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 predetermined manufacturing process targets, and particularly to a method for reverse control of food and pharmaceutical manufacturing processes. [Background technology]

[0002] With the development of the global economy and progress in society, small-batch, high-profit, and diversified manufacturing methods, such as those typified by industrial biochemistry, are becoming increasingly important in order to meet people's ever-increasing living needs.Food and pharmaceutical manufacturing generally involves biochemical transformation or reaction processes, and the product goal is determined by controlling key variables such as temperature, flow rate, and concentration in 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, thereby achieving the final manufacturing requirements or product goal.

[0003] The design of manufacturing control processes is closely related to product quality, yield, and production time. In the food and pharmaceutical industries, control process design is the foundation of manufacturing. The diversification of product types places higher requirements on the rapid design of control processes, and it is also a key part of realizing smart manufacturing. Generally, control processes are mainly obtained through repeated experiments by engineers, but experimental methods require a large amount of manpower, materials, and time, and are particularly difficult to adapt to the manufacturing needs of modern smart manufacturing, which requires a wide variety of products, small batches, and multiple targets. In addition, traditional experimental design methods are difficult to obtain dynamic manufacturing operation processes. Summary of the Invention [Problem to be solved by the invention]

[0004] The present invention provides a method for inverse control of food and pharmaceutical manufacturing processes, which involves constructing a process kinetics model based on a biochemical reaction process, and then performing inverse calculations on the process kinetics model to determine the manufacturing operation process under a specified manufacturing target while ensuring the stability of process kinetic changes. This solves the problem that traditional experimental methods require a large amount of manpower, materials, and time, and enables the control process of the manufacturing process to be obtained more efficiently and quickly. This provides a solution for the rapid design of control processes for different products, and solves the difficult problem of dynamic control process design. [Means for solving the problem]

[0005] In order to solve the above technical problems, an embodiment of the present invention provides a method for reverse control of food and pharmaceutical manufacturing processes, the method comprising: Step S1: Determine the expected output trajectory, which is the manufacturing process target, based on the product requirements of food and pharmaceutical manufacturing, and build a process kinetic model based on the 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, the manufacturing process control curve being a manufacturing operation process; The method includes a step S3 of performing control operations using the manufacturing operation steps based on predetermined manufacturing targets for food and medicine to achieve the manufacturing targets for food and medicine.

[0006] In one embodiment of the present invention, in step S1, the process dynamics model is defined as the following process state equation: JPEG2025533370000002.jpg33170JPEG2025533370000003.jpg32170For ease of presentation, the above process state equations are in vector form: JPEG2025533370000004.jpg92170

[0007] JPEG2025533370000005.jpg86170JPEG2025533370000006.jpg64170JPEG2025533370000007.jpg121170For simplicity, the above equation is expressed in the following vector form: JPEG2025533370000008.jpg53170JPEG2025533370000009.jpg19170JPEG2025533370000010.jpg30170

[0008] JPEG2025533370000011.jpg55170 Internal dynamics JPEG2025533370000012.jpg65170

[0009] In one embodiment of the present invention, the specific steps of obtaining the manufacturing process control curve in step S2 are as follows: Step S21: The expected output trajectory is known as the external dynamics, and the internal dynamics is obtained. Step S22: Obtain a manufacturing process control curve based on the obtained internal dynamics and the inverse model between the internal and external dynamics; In step S21, the specific steps for acquiring internal dynamics are as follows: Step S211: construct a nonlinear internal dynamics equation; JPEG2025533370000013.jpg11170JPEG2025533370000014.jpg21170Step S212: Convert the above nonlinear internal dynamic equation into an integral equation; JPEG2025533370000015.jpg8170JPEG2025533370000016.jpg94170Step S213: Solve the above approximate integral equation using the Picard iteration method; JPEG2025533370000017.jpg36170Step S214: Obtain the internal dynamics in vector form using the discretization method; JPEG2025533370000018.jpg70170JPEG2025533370000019.jpg11170where M is the reversible internal dynamics decomposition matrix, JPEG2025533370000020.jpg44170

[0010] JPEG2025533370000021.jpg67170

[0011] In one embodiment of the present invention, the process kinetic model is a relationship equation of material balance, heat balance and energy balance between materials.

