Proportional-integral-derivative loop control method and related device

Abstract

The invention discloses a proportional-integral-derivative loop control method and a related device, and relates to the technical field of automatic control, after a set value and a current measurement value of a controlled object are obtained, the deviation of the controlled object is calculated, and the set value, the current measurement value and the deviation are input into a data analysis module; the current variation trend information of the controlled object is obtained, the current variation trend information and the current deviation state information are input into the parameter group selection unit, a sub-parameter group matched with the current working condition of the controlled object is determined, and the sub-parameter group is input into the proportional integral differential control unit to adjust the current measured value. And outputting the current operation value of the controlled object, and finally, controlling the controlled object by adopting the current operation value. According to the method, the sub-parameter group suitable for the current working condition can be matched for the controlled object in real time according to the trend change and the deviation state of the controlled variable, the current measurement value is adjusted by adopting the sub-parameter group, the current operation value is output to control the controlled object, and the parameter adjustment efficiency is high.

Description

Technical Field

[0001] The present application relates to the field of automation control technology, and in particular to a proportional-integral-differential loop control method and related devices. Background Art

[0002] Proportional-integral-derivative control, abbreviated as PID (Proportional-Integral-Derivative) control, is used to form a control deviation based on the set value and the measured value, and to control the controlled object by linearly combining the deviation in proportion, integration and differentiation.

[0003] As a linear controller, the conventional PID controller is one of the earliest developed control strategies and the most widely used control strategy in modern chemical process control. Specifically, PID control occupies a dominant position in the control of continuous process industries. It has the advantages of being easy to understand, widely applicable, flexible to adjust, stable and robust.

[0004] Among them, the setting of PID parameters in PID control directly affects the operation effect and quality of the control system. However, there are some common disadvantages in the setting of PID parameters in the prior art: the parameters are difficult to adjust. Summary of the invention

[0005] In view of the above problems, the present application provides a proportional integral differential loop control method and related devices to achieve the purpose of improving the parameter adjustment efficiency in the PID control process. The specific scheme is as follows:

[0006] The first aspect of the present application provides a proportional-integral-differential loop control method, comprising:

[0007] Obtain the set value and current measured value of the controlled object, and determine the deviation of the controlled object based on the set value and the current measured value;

[0008] Input the set value, current measured value and deviation into the data analysis module for processing to obtain the current deviation status information and the current change trend information of the current measured value relative to the set value;

[0009] Inputting the current change trend information and the current deviation state information into the parameter group selection unit, and determining a sub-parameter group matching the current change trend information and the current deviation state information;

[0010] Input the sub-parameter group into the proportional integral derivative control unit to adjust the current measurement value and obtain the current operation value of the controlled object;

[0011] Send the current operation value to the controlled object to control the controlled object.

[0012] In a possible implementation, the change trend information includes convergence and divergence, and the deviation state information is used to indicate the preset state partition to which the deviation belongs; the preset state partition includes a normal area, a low risk area, a medium risk area, and a high risk area; the current measurement value and the deviation are input into the data analysis module for processing to obtain the current change trend information and the current state information of the controlled variable, including:

[0013] The data analysis module is used to analyze the change trend of the current measured value relative to the set value and the preset state partition to which the deviation belongs, so as to obtain the current change trend information and the current state information.

[0014] In a possible implementation, a data analysis module is used to analyze the preset state partition to which the deviation belongs, including:

[0015] The preset partitioning rules are used to analyze the preset state partition to which the deviation belongs; the preset partitioning rules are:

[0016] When the deviation is less than the first preset deviation threshold, the current state information indicates that the deviation belongs to the normal zone;

[0017] When the deviation is greater than a first preset deviation threshold and less than a second preset deviation threshold, the current state information indicates that the deviation belongs to a low risk area;

[0018] When the deviation is greater than the second preset deviation threshold and less than the third preset deviation threshold, the current status information indicates that the deviation belongs to the medium risk area;

[0019] When the deviation is greater than the third preset deviation threshold, the current status information indicates that the deviation belongs to a high risk area.

[0020] In a possible implementation, the parameter group selection unit includes a first parameter group, a second parameter group, a third parameter group, and a fourth parameter group;

[0021] Inputting the current change trend information and the current state information into the parameter group selection unit, and determining the sub-parameter group matching the current change trend information and the current state information, including:

[0022] The preset matching rules are used to match the current change trend information and the current state information to the sub-parameter group; the preset matching rules are:

[0023] When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the normal area, the sub-parameter group is the first parameter group;

[0024] When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the low risk area, the sub-parameter group is the first parameter group;

[0025] When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the medium risk area, the sub-parameter group is the second parameter group;

[0026] When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to a high-risk area, the sub-parameter group is the third parameter group;

[0027] When the current change trend information is divergence, and the current deviation state information indicates that the deviation belongs to the normal area, the sub-parameter group is the first parameter group;

[0028] When the current change trend information is divergence, and the current deviation state information indicates that the deviation belongs to a low risk area, the sub-parameter group is the second parameter group;

[0029] When the current change trend information is divergent, and the current deviation status information indicates that the deviation belongs to the medium risk area, the sub-parameter group is the third parameter group;

[0030] When the current change trend information is divergent, and the current deviation state information indicates that the deviation belongs to a high-risk area, the sub-parameter group is the fourth parameter group.

[0031] In a possible implementation, the method is applied to a user function module or a global function module in a distributed control system, that is, the data analysis module, the parameter group selection unit and the proportional integral differential control unit belong to the user function module or the global function module.

[0032] A second aspect of the present application provides a proportional-integral-differential loop control device, comprising:

[0033] An acquisition unit, a data analysis unit, a parameter group selection unit, a control unit and a sending unit; wherein:

[0034] An acquisition unit, used to acquire a set value and a current measured value of a controlled object, and determine a deviation of the controlled object according to the set value and the current measured value;

[0035] A data analysis unit, used to input the set value, current measurement value and deviation into the data analysis module for processing, and obtain the current deviation state information and the current change trend information of the current measurement value relative to the set value;

[0036] A parameter group selection unit, used to input the current change trend information and the current deviation state information into the parameter group selection unit, and determine a sub-parameter group matching the current change trend information and the current deviation state information;

[0037] A control unit, used for inputting the sub-parameter group into the proportional integral derivative control unit to adjust the current measurement value and obtain the current operation value of the controlled object;

[0038] The sending unit is used to send the current operation value to the controlled object to control the controlled object.

