time, the accumulated absolute value of the difference value, and the preset number, and using the average amplitude as the amplitude characteristic data of the target process index.

[0011] Optionally, after determining the amplitude characteristic data of the target process index, the method further includes: filtering the amplitude characteristic data of the target process index.

[0012] According to another aspect of the embodiments of the present invention, there is also provided an industrial system control device, including: a processing module configured to determine a current measurement value and a historical measurement value of a target process index, where the target process index is any one of multiple process indexes corresponding to the operation of the industrial system; a first calculation module configured to determine the amplitude characteristic data of the target process index based on the current measurement value and the historical measurement value; a second calculation module configured to optimize the controller parameters of a target controller based on the amplitude characteristic data, where the target controller is a controller for controlling the operating state of the industrial system; and a control module configured to control the operating state of the industrial system based on the optimized target controller.

[0013] According to another aspect of the embodiments of the present invention, a non-volatile storage medium is further provided. The non-volatile storage medium includes a stored program, wherein when the program runs, it controls the device where the non-volatile storage medium is located to execute the industrial system control method.

[0014] According to another aspect of the embodiments of the present invention, an electronic device is further provided. The electronic device includes a processor for running a program, wherein when the program runs, it executes the industrial system control method.

[0015] In the embodiments of the present invention, the current measurement value and the historical measurement value of the target process index are determined, wherein the target process index is any one of multiple process indexes corresponding to the operation of the industrial system, and the current measurement value is the measurement value closest to the current time point at the acquisition time point; according to the current measurement value and the historical measurement value, the amplitude characteristic data of the target process index is determined; according to the amplitude characteristic data, the controller parameters of the target controller are optimized, wherein the target controller is the controller for controlling the working state of the industrial system; according to the optimized controller parameters, the working state of the industrial system is controlled. By combining the current measurement value and the historical measurement value to jointly determine the amplitude characteristic of the target process index, the purpose of accurately determining the amplitude characteristic of the target process index is achieved under the condition that the oscillation period of the disturbance is constantly changing, etc., thereby realizing the technical effect of ensuring the stable operation of the industrial system when the oscillation period of the disturbance is constantly changing, and further solving the technical problem that the industrial system cannot achieve fast and stable operation due to the inability to determine the oscillation characteristic of the target index when the oscillation period is constantly changing in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present invention, and constitute a part of this application. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0017] Figure 1 is a schematic flowchart of an industrial system control method provided according to an embodiment of the present invention;

[0018] Figure 2 is a schematic flowchart of a process for determining the amplitude characteristic data of a target process index provided according to an embodiment of the present invention;

[0019] Figure 3 is a schematic flowchart of a process for determining the amplitude characteristic data of a target process index provided according to an embodiment of the present invention;

[0020] Figure 4 is a schematic flowchart of a process for determining the amplitude characteristic data of a target process index provided according to an embodiment of the present invention;

[0021] Figure 5 It is a schematic flowchart of a process for determining the amplitude characteristic data of a target process index provided according to an embodiment of the present invention;

[0022] Figure 6 It is a schematic flowchart of a process for determining the amplitude characteristic data of a target process index provided according to an embodiment of the present invention;

[0023] Figure 7 It is a schematic flowchart of a process for determining the amplitude characteristic data of a target process index provided according to an embodiment of the present invention;

[0024] Figure 8 It is a schematic structural diagram of an industrial system control device provided according to an embodiment of the present invention. Detailed implementation manners

[0025] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order different from those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0027] According to an embodiment of the present invention, a method embodiment of an industrial system control method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0028] Figure 1 It is an industrial system control method according to an embodiment of the present invention, as Figure 1 shown, the method includes the following steps:

[0029] Step S102: Determine the current measurement value and the historical measurement value of the target process index, where the target process index is any one of multiple process indexes corresponding to the operation of the industrial system, and the current measurement value is the measurement value closest to the current time point at the acquisition time point.

[0030] In some embodiments of the present application, when the industrial system is operating, the data acquisition module integrated on the industrial system samples the industrial system at a preset frequency and stores the sampled values in the storage module according to the sampling time. Among them, the above preset frequency can be set by the user according to their own needs. For example, the industrial system of a steel mill can collect data once every 50 ms, while the chemical plant can choose to collect data once every 1 s.

