Method and apparatus for preset time disruption observation capacity control of re-entrant manufacturing systems

Abstract

The application provides a preset time disturbance observation production capacity control method and device of a reentrant manufacturing system, and relates to the technical field of control science and engineering. In the product manufacturing process of driving the reentrant manufacturing system according to the specified product delivery time limit and the specified system delivery output, the system disturbance observer is used to accurately estimate the external disturbance of the system within the preset disturbance estimation time period before the specified product delivery time limit, and the state feedback control mechanism is used to simultaneously consider the system output control function and the external disturbance influence elimination function, so that the corresponding reentrant manufacturing system can respond to market demand within the specified product delivery time limit, complete the product delivery work of the specified system delivery output, effectively eliminate the negative influence of the external disturbance of the system on the system capacity, and improve the system reliability and control robustness of the reentrant manufacturing system.

Description

Technical Field

[0001] This application relates to the fields of control science and engineering technology, and more specifically, to a method and device for controlling the production capacity of a reentrant manufacturing system by pre-set time disturbance observation. Background Technology

[0002] With the significant improvement in the level of informatization in the manufacturing industry, the production scale and complexity of manufacturing plants are constantly expanding, and product manufacturing processes are becoming increasingly complex. Various new large-scale manufacturing systems, distinct from traditional assembly line manufacturing systems, have attracted widespread attention from industry and academia. Among these, reentrant manufacturing systems are particularly important. Compared to traditional assembly line manufacturing systems, reentrant manufacturing systems are production systems where products repeatedly access the same workstations at different processing stages. They are typically applied in highly automated and customized industries, such as semiconductor manufacturing, printed circuit board assembly, chemical processing, and automobile production.

[0003] In the application of reentrant manufacturing systems, there are often urgent or unplanned orders that require the manufacturing system to deliver a specified number of products within a strictly agreed-upon delivery deadline, while avoiding storage costs exceeding the product's intrinsic value. This necessitates the introduction of flexible capacity control mechanisms within the reentrant manufacturing system to ensure timely order delivery. It is worth noting that reentrant manufacturing systems are typically subject to various external disturbances in actual production environments (e.g., insufficient raw materials, changes in production environment conditions, workstation malfunctions, etc.), which can severely negatively impact the capacity control performance of the reentrant manufacturing system, making it highly susceptible to order delays. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a preset time disturbance observation capacity control method and computer equipment for a reentrant manufacturing system. This method enables the reentrant manufacturing system to accurately estimate external disturbances during the product manufacturing process according to specified product delivery deadlines and specified system delivery output. It utilizes a system disturbance observer to estimate external disturbances within a preset disturbance estimation period before the specified product delivery deadline. Furthermore, it employs a state feedback control mechanism to simultaneously address both system output control and external disturbance impact elimination. This ensures that the reentrant manufacturing system can respond to market demand within the specified product delivery deadline, complete the product delivery of the specified system delivery output, and simultaneously eliminate the negative impact of external disturbances on system capacity, thereby improving the system reliability and control robustness of the reentrant manufacturing system.

[0005] To achieve the above objectives, the technical solutions adopted in the embodiments of this application are as follows:

[0006] In a first aspect, this application provides a method for controlling the production capacity of a reentrant manufacturing system based on preset time disturbance observation, the method comprising:

[0007] The system output error dynamics model and system response error model of the target reentrant manufacturing system are obtained under external interference environment, which are matched with the preset product delivery cycle and preset system delivery output, as well as the system interference observer model matched with the preset interference estimation time, wherein the preset interference estimation time is less than the preset product delivery cycle.

[0008] The system output error dynamics model and the system response error model are used to calculate the current actual system output error and actual system response error of the target reentrant manufacturing system, respectively.

[0009] The system interference is estimated by calling the system interference observer model to obtain the current system interference estimate of the target reentrant manufacturing system;

[0010] Based on the state feedback control law correlation between the system output error dynamic model, the system disturbance observer model, and the system response error model, a model stability analysis is performed on the system output error dynamic model to obtain the current expected control gain matrix of the target reentrant manufacturing system.

[0011] Based on the actual system output error, the system disturbance estimate, the actual system response error, and the desired control gain matrix, a desired system control input signal conforming to the state feedback control law correlation is constructed for the target reentrant manufacturing system.