[0039] In a possible implementation, the parameter group selection unit includes a first parameter group, a second parameter group, a third parameter group, and a fourth parameter group;

[0040] Parameter selection unit for:

[0041] The preset matching rules are used to match the current change trend information and the current state information to the sub-parameter group; the preset matching rules are:

[0042] When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the normal area, the sub-parameter group is the first parameter group;

[0043] When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the low risk area, the sub-parameter group is the first parameter group;

[0044] When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the medium risk area, the sub-parameter group is the second parameter group;

[0045] When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to a high-risk area, the sub-parameter group is the third parameter group;

[0046] When the current change trend information is divergence, and the current deviation state information indicates that the deviation belongs to the normal area, the sub-parameter group is the first parameter group;

[0047] When the current change trend information is divergence, and the current deviation state information indicates that the deviation belongs to a low risk area, the sub-parameter group is the second parameter group;

[0048] When the current change trend information is divergent, and the current deviation status information indicates that the deviation belongs to the medium risk area, the sub-parameter group is the third parameter group;

[0049] When the current change trend information is divergent, and the current deviation state information indicates that the deviation belongs to a high-risk area, the sub-parameter group is the fourth parameter group.

[0050] A third aspect of the present application provides a proportional-integral-differential loop control device, comprising at least one processor and a memory connected to the processor, wherein:

[0051] The memory is used to store computer programs;

[0052] The processor is used to execute the computer program so that the electronic device can implement the proportional integral differential loop control method as described in any one of the above items.

[0053] A fourth aspect of the present application provides a computer program product, comprising computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements the proportional-integral-differential loop control method as described in any one of the above.

[0054] In a fifth aspect, the present application provides a computer storage medium, which carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement the proportional-integral-differential loop control method as described in any one of the above.

[0055] By means of the above technical scheme, the proportional integral differential loop control and related devices provided by the present application obtain the set value and the current measured value of the controlled object, calculate the deviation of the controlled object, input the set value, the current measured value and the deviation into the data analysis module, obtain the current deviation state information and the current change trend information of the current measured value relative to the set value, input the current change trend information and the current deviation state information into the parameter group selection unit, determine the sub-parameter group matching the current working condition of the controlled object, and finally, input the sub-parameter group into the proportional integral differential control unit to adjust the current measured value, output the current operating value of the controlled object, and finally, use the current operating value to control the controlled object. The present application can match the sub-parameter group suitable for the current working condition for the controlled object in real time according to the trend change and the deviation state of the controlled variable, use the sub-parameter group to adjust the current measured value, output the current operating value to control the controlled object, and the parameter adjustment efficiency is high. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale.

[0057] Figure 1 A flow chart of a proportional-integral-differential loop control method provided in this application;

[0058] Figure 2 A control schematic diagram of the proportional-integral-differential loop control method provided in this application;

[0059] Figure 3 This is a flow chart of the proportional-integral-differential loop control method provided in this application;

[0060] Figure 4 This is an example diagram of the operation page of the PID controller provided in this application;

[0061] Figure 5 An example diagram for comparing the adjustment effects provided for this application;

[0062] Figure 6 A schematic diagram of the structure of a proportional-integral-differential loop control device provided in this application;

[0063] Figure 7 This is a schematic diagram of the structure of the proportional-integral-differential loop control device provided in this application. DETAILED DESCRIPTION

[0064] The following describes the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. The terms used in the implementation method section of the present application are only used to explain the specific embodiments of the present application, and are not intended to limit the present application.

[0065] The embodiments of the present application are described below in conjunction with the accompanying drawings. Those skilled in the art will appreciate that, with the development of technology and the emergence of new scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0066] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and need not be used to describe a specific order or sequential order. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances, which is only to describe the distinction mode adopted by the objects of the same attributes when describing in the embodiments of the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, so that the process, method, system, product or equipment comprising a series of units need not be limited to those units, but may include other units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0067] PID control is the most widely used control strategy in modern chemical process control. To date, about 90% of control loops still have PID structure, which is composed of three parts: proportional, integral, and differential output. Among them, P is the proportion, specifically the proportional parameter, which mainly determines the response degree of the output signal to the deviation. A higher proportional gain can quickly respond to the deviation change. Proportional control will directly affect the dynamic response speed and accuracy of the system; I is the integral, which can memorize the deviation and is mainly used to eliminate the residual and improve the system's zero difference. The strength of the integral effect depends on the integral time constant Ti. The larger Ti is, the weaker the integral effect is, and vice versa; D is the differential, which can reflect the change trend (rate of change) of the deviation signal and can introduce an effective early correction signal into the system before the deviation signal value becomes too large, thereby speeding up the system's action speed and reducing the adjustment time.

[0068] It should be noted that PID control occupies a dominant position in the field of continuous process control. It has the advantages of being easy to understand, widely applicable, flexible to adjust, stable, and robust. However, there are some common shortcomings in the setting of PID parameters in the prior art: PID parameters are difficult to adjust, and technicians with professional knowledge and experience are required to complete parameter adjustment. The parameter adjustment process takes a long time and the parameter adjustment efficiency is low; the PID control process is sensitive to interference, and improper use of parameters may lead to unstable system output; the performance is limited, and it is difficult to use a set of PID parameters to adapt the entire control process for nonlinear or time-varying systems. Accordingly, nonlinear or time-varying PID loops in known technologies will have poor performance such as oscillation or large residuals due to the inability to adjust parameters in real time, which requires the operating conditions to be switched to manual and requires manual intervention.

[0069] In order to solve the above problems, there are many methods for transformation and innovation of PID control in known technologies. For example, the control loop is evaluated for loop quality, and the PID parameters are adjusted after the oscillation and residual classification conditions are set to overcome the problem of excessive oscillation or residual generated by the loop. This adjustment method requires manual adjustment of the PID parameters of various working conditions and then setting upper and lower limits. The adjustment parameters are adjusted according to a fixed formula, which requires long-term adjustment and professional knowledge. The control calculation design has high requirements on time and memory. Moreover, it will only intervene and make adjustments when oscillation is triggered or the residual is too large, and the adaptability to working conditions is poor.

[0070] Another solution is to calculate the state characteristic vector and noise level based on the change trend of the loop, that is, the first-order derivative and second-order derivative of the deviation, determine the loop state, and control the PID parameters according to the loop state. The calculation process of this method is relatively complex and difficult to configure and implement. It is a process of self-tuning and adjusting the PID parameters. It requires that the field loop can support the production instability risks such as oscillation and divergence caused by its parameter changes before it can be implemented, and when the working conditions change, the function needs to be re-used for re-tuning.

