Reverse control methods for food and pharmaceutical manufacturing processes

Abstract

The present invention discloses an inverse control method for food and pharmaceutical manufacturing processes, which includes step S1: determining an expected output trajectory, which is the manufacturing process target, based on the product needs of food and pharmaceutical manufacturing, and constructing a process kinetic model based on a biochemical reaction process; step S2: back-calculating the process kinetic model based on the manufacturing process target to obtain a corresponding manufacturing process control curve, which is a manufacturing operation process; and step S3: using the manufacturing operation process to perform control operations to achieve the food and pharmaceutical manufacturing target based on the specified food and pharmaceutical manufacturing target. The present invention overcomes the drawbacks of traditional experimental methods, which require a large number of personnel, materials, and time, and more effectively and quickly obtains a manufacturing process control plan, providing a solution for the rapid design of control plans for different products and resolving the difficult problem of dynamic control process design.

Description

Technical Field

[0001] The present invention relates to the technical field of dynamic control of biochemical reaction processes under a predetermined manufacturing process target, and specifically relates to a reverse control method for food and pharmaceutical manufacturing processes.

Background Art

[0002] With the development of the world economy and the progress of society, in order to meet the increasing living needs of people day by day, the manufacturing method of small lots, high profits, and many varieties represented by industrial biochemistry technology is highly regarded. Food and pharmaceutical manufacturing generally involves biochemical changes or reaction processes, and the product target is determined by the control process of important variables such as the temperature, flow rate, and concentration of the manufacturing process. Once the process is determined, field digital controllers, industrial distributed control systems (DCS), etc. perform real-time control according to the process curve, and thereby the final manufacturing requirements or product targets can be achieved.

[0003] The design of the manufacturing control process is closely related to the quality, production volume, and manufacturing time of products, etc. For the food and pharmaceutical industries, the control process design is the basis of manufacturing. The diversification of product types places higher requirements on the rapid design of the control process and is also a major part of realizing smart manufacturing. Generally, the control process is mainly obtained through repeated experiments by technicians, but the experimental method requires a large amount of personnel, materials, and time, and it is particularly difficult to adapt to the manufacturing needs of many varieties, small lots, and multiple targets due to modern smart manufacturing. Also, it is difficult to obtain a dynamic manufacturing operation process with the conventional experimental design method.

Summary of the Invention

Problems to be Solved by the Invention

[0004] This invention provides a reverse control method for food and pharmaceutical manufacturing processes. It constructs a process dynamics model based on biochemical reaction processes, reverse-engineers the process dynamics model, and determines the manufacturing operation process under predetermined manufacturing targets while ensuring the stability of process dynamics changes. This solves the problem that conventional experimental methods require a large amount of personnel, materials, and time, and allows for more effective and rapid acquisition of control steps in the manufacturing process. It provides a solution for the rapid design of control steps for different products and solves the difficult problem of dynamic control process design. [Means for solving the problem]

[0005] To solve the above technical problems, embodiments of the present invention provide a reverse control method for food and pharmaceutical manufacturing processes, and this method is Step S1 involves determining the expected output trajectory, which is the manufacturing process target, based on the product requirements for food and pharmaceutical manufacturing, and constructing a process dynamics model based on the biochemical reaction process. Based on the aforementioned manufacturing process objectives, the process dynamics model is reverse-engineered to obtain the corresponding manufacturing process control curve, and the manufacturing process control curve is defined as the manufacturing operation step S2, The process includes step S3, which involves performing control operations using the manufacturing process to achieve predetermined manufacturing targets for food and pharmaceuticals.

[0006] In one embodiment of the present invention, in step S1, the process dynamics model is defined as the following process state equation: JPEG0007852950000001.jpg33170JPEG0007852950000002.jpg32170To make it easier to show, the above process state equation is expressed in vector form, JPEG0007852950000003.jpg92170

[0007] JPEG0007852950000004.jpg86170JPEG0007852950000005.jpg64170JPEG0007852950000006.jpg121170To simplify, the above expression is taken in the following vector form: JPEG0007852950000007.jpg53170JPEG0007852950000008.jpg19170JPEG0007852950000009.jpg30170

[0008] JPEG0007852950000010.jpg55170 Internal Dynamics JPEG0007852950000011.jpg65170

[0009] In one embodiment of the present invention, step S2 involves the following specific steps for determining the manufacturing process control curve: Step S21: The expected output trajectory is known to be external dynamics, and internal dynamics are obtained. Step S22: Based on the internal dynamics and the inverse model between internal and external dynamics obtained above, obtain the manufacturing process control curve. In step S21, the specific steps for obtaining internal dynamics are as follows: Step S211: Construct the nonlinear internal dynamic equations, JPEG0007852950000012.jpg11170JPEG0007852950000013.jpg21170 Step S212: Convert the above nonlinear internal dynamic equation into an integral equation, JPEG0007852950000014.jpg8170JPEG0007852950000015.jpg94170 Step S213: Solve the above approximate integral equation using the Picard iterative method, JPEG0007852950000016.jpg 36170 Step S214: Obtain the internal dynamics of the vector form using the discretization method. JPEG0007852950000017.jpg70170JPEG0007852950000018.jpg11170 Here, M is the reversible internal dynamics decomposition matrix, JPEG0007852950000019.jpg44170

[0010] JPEG0007852950000020.jpg67170

[0011] In one embodiment of the present invention, the process dynamics model is a relational equation for material balance, thermal balance, and energy balance between materials.