[0012] In an optional implementation, the system output error dynamics model is represented by the following hyperbolic partial differential equation:

[0013] ;

[0014] in, Used to indicate product completion level Used to represent time variables Used to indicate that the product has not yet begun processing. Used to indicate that the product has been processed. This is used to indicate the starting point of operation in the target reentrant manufacturing system. Used to indicate the preset product delivery cycle. This is used to indicate that the target reentrant manufacturing system is in Time and completion rate The actual number of products produced at that time Used to indicate product processing speed This matrix represents the dynamic coupling relationships between all reentrant production lines in the target reentrant manufacturing system. The control input coefficient matrix used to represent the target reentrant manufacturing system This is used to indicate that the target reentrant manufacturing system is in Time and completion rate External interference at that time This is used to indicate that the target reentrant manufacturing system is in At any given time and the actual number of products is System control input signals at that time This is used to indicate that the target reentrant manufacturing system has a completion level of [missing information]. The preset system delivery output at that time This is used to indicate that the target reentrant manufacturing system is in Time and completion rate System output error at that time.

[0015] In an optional implementation, the system response error model is represented by the following functional expression:

[0016] ;

[0017] in, Used to indicate product completion level Used to represent time variables This is used to indicate the starting point of operation in the target reentrant manufacturing system. Used to indicate the preset product delivery cycle. This is used to indicate that the target reentrant manufacturing system is in Time and completion rate System output error at that time The state scaling gain function with respect to the time variable is used to represent the system response error model. This is used to indicate that the target reentrant manufacturing system is in Time and completion rate The system response error at that time.

[0018] In an optional implementation, the system disturbance observer model is represented by the following partial differential equation:

[0019] ;

[0020] in, Used to indicate product completion level Used to represent time variables Used to indicate that the product has not yet begun processing. Used to indicate that the product has been processed. This is used to indicate the starting point of operation in the target reentrant manufacturing system. Used to represent the preset interference estimation duration, This is used to indicate that the target reentrant manufacturing system is in Time and completion rate The actual number of products produced at that time The system disturbance observer model is used to represent the system disturbance observer model in Time and completion rate At the time The estimated value, The system disturbance observer model is used to represent the system disturbance observer model in Time and completion rate Production forecast error at that time This is used to indicate that the target reentrant manufacturing system is in At any given time and the actual number of products is System control input signals at that time Used to indicate product processing speed This matrix represents the dynamic coupling relationships between all reentrant production lines in the target reentrant manufacturing system. The control input coefficient matrix used to represent the target reentrant manufacturing system The system disturbance observer model is used to represent the system disturbance observer model in Time and completion rate Estimated external disturbances to the system at that time The system disturbance observer model is used to represent the system disturbance observer model in Time and completion rate Production forecast error at that time The disturbance effect transformation gain function with respect to the time variable is used to represent the disturbance observer model of the system. Used to represent symbolic functions, Used to indicate the rate of maximum interference effect. It is a positive number.

[0021] In an optional implementation, the step of calling the system interference observer model to perform system interference estimation and obtaining the current system interference estimate of the target reentrant manufacturing system includes:

[0022] Construct the first Lyapunov function of the system disturbance observer model with respect to the production prediction error, and determine the disturbance influence rate constraint condition of the system production error dynamic model;

[0023] Based on the interference impact rate constraint and the function stability condition of the first Lyapunov function, the system interference observer model and the system output error dynamics model are jointly solved to obtain the current system interference estimate of the target reentrant manufacturing system.

[0024] In an optional implementation, the first Lyapunov function of the system disturbance observer model is represented by the following function:

[0025] ;

[0026] The stability condition of the first Lyapunov function is expressed by the following inequality:

[0027] ;

[0028] The disturbance influence rate constraint condition of the system output error dynamic model is expressed by the following inequality:

[0029] ;

[0030] in, The first Lyapunov function used to represent the system disturbance observer model. for The transpose of the matrix, This is used to indicate that the target reentrant manufacturing system is in Time and completion rate The rate of change of external disturbances at that time For positive integers, For the time variable of the first Lyapunov function The first derivative.