[0071] Another solution is to classify and judge the two arrays based on the loop deviation and the deviation change rate. After obtaining a set of daily PID parameters, it is necessary to separately increase and set the proportional adjustment coefficient, integral adjustment coefficient, differential adjustment coefficient and other parameters. The controller automatically adjusts the PID parameters according to the deviation range and the change rate. This method can realize multi-parameter PID automatic adjustment and control, but its flexibility is poor. It can only set one set of PID parameters. Other PID parameters are fine-tuned and calculated based on the original parameters according to its rules, and cannot be adjusted more adaptably according to loops with different characteristics.

[0072] It can be seen that the PID parameter tuning methods proposed in the known technologies cannot adapt well to different working conditions and have poor working condition adaptability.

[0073] In order to solve the above problems, the present application proposes a proportional-integral-differential loop control method and related devices.

[0074] Optional, see Figure 1 , a flow chart of a proportional-integral-differential loop control method provided in this application.

[0075] like Figure 1 As shown, the proportional integral differential loop control method includes the following steps:

[0076] Step 101: Obtain a set value and a current measured value of a controlled object, and determine a deviation of the controlled object according to the set value and the current measured value.

[0077] In the field of automated control technology in continuous process industries, the controlled objects can be various physical quantities that need to be controlled in the system or process regulated by a PID controller, such as temperature, pressure, flow, liquid level, vehicle speed, etc.

[0078] When the system regulated by the PID controller is a temperature control system, the temperature is the controlled object. For example, in boiler temperature control, the PID controller adjusts the fuel supply and air flow rate according to the deviation of the boiler outlet steam temperature from the set value to keep the boiler outlet steam temperature within the set range;

[0079] When the system regulated by the PID controller is a liquid level control system, the liquid level is the controlled object. For example, in a liquid storage tank, the PID controller can adjust the speed of the feed pump according to the feedback signal of the liquid level sensor to keep the liquid level in the tank stable;

[0080] When the system regulated by the PID controller is a pressure control system, the pressure is the controlled object. For example, in a natural gas pipeline, the PID controller can adjust the speed and valve opening of the compressor according to the pressure sensor signal in the pipeline to keep the pressure in the pipeline stable.

[0081] It should be noted that the current measured value is the output value of the controlled object collected by the sensor. It can be understood that the PID control unit used in this application uses a negative feedback control method to stabilize the state of the controlled object at the desired position, and ultimately eliminates the deviation between the measured value of the controlled object and the set value.

[0082] Specifically, the PID control unit is the core of the PID control algorithm, and the formula is as follows:

[0083] ;

[0084] Among them, PB is the proportionality, which controls the amplitude of the adjustment output; TI is the integral time. The larger the integral time, the weaker the integral effect. TD is the differential time. The larger the differential time, the stronger the differential effect. Let the measured value of the controlled object be PV, and PV represents the actual position of the controlled object. Let the set value of the controlled object be SV, and SV represents the ideal position that the controlled object needs to be in. e(t) is the deviation calculated based on the set value and the measured value, that is, e(t)=SV-PV. Then the PID control unit will calculate a control quantity MV based on the deviation e(t) and act on the actuator. The control quantity can be understood as the operating value acting on the control object for controlling the operation object.

[0085] Optionally, a current measurement value and a set value of the controlled object are obtained from a sensor, and a deviation of the controlled object is calculated based on the current measurement value and the set value.

[0086] Step 102: Input the set value, current measurement value and deviation into the data analysis module for processing to obtain current deviation status information and current change trend information of the current measurement value relative to the set value.

[0087] It should be noted that the data analysis module is mainly used to analyze the trend changes of the controlled variables, the deviation between the current measured value and the set value, and the deviation changes, to obtain the current change trend information of the current measured value relative to the set value and the current deviation status information.

[0088] Optionally, the set value, the current measured value, and the calculated deviation of the controlled object between the current measured value and the set value are input into a data analysis module, which analyzes the changing trend of the current measured value relative to the set value and the preset state partition to which the deviation belongs, to obtain the current changing trend of the controlled object and the current deviation state information.

[0089] It should be noted that the change trend information mainly includes two types: convergence and divergence. When the change of the measured value PV tends to be close to the set value SV, the PID control loop is considered to be convergent. On the contrary, when the change of the measured value PV tends to deviate from the set value SV, the PID control loop is considered to be divergent. The change trend information is mainly used to analyze the controllability of the controlled object; the deviation state information is mainly used to indicate the preset state partition to which the deviation belongs. The preset state partition can include normal area, low risk area, medium risk area and high risk area.

[0090] Specifically, the data analysis module uses a preset division rule to analyze the preset state partition to which the deviation belongs. When the deviation is less than the first preset deviation threshold, the current deviation state information indicates that the deviation belongs to the normal area; when the deviation is greater than the first deviation threshold and less than the second deviation threshold, the current state information indicates that the deviation belongs to the low-risk area; when the deviation is greater than the second preset deviation threshold and less than the third preset deviation threshold, the current state information indicates that the deviation belongs to the medium-risk area; when the deviation is greater than the third preset deviation threshold, the current state information indicates that the deviation belongs to the high-risk area. Among them, the normal area can be understood as the normal deviation area, the low risk area can be understood as the low deviation area, the medium risk area can be understood as the medium deviation area, and the high risk area can be understood as the high deviation area.

[0091] The present application can set different numbers of preset state partitions as needed. Exemplarily, the number of preset state partitions can also be three or five.

[0092] Step 103: input the current change trend information and the current deviation state information into the parameter group selection unit, and determine the sub-parameter group that matches the current change trend information and the current deviation state information.

[0093] The current change trend information and current deviation state information of the control object obtained by the data analysis module are mainly used to select sub-parameter groups in the parameter group selection unit. Different PID parameters are set in the parameter group selection unit according to the change trend of the PID control loop and the adjustment requirements of the deviation state.

[0094] It can be understood that when the number of preset state partitions is four, the sub-parameter groups in the parameter group selection unit correspond to four: the first group of PID parameters, the second group of PID parameters, the third group of PID parameters and the fourth group of PID parameters. That is, multiple groups of PID parameter groups can be divided according to the risk state to adaptively adjust the PID parameters of the PID calculation unit so as to cope with different working conditions.