[0031] Step S104: Determine the amplitude characteristic data of the target process index based on the current measurement value and the historical measurement value.

[0032] In some embodiments of the present application, the specific method for determining the amplitude characteristic data of the target process index based on the current measurement value and the historical measurement value is as follows: Determine the reference value based on the current measurement value or the historical measurement value; Determine the preset number of the historical measurement values, where the preset number is the number of historical measurement values used to determine the amplitude characteristic data of the target process index; Read the historical measurement values in sequence until the preset number of historical measurement values is read, and after each reading of the historical measurement value, calculate the difference between the current measurement value and the historical measurement value, and the absolute value of the difference of the differences; Determine the amplitude characteristic data of the target process index based on the difference and the absolute value of the difference.

[0033] In some embodiments of the present application, the process of determining the reference value based on the current measurement value or the historical measurement value includes the following methods: As Figure 2 shown, use the current measurement value as the reference value; and, as Figure 4 shown, use the average value of the historical measurement values as the reference value.

[0034] In some embodiments of the present application, the method for determining the amplitude characteristic data of the target process index based on the difference and the absolute value of the difference includes: after calculating the difference between the current measurement value and the historical measurement value each time, calculating the cumulative value of the difference between the current measurement value and the historical measurement value, where the cumulative value of the difference is equal to the sum of the differences between the current measurement value and the historical measurement value in each previous time; and, after calculating the absolute value of the difference between the current measurement value and the historical measurement value each time, calculating the cumulative value of the absolute value of the difference between the current measurement value and the historical measurement value, where the cumulative value of the absolute value of the difference is equal to the sum of the differences between the measurement value and the historical measurement value in each previous time; determining the amplitude characteristic data of the target process index based on the cumulative value of the difference and the cumulative value of the absolute value of the difference.

[0035] In some embodiments of the present application, the specific manner of determining the amplitude characteristic data of the target process index based on the cumulative value of the difference and the cumulative value of the absolute value of the difference includes: after obtaining the cumulative value of the difference and the cumulative value of the absolute value of the difference each time, calculating the average amplitude of the target process index based on the absolute value of the cumulative value of the difference, the cumulative value of the absolute value of the difference, and the cumulative number of the historical measurement values that have been read currently; determining the maximum average amplitude from the calculated multiple average amplitudes, and using the maximum average amplitude as the amplitude characteristic data of the target process index.

[0036] Specifically, in some embodiments of the present application, the process of determining the amplitude characteristic data of the target process index is as Figure 2 shown, including the following processes:

[0037] The first step is parameter reset, including clearing the cumulative deviation value (SumEn = 0), clearing the cumulative absolute value of the deviation (SumAbsEn = 0), clearing the maximum average amplitude (MaxAveWave = 0), clearing the number of sampling points (n = 0), etc.

[0038] The second step is to read the current measurement value (CV). Specifically, compared with the calculation method with the average value as the reference point, selecting the current measurement value as the calculation reference point can obtain better control performance, that is, when the oscillation waveform returns to the center point, the maximum amplitude corresponding to the target process index can be calculated.

[0039] The third step is to determine the number of sampling points n that have been read currently. If the number of sampling points n is less than the preset total number of sampling points S, then jump to the fourth step to read the historical measurement value (CVn) before the nth point. The recording of the historical measurement value can be uniformly recorded by the software platform or saved sequentially in the memory by the algorithm. If the number of sampling points is not less than the preset total number of sampling points S, then end the loop.

[0040] Step 5: Calculate the deviation (En) between CVn and CV.

[0041] Step 6: Calculate the cumulative deviation value (SumEn = SumEn + En). Specifically, when oscillation occurs, the deviations are positive and negative, and they will cancel each other out during the cumulative calculation of deviations. If oscillation does not occur, the deviations will not cancel each other out during the cumulative calculation.

[0042] Step 7: Calculate the cumulative absolute deviation value (SumAbsEn = SumAbsEn + Abs(En)). Specifically, first calculate the absolute value of the deviation (En), and then perform the accumulation. Thus, regardless of whether oscillation occurs, the cumulative calculation of the absolute deviation will not cancel each other out.