[0031] In an optional implementation, the step of performing model stability analysis on the system output error dynamics model based on the state feedback control law correlation between the system output error dynamics model, the system disturbance observer model, and the system response error model to obtain the current desired control gain matrix of the target reentrant manufacturing system includes:

[0032] Construct the second Lyapunov function of the system response error model with respect to the system response error;

[0033] Based on the correlation of the state feedback control law, the function stability conditions of the system output error dynamic model and the second Lyapunov function are jointly and equivalently characterized to obtain the model stability convergence conditions involving the system control gain matrix.

[0034] Based on the dynamic coupling relationship matrix and control input coefficient matrix of the target reentrant manufacturing system, the inequality of the model's stability convergence condition is solved to obtain the desired control gain matrix.

[0035] In an optional implementation, the second Lyapunov function of the system response error model is represented by the following function:

[0036] ;

[0037] The stability condition of the second Lyapunov function is expressed by the following inequality:

[0038] ;

[0039] The stability and convergence condition of the model is expressed by the following matrix inequality:

[0040] ;

[0041] in, , , Used to indicate product completion level Used to represent time variables This is used to indicate the starting point of operation in the target reentrant manufacturing system. Used to indicate the preset product delivery cycle. This is used to indicate that the target reentrant manufacturing system is in Time and completion rate System response error at that time for The transpose of the matrix, Used to indicate that the product has not yet begun processing. Used to indicate that the product has been processed. The second Lyapunov function is used to represent the system response error model. The symmetric positive definite matrix used for the second Lyapunov function This is used to represent the state scaling gain function of the target reentrant manufacturing system with respect to the time variable. For positive integers, The time variable of the second Lyapunov function The first derivative, for The inverse matrix, The control input coefficient matrix used to represent the target reentrant manufacturing system This matrix represents the dynamic coupling relationships between all reentrant production lines in the target reentrant manufacturing system. The system control gain matrix used to represent the target reentrant manufacturing system. for The transpose of the matrix, for The transpose of the matrix, for The transpose of .

[0042] In an optional implementation, the state feedback control law correlation is represented by the following functional expression:

[0043] ;

[0044] in, Used to indicate product completion level Used to represent time variables Used to indicate that the product has not yet begun processing. Used to indicate that the product has been processed. This is used to indicate the starting point of operation in the target reentrant manufacturing system. Used to indicate the preset product delivery cycle. This is used to indicate that the target reentrant manufacturing system is in Time and completion rate The actual number of products produced at that time This is used to indicate that the target reentrant manufacturing system is in At any given time and the actual number of products is System control input signals at that time This is used to indicate that the target reentrant manufacturing system has a completion level of [missing information]. The preset system delivery output at that time The dynamic model used to represent the system output error in Time and completion rate System output error at that time The state scaling gain function with respect to the time variable is used to represent the system response error model. The system response error model is used to represent the system response error model in Time and completion rate System response error at that time The system control gain matrix used to represent the target reentrant manufacturing system. The system disturbance observer model is used to represent the system disturbance observer model in Time and completion rate The estimated amount of external disturbances to the system at that time.

[0045] Secondly, this application provides a computer device including a processor and a memory, wherein the memory stores a computer program that can be executed by the processor, and the processor can execute the computer program to implement the preset time disturbance observation capacity control method for reentrant manufacturing systems as described in any of the foregoing embodiments.

[0046] In this case, the beneficial effects of the embodiments of this application may include the following:

[0047] This application, after obtaining the system output error dynamics model and system response error model of the target reentrant manufacturing system under external disturbance environment, matching the preset product delivery cycle (which can be used to characterize the specified product delivery time limit) and preset system delivery output (which can be used to characterize the specified system delivery output), and the system disturbance observer model matching the preset disturbance estimation time (which can be used to characterize the preset disturbance estimation time period before the specified product delivery time limit), calls the system output error dynamics model, system response error model, and system disturbance observer model to calculate the current actual system output error, actual system response error, and system disturbance estimate of the target reentrant manufacturing system, respectively. Then, based on the correlation of the state feedback control law considering the influence of external disturbance on the system, the system output error is... A dynamic model is used to perform model stability analysis to obtain the current expected control gain matrix of the target reentrant manufacturing system. Then, based on the actual system output error, system disturbance estimate, actual system response error, and expected control gain matrix, an expected system control input signal that conforms to the correlation of the state feedback control law is constructed. This expected system control input signal can effectively eliminate the negative impact of external disturbances on system capacity while driving the target reentrant manufacturing system to perform product manufacturing operations according to the specified product delivery time limit and the specified system delivery output. This ensures that the corresponding reentrant manufacturing system can respond normally to market demand within the specified product delivery time limit and complete the product delivery operation of the specified system delivery output, thereby improving the system reliability and control robustness of the reentrant manufacturing system.