[0095] The first set of PID parameters is defined for use in the normal area, and is mainly used for situations where the controlled object fluctuates slightly during daily production. At this time, the control is based on the normal production PID debugging parameters, with the purpose of reducing the output change of the operating value MV acting on the controlled object and fine-tuning the PID parameters of the loop. In addition, when the PID control loop data belongs to the low-risk area and converges, it is determined that the measured value of the loop data tends to the set value, and the first set of PID parameters is also selected to control the controlled object.

[0096] The second set of PID parameters is defined for use in low-risk areas, and is mainly used when the loop data is in a low deviation area and divergent, or when the loop data is in a medium deviation area and convergent. At this time, the second set of PID parameters is mainly proportional control, slightly strengthening the integral effect and appropriately increasing the differential. The output amplitude of the second set of PID control parameters is significantly increased relative to the first set of PID control parameters, with the goal of suppressing loop divergence and ensuring that the output direction is opposite to the direction of change of the current measured value. It should be noted that the output amplitude specifically refers to the sum of the proportional action, integral action and differential action and then output to the operation value. The reason why the output amplitude of the second group of PID parameters is larger than that of the first group of PID parameters is that the first group of PID parameters is used to maintain the current stable state of the PID control loop, and only the current measured value needs to be fine-tuned. When the first group of PID parameters is used for fine-tuning and can no longer meet the control requirements, it is necessary to increase the output to return the measured value to the set value as soon as possible. Therefore, it is necessary to increase the output amplitude. The reason why the output amplitude of the third and fourth groups of PID parameters increases is also because the adjustment amplitude of the current measured value of the previous group can no longer meet the control requirements; further, the output amplitude of the second group of PID control parameters is significantly increased relative to the first group of PID control parameters because the proportional action and differential action are adjusted, so as to suppress the change of the current measured value from the target value as soon as possible.

[0097] The third group of PID parameters is defined for use in the medium-risk area. It is mainly used when the loop data is in the medium deviation area and diverges, or when the loop data is in the high deviation area and converges. This group of PID parameters further strengthens the proportional control, and the integral effect is enhanced relative to the second group of parameters. The differential is converted according to the formula to keep the differential output unchanged. At this time, the output amplitude increases relative to the second group of parameters. This group of parameters also aims to suppress loop divergence to ensure that the output direction is opposite to the direction of change of the current measured value.

[0098] The fourth group of PID parameters is defined for use in high-risk areas. It is mainly used when the loop data is in a high deviation area and diverges. At this time, it can be determined that the operating conditions have changed. If the loop is not adjusted as soon as possible, it will be out of control. This group of PID parameters will further strengthen the proportional control, and the integral will be enhanced relative to the third group of parameters. The differential is converted according to the formula to keep the differential output unchanged. At this time, the output amplitude increases relative to the third group of parameters. This group of parameters also aims to suppress loop divergence to ensure that the output direction is opposite to the direction of change of the current measured value.

[0099] It can be seen that the adjustment of the adjacent sub-parameter groups in the parameter group selection unit to the current measurement value is gradual and progressive, especially the proportionality in the sub-parameter group, which cannot be adjusted too much at one time, otherwise it will easily cause output jump value.

[0100] Optionally, the parameter group selection unit uses a preset matching rule to match the sub-parameter group for the current change trend information and the current state information.

[0101] The preset matching rules are as follows:

[0102] Determine whether the change trend of the current measured value relative to the set value is divergent or convergent.

[0103] When the current change trend information is convergence and the current deviation state information is in the normal zone, the first group of PID parameters is selected to be written into the PID control unit, and the operation value is output after adjusting the current measurement value to control the control object;

[0104] When the current change trend information is convergence and the current deviation state information is in a low risk zone, the first group of PID parameters is selected to be written into the PID control unit, and the operation value is output after adjusting the current measurement value to control the control object;

[0105] When the current change trend information is convergence and the current deviation state information is in the medium risk zone, the second group of PID parameters is selected to be written into the PID control unit, and the operation value is output after adjusting the current measurement value to control the control object;

[0106] When the current change trend information is convergence and the current deviation state information is in a high-risk area, the third group of PID parameters is selected to be written into the PID control unit, and the operation value is output after adjusting the current measurement value to control the control object;

[0107] When the current change trend information is divergent and the current deviation state information is in the normal zone, the first group of PID parameters is selected to be written into the PID control unit, and the operation value is output after adjusting the current measurement value to control the control object;

[0108] When the current change trend information is divergent and the current deviation state information is in a low risk zone, the second group of PID parameters is selected to be written into the PID control unit, and the operation value is output after adjusting the current measurement value to control the control object;

[0109] When the current change trend information is divergent and the current deviation state information is in the medium risk zone, the third group of PID parameters is selected to be written into the PID control unit, and the operation value is output after adjusting the current measurement value to control the control object;

[0110] When the current change trend information is divergent and the current deviation state information is in a high-risk area, the fourth group of PID parameters is selected to be written into the PID control unit, and the operation value is output after adjusting the current measurement value to control the control object.

[0111] Step 104: Input the sub-parameter group into the proportional-integral-derivative control unit to adjust the current measurement value to obtain the current operating value of the controlled variable.

[0112] The sub-parameter group determined in the parameter group selection unit and matching the change trend and deviation state of the current measurement value is input into the proportional integral differential control unit (PID control unit), and the PID control unit adjusts the current measurement value and outputs the adjusted current operation value of the controlled object.

[0113] Step 105: Send the current operation value to the controlled object to control the controlled object.

[0114] Finally, the current operating value is sent to the controlled object to adjust the current measured value while fitting the working conditions of the PID control loop.

[0115] Optional, see Figure 2 , a control schematic diagram of the proportional-integral-differential loop control method provided in this application.

[0116] like Figure 2 As shown, the PID control unit in the present application adopts a negative feedback control method to stabilize the state of the controlled object at the desired position in order to eliminate the difference between the measured value and the set value. On this basis, a data analysis module and a P / I / D parameter group are added.

[0117] Among them, the data analysis module is used to analyze the trend change of the controlled variable and the state area where the deviation is located based on the set value SV, the measured value PV and the deviation e(t) between the set value and the measured value of the controlled object; the data analysis module will input the trend change of the controlled variable and the state area where the deviation is located into the P / I / D parameter group, and the P / I / D parameter group will determine the PID parameter group that matches the state area where the trend change and the deviation are located for the controlled variable. This step can be understood as the P / I / D parameter group selects the parameter group for adjusting the controlled variable that matches the current working condition of the control variable from the pre-set parameter group for the control variable. After that, the P / I / D parameter group will input the selected parameter group into the PID control unit, and the PID control unit will adjust the current measured value and output the operation value MV to act on the controlled object.