[0043] Step 8: Calculate the average amplitude (AveWave = (SumAbsEn - Abs(SumEn)) / n). Specifically, the average amplitude (AveWave) of the current cumulative number of times can be obtained by subtracting the absolute value of the cumulative deviation value from the cumulative absolute deviation value and then dividing by the cumulative number of times n. If oscillation does not occur, the average amplitude is equal to 0. If oscillation occurs, the average amplitude is greater than 0.

[0044] Step 9: Compare the average amplitude obtained in this calculation with the maximum average amplitude obtained in the previous loop. If the maximum average amplitude (MaxAveWave) is less than the average amplitude (AveWave) (calculated above), then set the maximum average amplitude (MaxAveWave) equal to the average amplitude. Otherwise, directly jump to the accumulation of the number of sampling points. The selected maximum average amplitude can significantly reflect the oscillation characteristics of the target process index.

[0045] Step 10: Accumulate the number of sampling points (n = n + 1), go back to Step 3, and continue the loop.

[0046] In some embodiments of the present application, determining the amplitude characteristic data of the target process index based on the cumulative value of the difference and the cumulative value of the absolute value of the difference includes: after reading the preset number of the historical measurement values, based on the absolute value of the cumulative value of the difference calculated each time when reading the historical measurement values, the cumulative value of the absolute value of the difference, and the preset number, calculating the average amplitude of the target process index, and using the average amplitude as the amplitude characteristic data of the target process index.

[0047] In some embodiments of the present application, such as Figure 3As shown, when the operating conditions of the industrial system meet the requirements, the maximum average amplitude can be calculated only once after the loop ends instead of calculating it in each loop by setting a reasonable number of historical measurement values. The average amplitude corresponding to the target process index is directly calculated after the loop ends, and the finally calculated average amplitude is regarded as the amplitude characteristic data of the target process index. The specific steps are as follows:

[0048] The first step is parameter reset, including clearing the deviation accumulation value (SumEn = 0), clearing the absolute value accumulation value of the deviation (SumAbsEn = 0), clearing the maximum average amplitude (MaxAveWave = 0), clearing the number of sampling points (n = 0), etc.

[0049] The second step is to read the current measurement value (CV). Specifically, compared with the calculation method with the average value as the reference point, selecting the current measurement value as the calculation reference point can obtain better control performance, that is, when the oscillation waveform returns to the center point, the maximum amplitude corresponding to the target process index can be calculated.

[0050] The third step is to determine the number of sampling points n that have been read currently. If the number of sampling points n is less than the preset total number of sampling points S, jump to the fourth step to read the historical measurement value (CVn) before the nth point. The recording of historical measurement values can be uniformly recorded by the software platform or saved in order in the memory by the algorithm. If the number of sampling points is not less than the preset total number of sampling points S, jump to the ninth step.

[0051] The fifth step is to calculate the deviation (En) between CVn and CV.

[0052] The sixth step is to calculate the deviation accumulation value (SumEn = SumEn + En). Specifically, when oscillation occurs, the deviations are positive and negative, and they will cancel each other out during the deviation accumulation calculation. If oscillation does not occur, the deviations will not cancel each other out during the deviation accumulation calculation.

[0053] The seventh step is to calculate the absolute value accumulation value of the deviation (SumAbsEn = SumAbsEn + Abs(En)). Specifically, first calculate the absolute value of the deviation (En), and then accumulate it. Then, regardless of whether oscillation occurs, the accumulation calculation of the absolute value of the deviation will not cancel each other out.

[0054] The eighth step is to increment the number of sampling points (n = n + 1), and then return to the third step to continue the loop.

[0055] Step 9: Calculate the average amplitude (AveWave = (SumAbsEn - Abs(SumEn)) / n). Specifically, the accumulated value of the absolute deviation can be subtracted from the absolute value of the accumulated deviation, and then divided by the number of accumulations n to obtain the average amplitude (AveWave) for the current number of accumulations. If there is no oscillation, the average amplitude is equal to 0; if there is oscillation, the average amplitude is greater than 0.