[0012] In one embodiment of the present invention, the manufacturing process objective includes the requirement for product manufacturing, with concentration and temperature in the manufacturing process as output variables.

[0013] In one embodiment of the present invention, the manufacturing operation step includes a manufacturing operation step in which the feed flow rate and jacket temperature are the control variables. [Effects of the Invention]

[0014] As can be seen from the technical solutions described above, the reverse control method for food and pharmaceutical manufacturing processes according to the present invention utilizes a reverse design method based on known biochemical process dynamics models to determine manufacturing control processes corresponding to manufacturing output targets, and provides a rapid method for obtaining biochemical control processes. This method not only avoids the problems of requiring a large amount of personnel, materials, and time to determine manufacturing operations using experimental methods, but can also be applied to determining manufacturing operations in response to dynamically changing manufacturing needs, playing a clear role in improving the efficiency of determining biochemical control processes and the manufacturing efficiency of companies. [Brief explanation of the drawing]

[0015] [Figure 1] This is a flowchart of the reverse control method for food and pharmaceutical manufacturing processes according to the present invention. [Figure 2] This is an example diagram of a biochemical process reactor to which the present invention is applied. [Figure 3] This is a process control curve for feed flow rate and jacket temperature in an application example of the biochemical reactor of the present invention. [Figure 4] It is a comparison diagram of the manufacturing needs and actual manufacturing results of Material B in an application example of the biochemical reactor of the present invention.

Embodiment for Carrying Out the Invention

[0016] Hereinafter, the present invention will be further described with reference to the drawings and specific examples, so that those skilled in the art can better understand and implement the present invention. However, the examples given do not limit the present invention.

[0017] As shown in FIG. 1, the reverse control method for the food and pharmaceutical manufacturing process according to the present invention is Based on the product needs of food and pharmaceutical manufacturing, determining an expected output trajectory that is the manufacturing process target, and constructing a process dynamics model based on the biochemical reaction process, step S1; Based on the manufacturing process target, inverse calculating the process dynamics model to obtain a corresponding manufacturing process control curve, and the manufacturing process control curve is the manufacturing operation process, step S2; Including step S3 of performing control operations using the manufacturing operation process to achieve the manufacturing targets of food and pharmaceuticals based on predetermined food and pharmaceutical manufacturing targets.

[0018] The reverse control method for the food and pharmaceutical manufacturing process provided by the present invention constructs a process dynamics model based on the biochemical reaction process, inverse calculates the process dynamics model, and obtains the manufacturing operation process under a predetermined manufacturing target under the condition of ensuring the stability of the process dynamics change, solving the problem that the conventional experimental method requires a large amount of personnel, materials and time, and can more effectively and quickly obtain the control process of the manufacturing process, providing a solution for the rapid design of the control processes of different products, and solving the difficult problem of dynamic control process design.

[0019] In this embodiment, in step S1, the process dynamics model is set as the following process state equation JPEG0007852950000021.jpg33170JPEG0007852950000022.jpg27170To make it easier to show, the above process state equation is made into a more compact vector form, JPEG0007852950000023.jpg15170JPEG0007852950000024.jpg87170

[0020] JPEG0007852950000025.jpg154170JPEG0007852950000026.jpg109170JPEG0007852950000027.jpg120170To simplify, the above equations are expressed in the following vector form: JPEG0007852950000028.jpg19170JPEG0007852950000029.jpg87170

[0021] JPEG0007852950000030.jpg27170JPEG0007852950000031.jpg66170 In step S2, determining the manufacturing process control curve includes the following steps: Step S21: The expected output trajectory is known to be external dynamics, and internal dynamics are obtained. Step S22: Based on the internal dynamics and the inverse model between internal and external dynamics obtained above, obtain the manufacturing process control curve. In step S21, the specific steps for obtaining internal dynamics are as follows: Step S211: Construct the nonlinear internal dynamic equations, JPEG0007852950000032.jpg25170JPEG0007852950000033.jpg7170 Step S212: Convert the above nonlinear internal dynamic equation into an integral equation, JPEG0007852950000034.jpg 103170 Step S213: Solve the above approximate integral equation using the Picard iterative method. JPEG0007852950000035.jpg 37170 Step S214: Obtain the internal dynamics of the vector form using the discretization method, JPEG0007852950000036.jpg80170 Here, M is the reversible internal dynamics decomposition matrix, JPEG0007852950000037.jpg43170

[0022] JPEG0007852950000038.jpg65170

[0023] In this embodiment, the process dynamics model is an equation relating material balance, thermal balance, and energy balance between materials; the manufacturing process objective includes product manufacturing requirements with concentration and temperature as output variables in the manufacturing process; and the manufacturing operation steps include manufacturing operation steps with feed flow rate and reactor jacket temperature as control variables.