[0118] It should be noted that the proportional integral differential loop control method provided in the present application can be implemented in a user function module or a global function module in a distributed control system. Accordingly, the data analysis module, the P / I / D parameter group, and the PID control unit are all located in the user function module or the global function module. The distributed control system may be a DCS (Distributed Control System). The user function module and the global function module are the basic functions of the DCS control system, which can be designed by the user to implement unconventional logic programming and repeatedly called during configuration.

[0119] Exemplarily, the proportional-integral-differential loop control method provided in the present application can run on the ECS-700 platform of the DCS control system. On the basis of the original PID control unit, the PID algorithm and operating parameters are automatically adjusted based on the changing trend of the controlled variables and the loop deviation light information, thereby realizing the demand for automatic operation of the PID control loop under all working conditions.

[0120] In summary, the proportional integral differential loop control method provided by the present application obtains the set value and the current measured value of the controlled object, calculates the deviation of the controlled object, inputs the set value, the current measured value and the deviation into the data analysis module, obtains the current deviation state information and the current change trend information of the current measured value relative to the set value, inputs the current change trend information and the current deviation state information into the parameter group selection unit, determines the sub-parameter group that matches the current working condition of the controlled object, and finally, inputs the sub-parameter group into the proportional integral differential control unit to adjust the current measured value, outputs the current operating value of the controlled object, and finally, uses the current operating value to control the controlled object. The present application can match the sub-parameter group suitable for the current working condition for the controlled object in real time according to the trend change and the deviation state of the controlled variable, uses the sub-parameter group to adjust the current measured value, and outputs the current operating value to control the controlled object, and the parameter adjustment efficiency is high.

[0121] It should be noted that the sources of the relevant parameters involved in the proportional integral differential loop control process involve the real-time data and historical filtering data of the PID control loop in the DCS. The main parameters and descriptions are shown in Table 1:

[0122] Table 1

[0123] parameter describe parameter describe DSV1 Set Deviation 1 PB2 The ratio of the second set of parameters DSV2 Set deviation 2, which must be greater than DSV1 TI2 Integration of the second set of parameters DSV3 Set deviation 3, which must be greater than DSV2 TD2 Differentiation of the second set of parameters DPV Absolute value of deviation PB3 The ratio of the third set of parameters UP Convergence detection (1 convergence / 0 divergence) TI3 Integration of the third set of parameters PB Ratio output TD3 Differentiation of the third set of parameters TI Integral output PB4 The ratio of the fourth group of parameters TD Differential output TI4 The fourth set of parameters PIDID PID parameter group number TD4 Differentiation of the fourth set of parameters PB1 The ratio of the first set of parameters PV Measurements TI1 Integration of the first set of parameters SV Settings TD1 Differentiation of the first set of parameters MV Operation Value

[0124] Among them, the calculation formula of the absolute value of deviation DPV is: DPV=ABS(SV-PV);

[0125] The judgment basis of convergence detection UP can be: formula [ABS (PV's 10s filter value - SV) > ABS (PV's 3s filter value - SV)]. When it is satisfied, the change trend of the PID control loop is determined to be divergent, that is, UP=1 converges, and UP=0 diverges.

[0126] For example, see Figure 3 , an example flow chart of the proportional-integral-differential loop control method provided in this application.

[0127] First, the PID control loop data is preprocessed to calculate the current deviation absolute value DPV. Then, the convergence / divergence status of the PID control loop data is monitored UP and the calculation results are output to the data analysis module. The data analysis module reads the deviation area setting parameters, deviation 1 (DSV1), deviation 2 (DSV2) and deviation 3 (DSV3).

[0128] Next, determine whether the PID control loop converges, that is, determine whether UP is equal to 1. When UP=1, that is, the PID control loop converges, when DPV<DSV1, that is, the absolute value of the deviation is less than deviation 1, the PID parameters of parameter group 1 are assigned to the corresponding parameters of the PID loop, and input into the PID control unit to calculate the result output; when DPV>DSV1 and DPV<DSV2, that is, the absolute value of the deviation is greater than deviation 1 and less than deviation 2, the PID parameters of parameter group 1 are assigned to the corresponding parameters of the PID loop, and input into the PID control unit to calculate the result output; when DPV>DSV2 and DPV<DSV3, that is, the absolute value of the deviation is greater than deviation 2 and less than deviation 3, the PID parameters of parameter group 2 are assigned to the corresponding parameters of the PID loop, and input into the PID control unit to calculate the result output; when DPV>DSV3, that is, the absolute value of the deviation is greater than deviation 3, the PID parameters of parameter group 3 are assigned to the corresponding parameters of the PID loop, and input into the PID control unit to calculate the result output.

[0129] When UP≠1, that is, UP=0, the PID control loop diverges, when DPV<DSV1, that is, the absolute value of the deviation is less than deviation 1, the PID parameters of parameter group 1 are assigned to the corresponding parameters of the PID loop, and are input into the PID control unit to calculate the result output; when DPV>DSV1 and DPV<DSV2, that is, the absolute value of the deviation is greater than deviation 1 and less than deviation 2, the PID parameters of parameter group 2 are assigned to the corresponding parameters of the PID loop, and are input into the PID control unit to calculate the result output; when DPV>DSV2 and DPV<DSV3, that is, the absolute value of the deviation is greater than deviation 2 and less than deviation 3, the PID parameters of parameter group 3 are assigned to the corresponding parameters of the PID loop, and are input into the PID control unit to calculate the result output; when DPV>DSV3, that is, the absolute value of the deviation is greater than deviation 3, the PID parameters of parameter group 4 are assigned to the corresponding parameters of the PID loop, and are input into the PID control unit to calculate the result output.

[0130] In summary, the proportional integral differential loop control process provided by the present application can adaptively adjust the PID parameters to meet the production needs of the entire regulation process, reduce the intervention of operators, and improve the control performance of the control loop. Specifically, after the PID parameters of each working condition are adjusted, the parameters are automatically switched according to the trend change of the controlled variable, the deviation between the measured value and the set value, and the change of the deviation, so as to realize the change of the output response of the PID control loop in the control direction and control amplitude, and meet the needs of reagent control. It can be fine-tuned when the controlled variable fluctuates slightly, and can be adjusted in time and significantly when it fluctuates greatly or has a long-term deviation, so as to overcome the abnormal changes of the controlled variable. Configuration and debugging are relatively simple, can be replicated, and no additional investment is required.