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

[0013] In one embodiment of the present invention, the manufacturing operation steps include manufacturing operation steps in which the feed flow rate and the jacket temperature are used as operation variables. [Effects of the Invention]

[0014] As can be seen from the above technical solutions, the inverse control method for food and pharmaceutical manufacturing processes according to the present invention uses an inverse design method based on a known biochemical process kinetic model to determine a manufacturing control process corresponding to a manufacturing output target, providing a method for quickly obtaining a biochemical control process. This method not only avoids the problems of using experimental methods to determine a manufacturing operation process, which requires a large amount of manpower, materials, and time, but is also applicable to determining a manufacturing operation process according to dynamically changing manufacturing needs, and plays a significant role in improving the work efficiency of determining biochemical control processes and the manufacturing efficiency of enterprises. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a flowchart of a method for reverse control of food and pharmaceutical manufacturing processes according to the present invention. [Figure 2] 1 is an illustration of one biochemical process reactor to which the present invention is applied. [Figure 3] 1 is a process control curve of the feed flow rate and jacket temperature of an application example of the biochemical reactor of the present invention. [Figure 4] FIG. 10 is a comparison diagram of the manufacturing needs and actual manufacturing results of material B in the application example of the biochemical reactor of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0016] The present invention will be further described below with reference to the drawings and specific examples, which will enable those skilled in the art to better understand and practice the present invention, but the examples given are not intended to limit the present invention.

[0017] As shown in FIG. 1, the reverse control method for food and pharmaceutical manufacturing processes according to the present invention includes: Step S1: Determine the expected output trajectory, which is the manufacturing process target, based on the product needs of food and pharmaceutical manufacturing, and build a process kinetic model based on the 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, the manufacturing process control curve being a manufacturing operation process; The method includes a step S3 of performing control operations using the manufacturing operation steps based on predetermined manufacturing targets for food and medicine to achieve the manufacturing targets for food and medicine.

[0018] The inverse control method for food and pharmaceutical manufacturing processes provided by the present invention constructs a process kinetics model based on a biochemical reaction process, and then performs inverse calculations using the process kinetics model to determine the manufacturing operation process under a specified manufacturing target under conditions that ensure the stability of process kinetic changes. This solves the problem that traditional experimental methods require a large amount of manpower, materials, and time, and enables the control process of the manufacturing process to be obtained more effectively and quickly, providing a solution for the rapid design of control processes for different products, and resolving the difficult problem of dynamic control process design.

[0019] In this embodiment, in step S1, the process dynamics model is defined as the following process state equation: JPEG2025533370000022.jpg33170JPEG2025533370000023.jpg27170For ease of presentation, the above process state equations are put into a more compact vector form: JPEG2025533370000024.jpg15170JPEG2025533370000025.jpg87170

[0020] JPEG2025533370000026.jpg154170JPEG2025533370000027.jpg109170JPEG2025533370000028.jpg120170For simplicity, the above equation is expressed in the following vector form: JPEG2025533370000029.jpg19170JPEG2025533370000030.jpg87170

[0021] JPEG2025533370000031.jpg27170JPEG2025533370000032.jpg66170In step S2, obtaining a manufacturing process control curve includes the following steps: Step S21: The expected output trajectory is known as the external dynamics, and the internal dynamics is obtained. Step S22: Obtain a manufacturing process control curve based on the obtained internal dynamics and the inverse model between the internal and external dynamics; In step S21, the specific steps for acquiring internal dynamics are as follows: Step S211: construct a nonlinear internal dynamics equation; JPEG2025533370000033.jpg25170JPEG2025533370000034.jpg7170Step S212: Convert the above nonlinear internal dynamic equation into an integral equation; JPEG2025533370000035.jpg103170Step S213: Solve the above approximate integral equation using the Picard iteration method; JPEG2025533370000036.jpg37170Step S214: Obtain the internal dynamics in vector form using the discretization method; JPEG2025533370000037.jpg80170, where M is the reversible internal dynamics decomposition matrix, JPEG2025533370000038.jpg43170

[0022] JPEG2025533370000039.jpg65170

[0023] In this embodiment, the process dynamics model is a relational equation of material balance, heat balance, and energy balance between materials, the manufacturing process target includes a product manufacturing requirement with concentration and temperature in the manufacturing process as output variables, and the manufacturing operation process includes a manufacturing operation process with feed flow rate and reactor jacket temperature as operation variables.