[0048] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0049] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1A schematic diagram of the composition of a computer device provided in the embodiments of this application;

[0051] Figure 2 This is a flowchart illustrating the preset time disturbance observation capacity control method for reentrant manufacturing systems provided in this application embodiment.

[0052] Figure 3 for Figure 2 A flowchart illustrating the sub-steps included in step S230;

[0053] Figure 4 for Figure 2 The flowchart of the sub-steps included in step S240 is shown below.

[0054] Icons: 10-Computer equipment; 11-Memory; 12-Processor; 13-Communication unit. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0056] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0057] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0058] In the description of this application, it should be understood that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product is in use, or the orientation or positional relationship commonly understood by those skilled in the art. They are used only for the convenience of describing this application and simplifying the description, and are not intended to indicate or imply that the equipment or component referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0059] In the description of this application, it should also be noted that, unless otherwise expressly specified and limited, the terms "set up," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0060] Furthermore, it is understood in the description of this application that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. Those skilled in the art will understand the specific meaning of the above terms in this application based on the specific circumstances.

[0061] Through painstaking research, the applicant discovered that existing system capacity control solutions for reentrant manufacturing systems can use robust control technology to suppress the impact of external interference on the system. However, these solutions cannot completely eliminate the negative impact of external interference on the manufacturing system's capacity during the product production process, which can easily lead to orders not being delivered on time.

[0062] In this context, this application provides a preset time disturbance observation capacity control method and computer equipment for reentrant manufacturing systems. During the product manufacturing process of a reentrant manufacturing system according to a specified product delivery time limit and a specified system delivery output, the system disturbance observer accurately estimates external disturbances within a preset disturbance estimation period before the specified product delivery time limit. Furthermore, a state feedback control mechanism simultaneously considers both system output control and external disturbance impact elimination functions. This ensures that the corresponding reentrant manufacturing system can respond to market demand within the specified product delivery time limit, complete the product delivery operation of the specified system delivery output, and eliminate the negative impact of external disturbances on system capacity, thereby effectively improving the system reliability and control robustness of the corresponding reentrant manufacturing system.

[0063] The following detailed description of some embodiments of this application is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0064] Please refer to Figure 1 , Figure 1 This is a schematic diagram of the computer device 10 provided in this application embodiment. In this application embodiment, the computer device 10 can communicate with the central control platform corresponding to at least one reentrant manufacturing system. For any reentrant manufacturing system, during the product manufacturing process of driving the reentrant manufacturing system according to the product order delivery requirements (which require the corresponding reentrant manufacturing system to deliver a specified quantity of products (i.e., the specified system delivery output) within a specified product delivery deadline), the system interference observer completes the accurate estimation of external interference within a preset interference estimation period before the specified product delivery deadline. The state feedback control mechanism simultaneously takes into account the system output control function and the system external interference elimination function, so as to ensure that the corresponding reentrant manufacturing system can respond to market demand within the specified product delivery deadline, complete the product delivery operation of the specified system delivery output, and eliminate the negative impact of external interference on the system capacity, thereby improving the system reliability and control robustness of the reentrant manufacturing system. The computer device 10 may be a terminal device integrated with the central control platform corresponding to each reentrant manufacturing system (e.g., a control server responsible for implementing system scheduling and processing functions for multiple reentrant manufacturing systems), or it may be a terminal device independent of the central control platform corresponding to each reentrant manufacturing system (e.g., a laptop, a personal computer, a server, etc.).

[0065] In this embodiment, the computer device 10 may include a memory 11, a processor 12, and a communication unit 13. The memory 11, the processor 12, and the communication unit 13 are electrically connected to each other directly or indirectly to achieve data transmission or interaction. For example, these components can be electrically connected to each other via one or more communication buses or signal lines.