[0131] Specifically, the control direction is obtained by summing the proportional action, the integral action and the differential action. The proportional action is mainly to output the change of the deviation, the integral action is to integrate and accumulate the deviation, and the differential action is to make advance adjustments to the change trend of the measured value. The larger the proportional value, the larger the output change value, the larger the integral value, the weaker the integral effect, that is, the longer the time to return to the set value, the larger the differential value, the stronger the differential effect, and the earlier the advance adjustment time. It can be understood that the proportionality affects the control amplitude, and the integral and differential affect the change of the control direction.

[0132] The proportional-integral-derivative loop control method provided in the present application may exist in the form of a multi-parameter PID controller.

[0133] For example, see Figure 4 , an example diagram of the operation page of the PID controller provided in this application.

[0134] like Figure 4As shown in the figure, the upper part of the operation panel is the basic information of the PID controller operation. Click the bit number link to jump to the PID operation panel of the corresponding control loop for operation; the set value, measured value and operation value display the real-time parameters of the current control loop; the proportionality PB, integral TI and differential TD display the current running PID parameters, and as the data analysis module continues to analyze, it further matches the PID parameters of different groups. The loop detection and deviation calculation display the current status of the data analysis module analysis, which is convenient for operators to judge whether the deviation setting is appropriate.

[0135] The lower part of the operation panel is the deviation setting and PID parameter group. The parameter setting area sets the low deviation area, medium deviation area, and high deviation area according to the characteristics of the loop:

[0136] aWhen the deviation is less than the low deviation area or the deviation is greater than the low deviation area and the loop converges, the control loop selects the normal area PID group for normal adjustment, and the font of the corresponding PID parameter group "Normal Area" turns green.

[0137] bWhen the deviation is greater than the low deviation area and the loop diverges or when the deviation is greater than the medium deviation area and the loop converges, the control loop selects the low deviation area PID group with faster adjustment, and the font of the corresponding PID parameter group "low risk area" turns green.

[0138] cWhen the deviation is greater than the medium deviation area and the loop diverges or when the deviation is greater than the high deviation area and the loop converges, the control loop selects the medium deviation area PID group with faster adjustment, and the font of the corresponding PID parameter group "Medium Risk Area" turns green.

[0139] dWhen the deviation is greater than the high deviation area and the loop diverges, the control loop selects the high deviation area PID group with faster adjustment, and the font of the "high risk area" of the corresponding PID parameter group turns green.

[0140] Furthermore, the control principle and logic of the multi-parameter PID controller are as follows:

[0141] In order for the multi-parameter PID controller to operate normally, the following basic conditions must be met:

[0142] Condition 1: Currently in normal production status.

[0143] Condition 2: The loop is in automatic state and the loop output value has adjustable space.

[0144] The execution process of the controller is divided into the following four parts: The first part: The data analysis module preprocesses the loop data and calculates the absolute value of the current deviation DPV and the value of the state detection UP; The second part: The deviation setting parameters of the module are read, and the risk area state of the current loop is judged through comparative analysis; The third part: According to the risk area state division, the corresponding P / I / D group values are written to the PID control unit; The fourth part: The PID control unit calculates according to the given P / I / D parameter group and outputs the result to the output value MV. The following takes the liquid level as an example to introduce the specific logic.

[0145] Read the set value SV and the measured value PV of the current loop, calculate their deviation and take the absolute value to obtain the absolute value of the deviation DPV, and input it into the controller internally, that is, DPV = ABS(PV - SV); Calculate the average value within the previous 10s and the average value within the previous 3s of the measured value, respectively calculate the deviation from the set value SV, take the absolute value of the two deviations respectively, and compare their sizes. When the 10s deviation data is greater than the 3s data, the measured value tends to the set value, and the loop can be judged to be convergent, otherwise it is divergent. It can be expressed by the formula as follows: DPV10S = ABS(AVG(PV, NOW, -10S) - SV), DPV3S = ABS(AVG(PV, NOW, -3S) - SV). If DPV10S > DPV3S holds, then UP = 1, otherwise UP = 0.

[0146] Read the setting parameters DSV1 / DSV2 / DSV3. When UP = 1 and the loop is convergent, if DPV < DSV1 holds, the current is the normal area; if DPV > DSV1 and DPV < DSV2 holds, the current is the normal area; if DPV > DSV2 and DPV < DSV3 holds, the current is the low-risk area; if DPV > DSV3 holds, the current is the medium-risk area. When UP = 0 and the loop is divergent, if DPV < DSV1 holds, the current is the normal area; if DPV > DSV1 and DPV < DSV2 holds, the current is the low-risk area; if DPV > DSV2 and DPV > DSV3 holds, the current is the medium-risk area; if DPV > DSV3 holds, the current is the high-risk area. The risk area division is completed.

[0147] According to the status of the risk area, select the corresponding P / I / D parameter group to write into the PID control unit. The normal area selects the first group of PID parameters, that is, PB=PB1, TI=TI1, TD=TD1, PIDID=1; the low-risk area selects the second group of PID parameters, that is, PB=PB2, TI=TI2, TD=TD2, PIDID=2; the medium-risk area selects the third group of PID parameters, that is, PB=PB3, TI=TI3, TD=TD3, PIDID=3; the high-risk area selects the fourth group of PID parameters, that is, PB=PB4, TI=TI4, TD=TD4, PIDID=4.

[0148] Finally, the PID calculation unit performs PID calculation according to the adaptively selected P / I / D group and gives the calculation result to the output value.

[0149] The proportional-integral-differential loop control is carried out with the temperature of the distillation tower as the control object. The example is as follows:

[0150] The air cooling of the distillation tower top is controlled by 4 fans, two industrial frequency and two variable frequency. One or two of the two industrial frequency fans are turned on according to demand, and the two variable frequency fans are controlled by PID control loop. When the working conditions change, such as stopping one industrial frequency fan or it suddenly rains in summer, the temperature fluctuates greatly, and the PID control loop output needs to be adjusted significantly, and the operator may even switch to manual adjustment. After using the multi-parameter PID controller, the PID control loop can adjust the output in a timely and appropriate manner according to the needs without the need for operator intervention.

[0151] See also Figure 5 , an example diagram for comparing the adjustment effects provided in this application.