[0024] The application principle of the reverse control method for food and pharmaceutical production according to this embodiment will be described below with reference to actual application scenarios. A specific example of producing cyclopentene using a continuous stirred tank reactor (CSTR) is provided. Cyclopentene is commonly used in the pharmaceutical field.

[0025] As shown in Figure 2, a CSTR is a reactor widely used in biochemical reactions. It is a typical, highly nonlinear chemical reactor in the process industry. The chemical production process using a CSTR to produce cyclopentene has typical nonlinear, non-minimum phase characteristics. The chemical reaction equation is as follows: JPEG2025533370000040.jpg34170The above reaction produces the main product cyclopentene (abbreviated as material B) and the by-product dicyclopentadiene (abbreviated as material D) from cyclopentadiene (abbreviated as material A), which then continues to react with material B to produce the by-product cyclopentanone (abbreviated as material C).

[0026] The specific steps of the reverse control method for the cyclopentene production process include the following steps: Step 1: Build a biochemical reaction process kinetic model For the above biochemical reaction process, a biochemical reaction process kinetic model is constructed, and the process kinetic model is defined as a mole balance equation and an energy balance equation that satisfy material A and material B, as follows: JPEG2025533370000041.jpg78170The reaction rate coefficient is related to the reaction temperature and process parameters. The specific system parameters are shown in Table 1. The specific calculation formula for the reaction rate coefficient is as follows: JPEG2025533370000042.jpg10170JPEG2025533370000043.jpg70170JPEG2025533370000044.jpg48170

[0027] Step 2: Determine the manufacturing process goals JPEG2025533370000045.jpg45170

[0028] Step 3: Obtain the biochemical process control curve using the model inversion algorithm The specific steps required include the following: Step 1: Rewrite the biochemical reactor model described above into standard state equation form, JPEG2025533370000046.jpg100170JPEG2025533370000047.jpg82170JPEG2025533370000048.jpg28170Step 4: Under the new coordinate system that satisfies the state variables of step 3, i.e., JPEG2025533370000049.jpg151170JPEG2025533370000050.jpg70170That is, the above integral equation can be approximated as follows: Step 6: For the nonlinear integral equation in Step 5, the solution of the equation can be obtained by the Picard iteration method, namely: JPEG2025533370000052.jpg148170JPEG2025533370000053.jpg70170JPEG2025533370000054.jpg144170

[0029] Step 4: Use the manufacturing operation process to carry out control operations to achieve the manufacturing goal. JPEG2025533370000055.jpg32170

[0030] To verify the effectiveness of the inverse control method for manufacturing processes implemented in this application, Figure 3 shows the process control curves for the feed flow rate and reactor jacket temperature determined based on the production target, and Figure 4 shows a comparison of the actual production results of material B obtained based on the process control curve for the feed flow rate in Figure 3 and the production needs. As can be seen, the "stable inverse method" curve is basically a combination of the "CB reference trajectory" curve, and the "stable inverse method" curve shows the actual production results of material B achieved using the inverse control method of this example, while the "CB reference trajectory" curve shows the production needs of material B. This shows that the actual production results of material B achieved using the inverse control method of this example can meet the production needs of material B, further highlighting the effectiveness of the inverse control method for manufacturing processes provided by this example.

[0031] As described above, the inverse control method for food and pharmaceutical manufacturing processes provided by the present invention constructs a process kinetics model based on a biochemical reaction process, and then performs inverse calculations using the process kinetics model to determine the manufacturing operation process under a specified manufacturing target under conditions that ensure the stability of process kinetic changes. This solves the problem that traditional experimental methods require a large amount of manpower, materials, and time, and allows the control process of the manufacturing process to be obtained more effectively and quickly. This not only provides a solution to the rapid design of control processes for different products, but also solves the difficult problem of dynamic control process design.

[0032] As will be appreciated by those skilled in the art, the present application may be provided as a method, a system, or a computer program product. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment that combines software and hardware. The present application may also take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk memory, CD-ROM, optical memory, etc.) that contain computer-usable program code.