[0066] In this embodiment, the memory 11 may be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The memory 11 is used to store computer programs, and the processor 12 can execute the computer programs accordingly after receiving execution instructions.

[0067] In this embodiment, the processor 12 can be an integrated circuit chip with signal processing capabilities. The processor 12 can be a general-purpose processor, including at least one of a Central Processing Unit (CPU), Graphics Processing Unit (GPU), Network Processor (NP), Digital Signal Processor (DSP), Application-Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor can be a microprocessor or any conventional processor, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application.

[0068] In this embodiment, the communication unit 13 is used to establish a communication connection between the computer device 10 and other electronic devices through a network, and to send and receive data through the network, wherein the network includes a wired communication network and a wireless communication network.

[0069] In this embodiment, the computer device 10 may store a specific computer program related to the preset time interference observation capacity control function in the memory 11. By driving the processor 12 to execute the specific computer program stored in the memory 11, during the product manufacturing process of any reentrant manufacturing system according to the specified product delivery time limit and the specified system delivery output, the system interference observer completes the accurate estimation of external interference within the preset interference estimation time period before the specified product delivery time limit. The state feedback control mechanism simultaneously takes into account the system output control function and the system external interference impact elimination function, so as to ensure that the corresponding reentrant manufacturing system can respond to market demand within the specified product delivery time limit, complete the product delivery operation of the specified system delivery output, and eliminate the negative impact of external interference on the system capacity, thereby improving the system reliability and control robustness of the reentrant manufacturing system.

[0070] Understandable, Figure 1 The block diagram shown is only a schematic diagram of one configuration of the computer device 10. The computer device 10 may also include components such as... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown. Figure 1 The components shown can be implemented using hardware, software, or a combination thereof.

[0071] In this application, to ensure that the computer device 10 can effectively eliminate the negative impact of external interference on system capacity during the product manufacturing process of any reentrant manufacturing system according to a specified product delivery time limit and a specified system delivery output, and to enable the reentrant manufacturing system to respond normally to market demand within the specified product delivery time limit and complete the product delivery operation of the specified system delivery output, this application embodiment achieves the aforementioned objective by providing a preset time interference observation capacity control method for reentrant manufacturing systems. The preset time interference observation capacity control method provided by this application for reentrant manufacturing systems will be described in detail below.

[0072] Please refer to Figure 2 , Figure 2 This is a flowchart illustrating the preset time disturbance observation capacity control method provided by this application for a reentrant manufacturing system according to an embodiment of the present application. In this embodiment, Figure 2 The preset time interference observation capacity control method shown may include steps S210 to S250.

[0073] Step S210: Obtain the system output error dynamics model and system response error model of the target reentrant manufacturing system under external interference environment, which are matched with the preset product delivery cycle and preset system delivery output, as well as the system interference observer model matched with the preset interference estimation duration.

[0074] In this embodiment, the target reentrant manufacturing system is the reentrant manufacturing system that the computer device 10 currently needs to follow and control; the preset product delivery cycle is used to constrain the expected product delivery time limit (i.e., the specified product delivery time limit) of the target reentrant manufacturing system; the preset system delivery output is used to constrain the expected product production quantity of the target reentrant manufacturing system under different product completion levels. The preset system delivery output substantially matches the ever-changing market demand and can characterize the market demand-oriented production target capacity; the system output error dynamic model is used to describe the system dynamic model of the target reentrant manufacturing system regarding the system output error (i.e., the quantitative difference between the actual product production quantity of the target reentrant manufacturing system and the preset system delivery output) under external interference environment. At this time, the preset product delivery cycle and the preset system delivery output are used to constrain the capacity distribution of the system output error dynamic model. The system output error of the target reentrant manufacturing system needs to become zero at the specified product delivery time limit corresponding to the preset product delivery cycle and remain zero at any time point after the specified product delivery time limit (at this time, the target reentrant manufacturing system will continuously and stably perform product manufacturing operations according to the specified system delivery output).

[0075] In this embodiment, the system output error dynamic model can be represented by a hyperbolic partial differential equation that follows the law of conservation of mass to describe the spatiotemporal evolution of the target reentrant manufacturing system with respect to system output error under the combined constraints of external disturbances, specified product delivery time limits, and specified system delivery output.