[0152] On the left is the result of adjustment using a conventional PID control unit. It can be seen that the output of the adjustment process is slow, and the loop cannot be adjusted back to the normal range in time when the fluctuation is large. On the right is the effect after using a multi-parameter PID controller. PB changes and adjusts according to different risk states. When the operating conditions change greatly, the output value MV can be adjusted in time and significantly to meet the control requirements of the loop and meet the process control requirements.

[0153] To sum up, the proportional integral differential loop control method provided by this application has high control accuracy, does not require human intervention, has clear control logic, is easy to maintain and modify, has a wide range of applicable controlled objects, and can be promoted as a conventional control scheme without the need for additional investment in external servers.

[0154] A proportional-integral-differential loop control method provided in an embodiment of the present application is introduced above, and a device for executing the above-mentioned proportional-integral-differential loop control method will be introduced below.

[0155] See also Figure 6 , Figure 6 This is a schematic diagram of the structure of a proportional-integral-differential loop control device provided in this application. Figure 6 As shown, the device comprises:

[0156] Acquisition unit 10, data analysis unit 20, parameter group selection unit 30, control unit 40 and sending unit 50; wherein:

[0157] An acquisition unit 10 is used to acquire a set value and a current measured value of a controlled object, and determine a deviation of the controlled object according to the set value and the current measured value;

[0158] The data analysis unit 20 is used to input the set value, the current measured value and the deviation into the data analysis module for processing, and obtain the current deviation state information and the current change trend information of the current measured value relative to the set value;

[0159] The parameter group selection unit 30 is used to input the current change trend information and the current deviation state information into the parameter group selection unit, and determine the sub-parameter group matching the current change trend information and the current deviation state information;

[0160] A control unit 40, for inputting the sub-parameter group into the proportional integral derivative control unit to adjust the current measurement value to obtain the current operation value of the controlled object;

[0161] The sending unit 50 is used to send the current operation value to the controlled object to control the controlled object.

[0162] In one embodiment, the change trend information in the data analysis unit 20 includes convergence and divergence, and the deviation state information is used to indicate the preset state partition to which the deviation belongs; the preset state partition includes a normal area, a low risk area, a medium risk area, and a high risk area; the data analysis unit 20 is specifically used to:

[0163] The data analysis module is used to analyze the change trend of the current measured value relative to the set value and the preset state partition to which the deviation belongs, so as to obtain the current change trend information and the current state information.

[0164] In one embodiment, the data analysis unit 20 is specifically configured to:

[0165] The preset partitioning rules are used to analyze the preset state partition to which the deviation belongs; the preset partitioning rules are:

[0166] When the deviation is less than the first preset deviation threshold, the current state information indicates that the deviation belongs to the normal zone;

[0167] When the deviation is greater than a first preset deviation threshold and less than a second preset deviation threshold, the current state information indicates that the deviation belongs to a low risk area;

[0168] When the deviation is greater than the second preset deviation threshold and less than the third preset deviation threshold, the current status information indicates that the deviation belongs to the medium risk area;

[0169] When the deviation is greater than the third preset deviation threshold, the current status information indicates that the deviation belongs to a high risk area.

[0170] In one embodiment, the data analysis unit 20 includes a first parameter group, a second parameter group, a third parameter group, and a fourth parameter group;

[0171] The data analysis unit 20 is specifically used for:

[0172] Inputting the current change trend information and the current state information into the parameter group selection unit, and determining the sub-parameter group matching the current change trend information and the current state information, including:

[0173] The preset matching rules are used to match the current change trend information and the current state information to the sub-parameter group; the preset matching rules are:

[0174] When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the normal area, the sub-parameter group is the first parameter group;

[0175] When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the low risk area, the sub-parameter group is the first parameter group;

[0176] When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the medium risk area, the sub-parameter group is the second parameter group;

[0177] When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to a high-risk area, the sub-parameter group is the third parameter group;

[0178] When the current change trend information is divergence, and the current deviation state information indicates that the deviation belongs to the normal area, the sub-parameter group is the first parameter group;

[0179] When the current change trend information is divergence, and the current deviation state information indicates that the deviation belongs to a low risk area, the sub-parameter group is the second parameter group;

[0180] When the current change trend information is divergent, and the current deviation status information indicates that the deviation belongs to the medium risk area, the sub-parameter group is the third parameter group;

[0181] When the current change trend information is divergent, and the current deviation state information indicates that the deviation belongs to a high-risk area, the sub-parameter group is the fourth parameter group.

[0182] In one embodiment, the device is applied to a user function module or a global function module in a distributed control system, that is, a data analysis module, a parameter group selection unit and a proportional integral differential control unit belong to the user function module or the global function module.

[0183] The present application also provides a proportional integral differential circuit device in an embodiment. Figure 7 As shown, it shows a schematic diagram of a structure suitable for implementing the proportional-integral-differential loop control device provided by the present application. The proportional-integral-differential loop control device in the embodiment of the present application may include but is not limited to fixed terminals such as mobile phones, laptops, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, etc. Figure 7 The proportional-integral-derivative loop control device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0184] like Figure 7 As shown, the proportional-integral-differential loop control device may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage device 608 to a random access memory (RAM) 603. When the proportional-integral-differential loop control device is powered on, various programs and data required for the operation of the proportional-integral-differential loop control device are also stored in the RAM 603. The processing device 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0185] Typically, the following devices may be connected to the I / O interface 605: input devices 606 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 607 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 608 including, for example, a memory card, a hard disk, etc.; and communication devices 609. The communication device 609 may allow the PID control device to communicate with other devices wirelessly or by wire to exchange data. Although Figure 7 A proportional-integral-derivative loop control apparatus having various devices is shown, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead.

[0186] An embodiment of the present application also provides a computer program product including computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements any proportional-integral-differential loop control method provided in the embodiment of the present application.

[0187] A computer-readable storage medium is also provided in an embodiment of the present application. The storage medium carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any proportional-integral-differential loop control method provided in an embodiment of the present application.

[0188] It should also be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the drawings of the device embodiments provided by the present application, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines.

[0189] Through the description of the above implementation mode, the technicians in the field can clearly understand that the present application can be implemented by means of software plus necessary general hardware, and of course, it can also be implemented by special hardware including special integrated circuits, special CPUs, special memories, special components, etc. In general, all functions completed by computer programs can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be various, such as analog circuits, digital circuits or special circuits. However, for the present application, software program implementation is a better implementation mode in more cases. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a readable storage medium, such as a computer floppy disk, a U disk, a mobile hard disk, a ROM, a RAM, a magnetic disk or an optical disk, etc., including a number of instructions to enable a computer device (which can be a personal computer, a training device, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0190] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product.