[0033] The present application will be described with reference to flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present application. It will be understood that each flow and / or block of the flowcharts and / or block diagrams, and combinations of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to form a machine, and the instructions executed by the processor of the computer or other programmable data processing device form an apparatus for implementing the functions specified in one or more flows of the flowcharts and / or one or more blocks of the block diagrams.

[0034] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, whereby the instructions stored in the computer-readable memory form an article of manufacture that includes an instruction apparatus that implements the functions specified in one or more flows of the flowcharts and / or one or more blocks of the block diagrams.

[0035] These computer program instructions may be loaded onto a computer or other programmable data processing apparatus and execute a series of operational steps on the computer or other programmable apparatus to form a computerized process, whereby the instructions executing on the computer or other programmable apparatus provide steps for implementing the functions specified in one or more flows of the flowcharts and / or one or more blocks of the block diagrams.

[0036] It is apparent that the above examples are merely illustrative and do not limit the embodiments. Those skilled in the art can make various modifications and variations based on the above description. It is not necessary and cannot be possible to list all the embodiments here. Any modifications or variations revealed thereby fall within the scope of protection of the present invention.

Claims

1. A method for reverse control of food and pharmaceutical manufacturing processes, comprising: Step S1: determining an expected output trajectory, which is a manufacturing process target, based on product needs for 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, the manufacturing process control curve being a manufacturing operation process; A method for reverse control of food and pharmaceutical manufacturing processes, comprising step S3 of using the manufacturing operation process to carry out control operations based on predetermined food and pharmaceutical manufacturing targets to achieve the food and pharmaceutical manufacturing targets.

2. In step S1, the process dynamics model is defined as the following process state equation: For ease of presentation, the above process equations of state are in vector form: [・] T T in the formula denotes the transpose of a vector or matrix, Obtain a relationship between the manufacturing process control curve and the state trajectory based on the process state equation in vector form; 2. The method for reverse control of food and pharmaceutical manufacturing processes according to claim 1.

3. the i-th process output y of the process dynamics model i Find the derivative with respect to First, the output y i Find the first derivative with respect to Further output y i Find the kth derivative with respect to Each output y i For r i The corresponding derivatives are found as follows: For simplicity, we put the above equation in vector form: Obtain an inverse model of the process dynamics model; 3. The method for inversely designing control curves for food and pharmaceutical manufacturing processes according to claim 2.

4. Internal dynamics 3. The method for reverse control of food and pharmaceutical manufacturing processes according to claim 2, wherein the method is defined as follows:

5. Obtain an inverse model between internal and external dynamics, as follows:

4. The method for reverse control of food and pharmaceutical manufacturing processes according to claim 3.

6. In step S2, the specific steps for obtaining the manufacturing process control curve are as follows: Step S21: The expected output trajectory is known as the external dynamics, and the internal dynamics are obtained. Step S22: Obtain a manufacturing process control curve based on the obtained internal dynamics and the inverse model between internal and external dynamics; In step S21, the specific steps for acquiring internal dynamics are as follows: Step S211: Construct a nonlinear internal dynamics equation; Step S212: Convert the nonlinear internal dynamic equation into an integral equation; Step S213: Solve the approximate integral equation using the Picard iteration method. Step S214: Obtain the internal dynamics in vector form using a discretization method; The internal dynamics of the vector form after discretization is as follows: where M is the reversible internal dynamics decomposition matrix, Based on the inverse model between internal and external dynamics, the following formula for calculating the manufacturing process control curve was obtained:

6. The method for reverse control of food and pharmaceutical manufacturing processes according to claim 5.

7. The feature values ​​are λ 1 and -λ 2 and M is the reversible internal dynamics decomposition matrix, and λ 1 , λ 2 >0 7. The method for reverse control of food and pharmaceutical manufacturing processes according to claim 6.

8. 3. The method for reverse control of food and pharmaceutical manufacturing processes according to claim 1 or 2, wherein the process dynamics model is a relational equation of material balance, heat balance and energy balance between materials.

9. 2. The method for reverse control of food and pharmaceutical manufacturing processes according to claim 1, wherein the manufacturing process goals include product manufacturing requirements with concentration and temperature in the manufacturing process as output variables.

10. 2. The method for reverse control of food and pharmaceutical manufacturing processes according to claim 1, wherein the manufacturing operation steps include manufacturing operation steps in which the feed flow rate and the jacket temperature of the equipment are used as manipulated variables.

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