[0024] The following describes the application principle of the reverse control method for food and pharmaceutical manufacturing according to this embodiment, referring to actual application scenarios. Here, a specific example of producing cyclopentene using a continuous stirring reactor (CSTR) is provided, and cyclopentene is commonly used in the pharmaceutical field.

[0025] As shown in Figure 2, the CSTR is a reactor widely used in biochemical reactions and is a typical, highly nonlinear chemical reactor in process industries. The chemical industrial manufacturing process for producing cyclopentene using a CSTR has typical nonlinear, non-minimum phase characteristics, and the chemical reaction equation is as follows: JPEG0007852950000039.jpg34170 The above reaction produces the major product cyclopentene (abbreviated as material B) and the by-product dicyclopentadiene (abbreviated as material D) from cyclopentadiene (abbreviated as material A), and then material B continues to react to produce the by-product cyclopentanone (abbreviated as material C).

[0026] The specific steps of the reverse control method for the cyclopentene manufacturing process include the following steps: Step 1: Construct a biochemical reaction process dynamics model. For the above biochemical reaction process, a biochemical reaction process dynamics model was constructed, and the process dynamics model was defined as the molar balance equation and energy balance equation that satisfy material A and material B, as follows: JPEG0007852950000040.jpg78170 The reaction rate coefficient is related to the reaction temperature and process parameters. Refer to Table 1 for specific system parameters, and the specific formula for calculating the reaction rate coefficient is as follows: JPEG0007852950000041.jpg10170JPEG0007852950000042.jpg70170JPEG0007852950000043.jpg48170

[0027] Step 2: Determine the manufacturing process objectives. JPEG0007852950000044.jpg45170

[0028] Step 3: Use the inverse model algorithm to obtain the biochemical process control curve. The specific steps required include the following: Step 1: Rewrite the biochemical reactor model described above in the form of standard-state equations. JPEG0007852950000045.jpg100170JPEG0007852950000046.jpg82170JPEG0007852950000047.jpg28170 Step 4: Under a new coordinate system that satisfies the state variables of Step 3, i.e., JPEG0007852950000048.jpg151170JPEG0007852950000049.jpg70170 That is, the above integral equation can be approximated by the following equation, JPEG0007852950000050.jpg15170 Step 6: For the nonlinear integral equation in Step 5, the solution to the equation can be obtained by the Picard iteration method, i.e., JPEG0007852950000051.jpg148170JPEG0007852950000052.jpg70170JPEG0007852950000053.jpg144170

[0029] Step 4: Use the manufacturing operation process to perform control operations and achieve the manufacturing objectives. JPEG0007852950000054.jpg32170

[0030] To verify the effectiveness of the reverse control method for the manufacturing process implemented in this application, Figure 3 shows the process control curves for feed flow rate and reactor jacket temperature obtained based on the manufacturing target, and Figure 4 shows a comparison of the actual manufacturing results of material B and the manufacturing needs obtained based on the feed flow rate process control curve in Figure 3. As can be seen, the "stable reverse method" curve is basically combined with the "CB reference locus" curve, the "stable reverse method" curve shows the actual manufacturing results of material B achieved using the reverse control method of this embodiment, and the "CB reference locus" curve shows the manufacturing needs of material B. This shows that the actual manufacturing results of material B achieved using the reverse control method of this embodiment can satisfy the manufacturing needs of material B, further emphasizing the effectiveness of the reverse control method for the manufacturing process provided by this embodiment.

[0031] As described above, the reverse control method for food and pharmaceutical manufacturing processes provided by the present invention constructs a process dynamics model based on biochemical reaction processes, reverses the process dynamics model, and determines the manufacturing operation process under predetermined manufacturing targets while ensuring the stability of process dynamics changes. This solves the problem that conventional experimental methods require a large amount of personnel, materials, and time, and not only provides a solution for obtaining control steps of the manufacturing process more effectively and quickly, but also solves the difficult problem of designing dynamic control processes.