[0056] In some embodiments of the present application, as Figure 4 shown, after reading a preset number of historical measurement values, the average value of the above-mentioned preset number of historical measurement values can also be used as the reference value to replace the current measurement value, which specifically includes the following steps:

[0057] Step 1: Reset the parameters, including clearing the accumulated deviation value (SumEn = 0), clearing the accumulated absolute deviation value (SumAbsEn = 0), clearing the maximum average amplitude (MaxAveWave = 0), clearing the number of sampling points (n = 0), etc.

[0058] Step 2: Calculate the average value (AveCV) of multiple historical measurement values with a total number of sampling points of S, and use this average value as the reference value.

[0059] Step 3: Determine the number of sampling points n that have been read currently. If the number of sampling points n is less than the preset total number of sampling points S, then jump to Step 4 to read the historical measurement value (CVn) before the nth point. The recording of historical measurement values can be uniformly recorded by the software platform or saved sequentially in the memory by the algorithm. If the number of sampling points is not less than the preset total number of sampling points S, then end the loop.

[0060] Step 5: Calculate the deviation (En) between CVn and AveCV.

[0061] Step 6: Calculate the accumulated deviation value (SumEn = SumEn + En). Specifically, when there is oscillation, the deviations are positive and negative, and they will cancel each other out during the accumulated calculation of deviations. If there is no oscillation, the deviations will not cancel each other out during the accumulated calculation.

[0062] Step 7: Calculate the accumulated absolute deviation value (SumAbsEn = SumAbsEn + Abs(En)). Specifically, first calculate the absolute value of the deviation (En), and then perform the accumulation. Then, regardless of whether there is oscillation, the accumulated calculation of the absolute deviation will not cancel each other out.

[0063] Step 8: Calculate the average amplitude (AveWave = (SumAbsEn - Abs(SumEn)) / n). Specifically, the accumulated value of the absolute deviation can be subtracted by the absolute value of the accumulated deviation, and then divided by the number of accumulations n to obtain the average amplitude (AveWave) for the current number of accumulations. If there is no oscillation, the average amplitude is equal to 0. If there is oscillation, the average amplitude is greater than 0.

[0064] Step 9: Compare the average amplitude obtained from this calculation with the maximum average amplitude among the average amplitudes obtained in the previous cycles. If the maximum average amplitude (MaxAveWave) is less than the average amplitude (AveWave) (calculated above), then set the maximum average amplitude (MaxAveWave) equal to the average amplitude. Otherwise, directly jump to the accumulation of the number of sampling points. The selected maximum average amplitude can significantly reflect the oscillation characteristics of the target process index.

[0065] Step 10: Accumulate the number of sampling points (n = n + 1), and go back to Step 3 to continue the loop.

[0066] In some embodiments of the present application, as Figure 5 shown, to reduce the computational load, if the value of the total number of sampling points S is large, then sampling can be performed at intervals to make the actual number of sampling points close to the desired number of sampling points. Specifically, it includes the following steps:

[0067] Step 1: Reset the parameters and calculate the sampling interval. Among them, parameter reset includes clearing the accumulated deviation value (SumEn = 0), clearing the accumulated absolute deviation value (SumAbsEn = 0), clearing the maximum average amplitude (MaxAveWave = 0), clearing the number of sampling points (n = 0), etc. When calculating the sampling interval, assume that the number of historical measurement values is S and the desired number of sampling points is T. If S > 2T, then r = S / T and take the integer part. Otherwise, set r = 1.

[0068] Step 2: Read the current measurement value (CV). Specifically, compared with the calculation method based on the average value as the reference point, selecting the current measurement value as the calculation reference point can obtain better control performance, that is, when the oscillation waveform returns to the center point, the maximum amplitude corresponding to the target process index is calculated.

[0069] Step 3: Determine the number of sampling points n that have been read currently. If the number of sampling points n is less than the preset total number of sampling points S, then jump to Step 4 to read the historical measurement value (CVn) before the nth point. The recording of historical measurement values can be uniformly recorded by the software platform or sequentially saved in the memory by the algorithm. If the number of sampling points is not less than the preset total number of sampling points S, then end the loop.