[0076] In this process, the multiple reentrant production lines involved in the target reentrant manufacturing system are often coupled, making their dynamic models interdependent. Furthermore, the target reentrant manufacturing system is subject to various external disturbances in the actual production environment. Therefore, a control channel needs to be introduced in the dynamic modeling of the target reentrant manufacturing system to control its production capacity, ensuring that its production performance better meets market demands. Thus, hyperbolic partial differential equations following the law of mass conservation can be used to effectively describe the spatiotemporal evolution of the target reentrant manufacturing system's production quantity under external disturbances, resulting in a theoretical system output dynamics model. This theoretical system output dynamics model can be represented by the following hyperbolic partial differential equations:

[0077] ;

[0078] in, Used to indicate product completion level Used to represent time variables Used to indicate that the product has not yet begun processing. Used to indicate that the product has been processed. This is used to indicate the starting point of operation in the target reentrant manufacturing system. This is used to indicate that the target reentrant manufacturing system is in Time and completion rate The actual number of products produced at that time Used to indicate product processing speed This matrix represents the dynamic coupling relationships between all reentrant production lines in the target reentrant manufacturing system. The control input coefficient matrix used to represent the target reentrant manufacturing system This is used to indicate that the target reentrant manufacturing system is in Time and completion rate External interference at that time This is used to indicate that the target reentrant manufacturing system is in At any given time and the actual number of products is The system control input signal at that time. , The first [unit] used to indicate that the target is reentrant into the manufacturing system A reentrant production line in Time and completion rate The actual number of products at that time The number of reentrant production lines in the target reentrant manufacturing system is used to represent the total number of reentrant production lines; the boundary conditions of the theoretical system output dynamics model are: The initial conditions of the theoretical system's output kinetics model are: ,in The target reentrant manufacturing system has a product completion rate of The initial quantity of products at that time.

[0079] Based on this, the system output error of the target reentrant manufacturing system can be defined as " ",in This is used to indicate that the target reentrant manufacturing system has a completion level of [missing information]. Expected system output at that time This is used to indicate that the target reentrant manufacturing system is in Time and completion rate The system output error at that time. Specifically, because the system output error of the target reentrant manufacturing system needs to be considered within the preset product delivery cycle (i.e., The specified product delivery time limit corresponding to ) It becomes zero at time ) and at any point after the specified product delivery deadline (i.e. If the value remains zero, then based on the above theoretical system output dynamics model, it can be known that: when the target reentrant manufacturing system... There are no meaningful system control input signals during this period. As a steady-state spatial distribution function, it will satisfy the following under the mapping effect of the above theoretical system output kinetic model: First-order matrix differential equations:

[0080] .

[0081] Therefore, for In other words, it can be achieved by... Designed for " ",in This is used to indicate the specified number of products that the target reentrant manufacturing system ultimately needs to deliver, so that the target reentrant manufacturing system can... The system continuously and stably produces products according to a specified quantity within a given time period. At this point, the numerical boundary condition regarding the system output error of the target reentrant manufacturing system is "". " and" ".

[0082] At this point, the system output error dynamic model can be obtained by substituting the above-mentioned definition of system output error and the two numerical boundary conditions for system output error into the theoretical system output dynamic model. The system output error dynamic model is then represented by the following hyperbolic partial differential equation:

[0083] ;

[0084] in, Used to indicate product completion level Used to represent time variables Used to indicate that the product has not yet begun processing. Used to indicate that the product has been processed. This is used to indicate the starting point of operation in the target reentrant manufacturing system. Used to indicate the preset product delivery cycle. This is used to indicate that the target reentrant manufacturing system is in Time and completion rate The actual number of products produced at that time Used to indicate product processing speed This matrix represents the dynamic coupling relationships between all reentrant production lines in the target reentrant manufacturing system. The control input coefficient matrix used to represent the target reentrant manufacturing system This is used to indicate that the target reentrant manufacturing system is in Time and completion rate External interference at that time This is used to indicate that the target reentrant manufacturing system is in At any given time and the actual number of products is System control input signals at that time This is used to indicate that the target reentrant manufacturing system has a completion level of [missing information]. The preset system delivery output at that time This is used to indicate that the target reentrant manufacturing system is in Time and completion rate System output error at that time.