[0032] As those skilled in the art will understand, embodiments of this application may be provided as methods, systems, or computer program products. Accordingly, this application may be provided in the form of complete hardware embodiments, complete software embodiments, or embodiments combining software and hardware. Furthermore, this application may be provided in the form of a computer program product that runs on one or more computer-compatible storage media (including, but not limited to, magnetic disk memory, CD-ROM, optical memory, etc.) containing computer-compatible program code.

[0033] This application will be described with reference to flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products relating to embodiments of this application. As can be understood, computer program instructions can realize each flow and / or block of a flowchart and / or block diagram, and combinations of flows and / or blocks of a flowchart and / or block diagram. These computer program instructions can be provided to a processor of a general-purpose computer, a dedicated computer, an embedded processor, or other programmable data processing device to form a machine, and instructions executed by the processor of the computer or other programmable data processing device to form an apparatus for realizing one flow of a flowchart or one or more blocks of multiple flows and / or block diagrams.

[0034] These computer program instructions may also be stored in computer-readable memory that can guide a computer or other programmable data processing device to operate in a particular manner, thereby forming a product including an instruction unit, which implements a function specified in one or more flows of a flowchart and / or one or more blocks of a block diagram.

[0035] These computer program instructions may be implemented in a computer or other programmable data processing device, and a series of operational steps may be performed on the computer or other programmable device to form a computer-based process, thereby providing steps for realizing a function specified in one or more flows of a flowchart and / or one or more blocks of a block diagram.

[0036] As is clear, the above embodiments are merely illustrative examples and do not limit the embodiments. Those skilled in the art can make other different forms of changes and variations based on the above description. It is not necessary, nor is it possible, to list all embodiments here. Any changes and variations revealed thereby fall within the scope of protection of the present invention.

Claims

1. A reverse control method for food and pharmaceutical manufacturing processes, Step S1 involves determining the expected output trajectory, which is the manufacturing process target, based on the product needs of food and pharmaceutical manufacturing, and constructing a process dynamics model based on the biochemical reaction process. Based on the aforementioned manufacturing process objectives, the process dynamics model is reverse-engineered to obtain the corresponding manufacturing process control curve, and the manufacturing process control curve is defined as step S2, which is the manufacturing operation step. The process includes step S3, which involves performing control operations using the manufacturing process to achieve predetermined manufacturing targets for food and pharmaceuticals, based on the manufacturing targets for food and pharmaceuticals. In step S1, the process dynamics model is defined as the following process state equation: To make it easier to show, the above process state equation is expressed in vector form. [・] T In this case, T represents the transpose of a vector or matrix. Based on the above vector-form process state equation, we obtain a relational expression between the manufacturing process control curve and the state trajectory. The i-th process output y in the process dynamics model. i Find the derivative for , First, the output y i Find the first derivative for , Furthermore, i Find the k-th derivative for , Each output i against r i The derivatives are found in correspondence and are as follows: To simplify things, let's take the above equation in the following vector form: We obtain the inverse model of the process dynamics model, Internal structure Defined as, We obtained the inverse model between internal and external dynamics, which is as follows: A reverse control method for food and pharmaceutical manufacturing processes, characterized by the following features.

2. In step S2, the specific steps for determining the manufacturing process control curve are as follows: Step S21: The expected output trajectory is known to be external dynamics, and internal dynamics are obtained. Step S22: Based on the internal dynamics and the inverse model between internal and external dynamics obtained above, a manufacturing process control curve is obtained. In step S21, the specific steps for acquiring internal dynamics are as follows: Step S211: Construct the nonlinear internal dynamic equations, Step S212: Convert the above nonlinear internal dynamic equation into an integral equation, Step S213: Solve the above approximate integral equation using the Picard iteration method. Step S214: Obtain the internal dynamics of the vector form using the discretization method. The internal dynamics of the discretized vector form are as follows: Here, M is the reversible internal dynamics decomposition matrix, Based on the inverse model of internal and external dynamics, the following formula for calculating the manufacturing process control curve was obtained. The reverse control method for food and pharmaceutical manufacturing processes described in feature 1.

3. The characteristic values ​​are each λ 1 and -λ 2 And, M is an invertible internal dynamic decomposition matrix, and λ 1 , λ 2 > 0 The reverse control method for food and pharmaceutical manufacturing processes according to feature 2.

4. The reverse control method for food and pharmaceutical manufacturing processes according to claim 1, characterized in that the process dynamics model is an equation relating material balance, thermal balance, and energy balance between materials.

5. The reverse control method for food and pharmaceutical manufacturing processes according to claim 1, characterized in that the manufacturing process objectives include requirements for product manufacturing with concentration and temperature in the manufacturing process as output variables.

6. The reverse control method for food and pharmaceutical manufacturing processes according to claim 1, characterized in that the manufacturing operation process includes a manufacturing operation process in which the feed flow rate and the jacket temperature of the apparatus are used as control variables.

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