[0070] Step 5: Calculate the deviation (En) between CVn and CV.

[0071] Step 6, calculate the cumulative deviation value (SumEn = SumEn + En). Specifically, when oscillation occurs, the deviations are positive and negative, and they will cancel each other out during the cumulative calculation of deviations. If oscillation does not occur, they will not cancel each other out during the cumulative calculation of deviations.

[0072] Step 7, calculate the cumulative absolute deviation value (SumAbsEn = SumAbsEn + Abs(En)). Specifically, first calculate the absolute value of the deviation (En), and then perform the accumulation. Then, regardless of whether oscillation occurs, the cumulative calculation of the absolute deviation will not cancel each other out.

[0073] Step 8, calculate the average amplitude (AveWave = (SumAbsEn - Abs(SumEn)) / (n / r)). Specifically, the absolute value of the cumulative deviation value can be subtracted from the cumulative absolute deviation value, and then divided by the number of accumulations n to obtain the average amplitude (AveWave) of the current number of accumulations. If oscillation does not occur, the average amplitude is equal to 0. If oscillation occurs, the average amplitude is greater than 0.

[0074] Step 9, compare the average amplitude obtained from this calculation with the maximum average amplitude obtained in the previous loop. If the maximum average amplitude (MaxAveWave) is less than the average amplitude (AveWave) (calculated above), then set the maximum average amplitude (MaxAveWave) equal to the average amplitude. Otherwise, directly jump to the accumulation of the number of sampling points. The selected maximum average amplitude can significantly reflect the oscillation characteristics of the target process index.

[0075] Step 10, accumulate the number of sampling points (n = n + r), and return to Step 3 to continue the loop.

[0076] In some embodiments of the present application, as Figure 6 shown, after determining the amplitude characteristic data of the target process index, the amplitude characteristic data of the target process index can also be filtered to obtain more stable amplitude information, which specifically includes the following steps:

[0077] Step 1, reset the parameters, including clearing the cumulative deviation value (SumEn = 0), clearing the cumulative absolute deviation value (SumAbsEn = 0), clearing the maximum average amplitude (MaxAveWave = 0), clearing the number of sampling points (n = 0), etc.

[0078] Step 2, read the current measured value (CV). Specifically, compared with the calculation method based on the average value as the reference point, selecting the current measured value as the calculation reference point can obtain better control performance, that is, when the oscillation waveform returns to the center point, the maximum amplitude corresponding to the target process index can be calculated.

[0079] Step 3: Determine the number of sampled points n that have been read currently. If the number of sampled points n is less than the preset total number of sampled points S, jump to Step 4 to read the historical measurement value (CVn) before the nth point. The recording of historical measurement values can be uniformly recorded by the software platform or sequentially saved in the memory by the algorithm. If the number of sampled points is not less than the preset total number of sampled points S, end the loop and jump to Step 11.

[0080] Step 5: Calculate the deviation (En) between CVn and CV.

[0081] Step 6: Calculate the cumulative deviation value (SumEn = SumEn + En). Specifically, when oscillation occurs, the deviations are positive and negative, and they will cancel each other out during the cumulative calculation of deviations. If oscillation does not occur, the deviations will not cancel each other out during the cumulative calculation.

[0082] Step 7: Calculate the cumulative absolute deviation value (SumAbsEn = SumAbsEn + Abs(En)). Specifically, first calculate the absolute value of the deviation (En), and then perform the accumulation. Then, regardless of whether oscillation occurs, the cumulative calculation of the absolute deviation will not cancel each other out.

[0083] Step 8: Calculate the average amplitude (AveWave = (SumAbsEn - Abs(SumEn)) / n). Specifically, the cumulative absolute deviation value can be subtracted by the absolute value of the cumulative deviation value, and then divided by the number of accumulations n to obtain the average amplitude (AveWave) of the current number of accumulations. If oscillation does not occur, the average amplitude is equal to 0. If oscillation occurs, the average amplitude is greater than 0.