[0085] In this embodiment, the system response error model is used to describe the system response performance error of the target reentrant manufacturing system to external market demands at the entire manufacturing system level. Specifically, the system response error model can be scaled by introducing a time-varying gain function to describe the system response performance error, ensuring that the corresponding system response error also tends towards zero as the time variable approaches the specified product delivery deadline, thus enabling the target reentrant manufacturing system to achieve normal response to external market demands within the specified product delivery deadline. In this case, the system response error model can be represented by the following functional expression:

[0086] ;

[0087] in, Used to indicate product completion level Used to represent time variables This is used to indicate the starting point of operation in the target reentrant manufacturing system. Used to indicate the preset product delivery cycle. This is used to indicate that the target reentrant manufacturing system is in Time and completion rate System output error at that time The state scaling gain function with respect to the time variable is used to represent the system response error model. This is used to indicate that the target reentrant manufacturing system is in Time and completion rate The system response error at that time.

[0088] In this embodiment of the application, the preset interference estimation duration (i.e. The time interval is less than the preset product delivery cycle, so that the preset interference estimation time period (i.e., the preset interference estimation duration) corresponds to the preset interference estimation duration. Interference estimation time limit (i.e.) The specified product delivery deadline is approaching. The preset interference estimation time is used to constrain the system interference observer model's estimation cutoff time for external system interference. The system interference observer model can complete the accurate estimation of external system interference within the preset interference estimation time period. The system interference estimation error of the system interference observer model (i.e., the numerical difference between the actual system interference size and the system interference estimate) will gradually approach zero as the time variable approaches the aforementioned interference estimation time limit, and will become completely zero at the aforementioned interference estimation time limit (i.e., the system interference observer model accurately estimates the actual size of the specific external system interference actually received by the target reentrant manufacturing system within the aforementioned interference estimation time limit).

[0089] In this embodiment, for the system disturbance observer model, the observation operation of the production prediction error (i.e., the numerical difference between the actual production quantity and the estimated production quantity) of the target reentrant manufacturing system during the product manufacturing process can be used to indirectly describe whether the corresponding system disturbance estimation error converges to zero (wherein, the closer the production prediction error is to zero, the closer the estimated production quantity is to the actual production quantity, and the closer the system disturbance estimate is to the actual system disturbance magnitude, i.e., the system disturbance estimation error tends to zero). At this time, the system disturbance observer model can be represented by the following partial differential equation:

[0090] ;

[0091] in, Used to indicate product completion level Used to represent time variables Used to indicate that the product has not yet begun processing. Used to indicate that the product has been processed. This is used to indicate the starting point of operation in the target reentrant manufacturing system. Used to represent the preset interference estimation duration, This is used to indicate that the target reentrant manufacturing system is in Time and completion rate The actual number of products produced at that time The system disturbance observer model is used to represent the system disturbance observer model in Time and completion rate At the time The estimated value, The system disturbance observer model is used to represent the system disturbance observer model in Time and completion rate Production forecast error at that time Used to indicate that the target reentrant manufacturing system is in At any given time and the actual number of products is System control input signals at that time Used to indicate product processing speed This matrix represents the dynamic coupling relationships between all reentrant production lines in the target reentrant manufacturing system. The control input coefficient matrix used to represent the target reentrant manufacturing system The system disturbance observer model is used to represent the system disturbance observer model in Time and completion rate Estimated external disturbances to the system at that time The system disturbance observer model is used to represent the system disturbance observer model in Time and completion rate Production forecast error at that time The disturbance effect transformation gain function with respect to the time variable is used to represent the disturbance observer model of the system. Used to represent symbolic functions, Used to represent the maximum rate of impact of disturbance (i.e., the maximum rate at which external disturbances to the system have a negative impact on the target reentrant manufacturing system). It is a positive number.

[0092] Step S220: Call the system output error dynamics model and the system response error model to calculate the current actual system output error and actual system response error of the target reentrant manufacturing system, respectively.