[0191] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a training device or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, training device or data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a training device, a data center, etc. that includes one or more available media integration. Available media can be magnetic media, (e.g., floppy disk, hard disk, tape), optical media (e.g., DVD), or semiconductor media (e.g., solid-state hard disk (SSD)), etc.

Claims

1. A proportional integral differential loop control method, characterized in that: include: Obtaining a set value and a current measured value of a controlled object, and determining a deviation of the controlled object according to the set value and the current measured value; Inputting the set value, the current measured value and the deviation into a data analysis module for processing to obtain current deviation state information and current change trend information of the current measured value relative to the set value; Inputting the current change trend information and the current deviation state information into a parameter group selection unit, and determining a sub-parameter group matching the current change trend information and the current deviation state information; Inputting the sub-parameter group into a proportional-integral-derivative control unit to adjust the current measurement value to obtain a current operation value of the controlled object; The current operation value is sent to the controlled object to control the controlled object.

2. The proportional-integral-differential loop control method according to claim 1, characterized in that: The change trend information includes convergence and divergence, and the deviation state information is used to indicate the preset state partition to which the deviation belongs; the preset state partition includes a normal area, a low risk area, a medium risk area, and a high risk area; the current measurement value and the deviation are input into the data analysis module for processing to obtain the current change trend information and the current state information of the controlled variable, including: The data analysis module is used to analyze the change trend of the current measurement value relative to the set value and the preset state partition to which the deviation belongs, so as to obtain the current change trend information and the current state information.

3. The proportional-integral-differential loop control method according to claim 2, characterized in that: The adopting the data analysis module to analyze the preset state partition to which the deviation belongs includes: The preset state partition to which the deviation belongs is analyzed using a preset partition rule; the preset partition rule is: When the deviation is less than a first preset deviation threshold, the current state information indicates that the deviation belongs to a normal zone; When the deviation is greater than a first preset deviation threshold and less than a second preset deviation threshold, the current state information indicates that the deviation belongs to a low risk area; When the deviation is greater than a second preset deviation threshold and less than a third preset deviation threshold, the current state information indicates that the deviation belongs to a medium risk area; When the deviation is greater than a third preset deviation threshold, the current status information indicates that the deviation belongs to a high risk area.

4. The proportional-integral-differential loop control method according to claim 1, characterized in that: The parameter group selection unit includes a first parameter group, a second parameter group, a third parameter group and a fourth parameter group; The step of inputting the current change trend information and the current state information into a parameter group selection unit and determining a sub-parameter group matching the current change trend information and the current state information comprises: The preset matching rule is used to match the current change trend information and the current state information to the sub-parameter group; the preset matching rule is: When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the normal area, the sub-parameter group is the first parameter group; When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the low risk area, the sub-parameter group is the first parameter group; When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the medium risk area, the sub-parameter group is the second parameter group; When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the high risk area, the sub-parameter group is the third parameter group; When the current change trend information is divergent, and the current deviation state information indicates that the deviation belongs to the normal area, the sub-parameter group is the first parameter group; When the current change trend information is divergent, and the current deviation state information indicates that the deviation belongs to the low risk area, the sub-parameter group is the second parameter group; When the current change trend information is divergent, and the current deviation state information indicates that the deviation belongs to the medium risk area, the sub-parameter group is the third parameter group; When the current change trend information is divergent, and the current deviation state information indicates that the deviation belongs to the high-risk area, the sub-parameter group is the fourth parameter group.

5. The proportional-integral-differential loop control method according to claim 1, characterized in that: The method is applied to a user function module or a global function module in a decentralized control system, that is, the data analysis module, the parameter group selection unit and the proportional-integral-differential control unit belong to the user function module or the global function module.

6. A proportional-integral-differential loop control device, characterized in that: include: An acquisition unit, a data analysis unit, a parameter group selection unit, a control unit and a sending unit; wherein: The acquisition unit is used to acquire a set value and a current measurement value of the controlled object, and determine a deviation of the controlled object according to the set value and the current measurement value; The data analysis unit is used to input the set value, the current measurement value and the deviation into the data analysis module for processing to obtain current deviation state information and current change trend information of the current measurement value relative to the set value; The parameter group selection unit is used to input the current change trend information and the current deviation state information into the parameter group selection unit, and determine a sub-parameter group matching the current change trend information and the current deviation state information; The control unit is used to input the sub-parameter group into a proportional-integral-derivative control unit to adjust the current measurement value to obtain a current operation value of the controlled object; The sending unit is used to send the current operation value to the controlled object to control the controlled object.

7. The proportional-integral-differential loop control device according to claim 6, characterized in that: The parameter group selection unit includes a first parameter group, a second parameter group, a third parameter group and a fourth parameter group; The parameter selection unit is used to: The preset matching rule is used to match the current change trend information and the current state information to the sub-parameter group; the preset matching rule is: When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the normal area, the sub-parameter group is the first parameter group; When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the low risk area, the sub-parameter group is the first parameter group; When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the medium risk area, the sub-parameter group is the second parameter group; When the current change trend information is convergence, and the current deviation state information indicates that the deviation belongs to the high risk area, the sub-parameter group is the third parameter group; When the current change trend information is divergent, and the current deviation state information indicates that the deviation belongs to the normal area, the sub-parameter group is the first parameter group; When the current change trend information is divergent, and the current deviation state information indicates that the deviation belongs to the low risk area, the sub-parameter group is the second parameter group; When the current change trend information is divergent, and the current deviation state information indicates that the deviation belongs to the medium risk area, the sub-parameter group is the third parameter group; When the current change trend information is divergent, and the current deviation state information indicates that the deviation belongs to the high-risk area, the sub-parameter group is the fourth parameter group.

8. A proportional-integral-differential loop control device, characterized in that: The method comprises at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is used to execute the computer program so that the electronic device can implement the proportional-integral-differential loop control method as claimed in any one of claims 1 to 5.

9. A computer program product, characterized in that The invention comprises computer-readable instructions, and when the computer-readable instructions are executed on an electronic device, the electronic device implements the proportional-integral-differential loop control method as claimed in any one of claims 1 to 5.

10. A computer storage medium, characterized in that: The storage medium carries one or more computer programs, and when the one or more computer programs are executed by an electronic device, the electronic device can implement the proportional-integral-differential loop control method as described in any one of claims 1 to 5.

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