[0084] Step 9: Compare the average amplitude obtained in this calculation with the maximum average amplitude obtained in the previous loop. If the maximum average amplitude (MaxAveWave) is less than the average amplitude (AveWave) (calculated above), then set the maximum average amplitude (MaxAveWave) equal to the average amplitude. Otherwise, directly jump to the accumulation of the number of sampled points. The selected maximum average amplitude can significantly reflect the oscillation characteristics of the target process index.

[0085] Step 10: Accumulate the number of sampled points (n = n + 1), return to Step 3, and continue the loop.

[0086] Step 11: Filter the maximum average amplitude to obtain the filtered maximum average amplitude (MaxAveWaveFilt).

[0087] In some embodiments of the present application, as Figure 7 shown, when reading the historical measurement value, the historical measurement value can be read in the order opposite to the historical measurement value reading order shown in Figure 2 specifically including the following steps:

[0088] The first step is parameter reset, including clearing the deviation accumulation value (SumEn = 0), clearing the accumulated absolute value of deviation (SumAbsEn = 0), clearing the maximum average amplitude (MaxAveWave = 0), setting the number of sampling points (n = total number of sampling points S), etc.

[0089] The second step is to read the current measurement value (CV). Specifically, compared with the calculation method based on the average value as the reference point, selecting the current measurement value as the calculation reference point can obtain better control performance, that is, when the oscillation waveform returns to the center point, the maximum amplitude corresponding to the target process index is calculated.

[0090] The third step is to determine the number of sampling points n that have been read currently. If the number of sampling points n is greater than 0, then jump to the fourth step to read the historical measurement value (CVn) before the nth point. The recording of the historical measurement value can be uniformly recorded by the software platform or saved sequentially in the memory by the algorithm. If the number of sampling points n is not greater than 0, then end the loop.

[0091] The fifth step is to calculate the deviation (En) between CVn and CV.

[0092] The sixth step is to calculate the deviation accumulation value (SumEn = SumEn + En). Specifically, when oscillation occurs, the deviations are positive and negative, and they will cancel each other out during the deviation accumulation calculation. If oscillation does not occur, they will not cancel each other out during the deviation accumulation calculation.

[0093] The seventh step is to calculate the accumulated absolute value of deviation (SumAbsEn = SumAbsEn + Abs(En)). Specifically, first calculate the absolute value of the deviation (En), and then accumulate it. Then, regardless of whether oscillation occurs, the accumulated calculation of the absolute value of deviation will not cancel each other out.

[0094] The eighth step is to calculate the average amplitude (AveWave = (SumAbsEn - Abs(SumEn)) / n). Specifically, the accumulated absolute value of deviation can be subtracted by the absolute value of the deviation accumulation value, and then divided by the number of accumulations n to obtain the average amplitude (AveWave) of the current number of accumulations. If oscillation does not occur, the average amplitude is equal to 0. If oscillation occurs, the average amplitude is greater than 0.

[0095] The ninth step is to compare the average amplitude calculated this time with the maximum average amplitude obtained in the previous loop. If the maximum average amplitude (MaxAveWave) is less than the average amplitude (AveWave) (calculated above), then set the maximum average amplitude (MaxAveWave) equal to the average amplitude. Otherwise, directly jump to the accumulation of the number of sampling points. The selected maximum average amplitude can significantly reflect the oscillation characteristics of the target process index.

[0096] Step 10, accumulate the number of step sampling points (n = n - 1), return to Step 3, and continue to loop.

[0097] In step S106, according to the amplitude characteristic data, optimize the controller parameters of the target controller, where the target controller is a controller that controls the working state of the industrial system;

[0098] In some embodiments of the present application, the above target controller may be a PID controller or an MPC controller.

[0099] In step S108, control the working state of the industrial system according to the optimized controller parameters.

[0100] By determining the current measurement value and historical measurement value of the target process index, where the target process index is any one of multiple process indexes corresponding to the working of the industrial system, and the current measurement value is the measurement value closest to the current time point at the acquisition time point; according to the current measurement value and historical measurement value, determine the amplitude characteristic data of the target process index; according to the amplitude characteristic data, optimize the controller parameters of the target controller, where the target controller is a controller that controls the working state of the industrial system; according to the optimized controller parameters, control the working state of the industrial system, by combining the current measurement value and historical measurement value to jointly determine the amplitude characteristic of the target process index, the purpose of accurately determining the amplitude characteristic of the target process index is achieved in the case where the oscillation period of the disturbance is constantly changing, etc., thereby realizing the technical effect of ensuring the stable operation of the industrial system in the case where the oscillation period of the disturbance is constantly changing, and further solving the technical problem that the industrial system cannot achieve fast and stable operation due to the inability to determine the oscillation characteristic of the target index in the case where the oscillation period is constantly changing in the prior art.

[0101] According to an embodiment of the present invention, a device embodiment of an industrial system control device is provided. Figure 8 The industrial system control device according to an embodiment of the present invention is as Figure 8 shown. The device includes: a processing module 80, configured to determine the current measurement value and historical measurement value of the target process index, where the target process index is any one of multiple process indexes corresponding to the working of the industrial system; a first calculation module 82, configured to determine the amplitude characteristic data of the target process index according to the current measurement value and historical measurement value; a second calculation module 84, configured to optimize the controller parameters of the target controller according to the amplitude characteristic data, where the target controller is a controller that controls the working state of the industrial system; a control module 86, configured to control the working state of the industrial system according to the optimized target controller.

[0102] It should be noted that Figure 8The industrial system control device shown in can be used to execute Figure 1 the industrial system control method shown in. Therefore, the relevant explanations of Figure 1 the industrial system control method shown in also apply to Figure 8 the industrial system control device shown in.

[0103] According to an embodiment of the present invention, a non-volatile storage medium is further provided. The non-volatile storage medium includes a stored program. When the program runs, it controls the device where the non-volatile storage medium is located to execute the following industrial system control method: a processing module, configured to determine a current measurement value and a historical measurement value of a target process index, where the target process index is any one of multiple process indexes corresponding to the operation of the industrial system; a first calculation module, configured to determine amplitude characteristic data of the target process index based on the current measurement value and the historical measurement value; a second calculation module, configured to optimize the controller parameters of the target controller based on the amplitude characteristic data, where the target controller is a controller that controls the working state of the industrial system; a control module, configured to control the working state of the industrial system based on the optimized target controller.

[0104] According to an embodiment of the present invention, an electronic device is provided. The electronic device includes a processor, and the processor is used to run a program. When the program runs, it executes the following industrial system control method: a processing module, configured to determine a current measurement value and a historical measurement value of a target process index, where the target process index is any one of multiple process indexes corresponding to the operation of the industrial system; a first calculation module, configured to determine amplitude characteristic data of the target process index based on the current measurement value and the historical measurement value; a second calculation module, configured to optimize the controller parameters of the target controller based on the amplitude characteristic data, where the target controller is a controller that controls the working state of the industrial system; a control module, configured to control the working state of the industrial system based on the optimized target controller.

[0105] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments.

[0106] In the above embodiments of the present invention, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0107] In several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only illustrative. For example, the division of the units can be a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the couplings or direct couplings or communication connections shown or discussed with each other can be through some interfaces. The indirect couplings or communication connections of units or modules can be in electrical or other forms.

[0108] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place or distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0109] In addition, in each embodiment of the present invention, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0110] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention. The foregoing storage medium includes: USB flash drives, read-only memories (ROMs), random access memories (RAMs), mobile hard disks, magnetic disks, or optical discs and other various media that can store program codes.

[0111] The above is only the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. An industrial system control method, characterized in that, Including: Determine the current measurement value and historical measurement values of a target process index, where the target process index is any one of multiple process indexes corresponding to the operation of the industrial system, and the current measurement value is the measurement value closest to the current time point at the acquisition time point; Determine the amplitude characteristic data of the target process index based on the current measurement value and the historical measurement values; Optimize the controller parameters of a target controller based on the amplitude characteristic data, where the target controller is the controller that controls the operating state of the industrial system; Control the operating state of the industrial system based on the optimized controller parameters; Among them, determining the amplitude characteristic data of the target process index based on the current measurement value and the historical measurement values includes: after calculating the difference between the current measurement value and the historical measurement value each time, calculate the cumulative value of the differences between the current measurement value and the historical measurement value, where the cumulative value of the differences is equal to the sum of the differences between the current measurement value and the historical measurement value in previous times; and, After calculating the absolute value of the difference between the current measurement value and the historical measurement value each time, calculate the cumulative value of the absolute values of the differences between the current measurement value and the historical measurement value, where the cumulative value of the absolute values of the differences is equal to the sum of the absolute values of the differences between the current measurement value and the historical measurement value in previous times; Determine the amplitude characteristic data of the target process index based on the cumulative value of the differences and the cumulative value of the absolute values of the differences.

2. The industrial system control method according to claim 1, wherein Determining the amplitude characteristic data of the target process index based on the current measurement value and the historical measurement values includes: Determine a reference value based on the current measurement value or the historical measurement value; Determine the preset number of the historical measurement values, where the preset number is the number of historical measurement values used to determine the amplitude characteristic data of the target process index; Read the historical measurement values in sequence until the preset number of historical measurement values is read completely, and after reading each historical measurement value, calculate the difference between the current measurement value and the historical measurement value, and the absolute value of the difference.

3. The industrial system control method according to claim 2, wherein Determining a reference value based on the current measurement value or the historical measurement value includes: Taking the current measurement value as the reference value; and, Taking the average value of the historical measurement values as the reference value.

4. The industrial system control method according to claim 3, wherein Determining the amplitude characteristic data of the target process index based on the cumulative value of the differences and the cumulative value of the absolute values of the differences includes: After obtaining the cumulative value of the differences and the cumulative value of the absolute values of the differences each time, calculate the average amplitude of the target process index based on the absolute value of the cumulative value of the differences, the cumulative value of the absolute values of the differences, and the cumulative number of the historical measurement values that have been read currently; Determine the maximum average amplitude from the calculated multiple average amplitudes, and take the maximum average amplitude as the amplitude characteristic data of the target process index.

5. The industrial system control method according to claim 3, wherein Determining the amplitude characteristic data of the target process index based on the cumulative value of the differences and the cumulative value of the absolute values of the differences includes: After reading the preset number of the historical measurement values, based on the absolute value of the cumulative value of the differences calculated when reading the historical measurement values this time, the cumulative value of the absolute values of the differences, and the preset number, calculate the average amplitude of the target process index, and use the average amplitude as the amplitude characteristic data of the target process index.

6. The industrial system control method according to claim 3 or claim 4, characterized in that After determining the amplitude characteristic data of the target process index, the method further includes: Filter the amplitude characteristic data of the target process index.

7. An industrial system control device, characterized in that, It includes: A processing module, configured to determine the current measurement value and the historical measurement value of the target process index, where the target process index is any one of multiple process indexes corresponding to the operation of the industrial system; A first calculation module, configured to determine the amplitude characteristic data of the target process index based on the current measurement value and the historical measurement value; A second calculation module, configured to optimize the controller parameters of the target controller based on the amplitude characteristic data, where the target controller is a controller that controls the operating state of the industrial system; A control module, configured to control the operating state of the industrial system based on the optimized target controller; Among them, determining the amplitude characteristic data of the target process index based on the current measurement value and the historical measurement value includes: after calculating the difference between the current measurement value and the historical measurement value each time, calculate the cumulative value of the differences between the current measurement value and the historical measurement value, where the cumulative value of the differences is equal to the sum of the differences between the current measurement value and the historical measurement value in each previous time; and, After calculating the absolute value of the difference between the current measurement value and the historical measurement value each time, calculate the cumulative value of the absolute values of the differences between the current measurement value and the historical measurement value, where the cumulative value of the absolute values of the differences is equal to the sum of the absolute values of the differences between the current measurement value and the historical measurement value in each previous time; Determine the amplitude characteristic data of the target process index based on the cumulative value of the differences and the cumulative value of the absolute values of the differences.

8. A non-volatile storage medium, characterized in that, The non-volatile storage medium includes a stored program, where when the program runs, it controls the device where the non-volatile storage medium is located to execute the industrial system control method according to any one of claims 1 to 6.

9. An electronic device, the electronic device comprising a processor, characterized in that, The processor is used to run the program, where when the program runs, it executes the industrial system control method according to any one of claims 1 to 6.

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