[0093] In this embodiment, the expected system control input signal of the target reentrant manufacturing system at the previous moment can be used as the actual system control input signal of the target reentrant manufacturing system at the current moment. These signals are then input into the system output error dynamics model and the system response error model to solve for the unknown parameters, thereby obtaining the actual system output error and the actual system response error of the target reentrant manufacturing system at the current moment.

[0094] Step S230: Call the system interference observer model to estimate the system interference and obtain the current system interference estimate of the target reentrant manufacturing system.

[0095] In this embodiment, since the system interference observer model uses the production prediction error observation operation to achieve a high-precision system interference estimation function, when solving the system interference estimate of the target reentrant manufacturing system at the current moment based on the system interference observer model, it is necessary to comprehensively consider the convergence status of the production prediction error, the actual product production quantity involved in the system production error dynamics model, and the limited model parameters of the system interference observer model and the system production error dynamics model, in order to ensure that the corresponding system interference estimate has sufficiently strong data reliability.

[0096] Alternatively, please refer to Figure 3 , Figure 3 yes Figure 2 The flowchart of step S230 includes the sub-steps. In this embodiment of the application, step S230 may include sub-steps S231 to S232 to ensure that the corresponding estimated system interference has sufficient data reliability and can complete the accurate estimation of the external interference of the entire system within a preset interference estimation period before the specified product delivery deadline.

[0097] Sub-step S231: Construct the first Lyapunov function of the system disturbance observer model with respect to the production prediction error, and determine the disturbance influence rate constraint condition of the system production error dynamic model.

[0098] In this embodiment, the first Lyapunov function of the system disturbance observer model is represented by the following function:

[0099] ;

[0100] The stability condition of the first Lyapunov function is expressed by the following inequality:

[0101] ;

[0102] The disturbance influence rate constraint condition of the system output error dynamic model is expressed by the following inequality:

[0103] ;

[0104] in, The first Lyapunov function used to represent the system disturbance observer model. for The transpose of the matrix, Used to indicate that the target reentrant manufacturing system is in Time and completion rate The rate of change of external disturbances at that time For positive integers, For the time variable of the first Lyapunov function The first derivative.

[0105] Sub-step S232: Based on the interference influence rate constraint and the function stability condition of the first Lyapunov function, the system interference observer model and the system output error dynamics model are jointly solved to obtain the current system interference estimate of the target reentrant manufacturing system.

[0106] In this embodiment, the actual system control input signal of the target reentrant manufacturing system at the current moment can be substituted into the system disturbance observer model and the system output error dynamic model. The unknown parameters of the model can be solved by using the function stability condition of the first Lyapunov function and the disturbance influence rate constraint condition as model constraints, so as to obtain the system disturbance estimate of the target reentrant manufacturing system at the current moment.

[0107] Therefore, by executing the above sub-steps S231 to S232, this application can ensure that the estimated system interference has sufficient data reliability and can complete the accurate estimation of the external interference of the entire system within the preset interference estimation period before the specified product delivery deadline.

[0108] Step S240: Based on the correlation between the state feedback control law of the system output error dynamic model, the system disturbance observer model and the system response error model, perform model stability analysis on the system output error dynamic model to obtain the current expected control gain matrix of the target reentrant manufacturing system.

[0109] In this embodiment, the state feedback control law correlation is used to describe the parametric interaction between the system control input signal of the target reentrant manufacturing system and the system output error involved in the system output error dynamics model, the system disturbance estimate involved in the system disturbance observer model, and the system response error involved in the system response error model. This allows the state feedback control mechanism to simultaneously consider both system output control and external disturbance elimination functions. Therefore, the state feedback control law correlation can be designed to include a system disturbance compensation term (which directly matches the system disturbance estimate) corresponding to the external disturbance elimination function, and a theoretical output control term (which directly matches the system output error and system response error) corresponding to the system output control function. The state feedback control law correlation can then be represented by the following functional expression:

[0110] ;

[0111] in, Used to indicate product completion level Used to represent time variables Used to indicate that the product has not yet begun processing. Used to indicate that the product has been processed. This is used to indicate the starting point of operation in the target reentrant manufacturing system. Used to indicate the preset product delivery cycle. Used to indicate that the target reentrant manufacturing system is in Time and completion rate The actual number of products produced at that time Used to indicate that the target reentrant manufacturing system is in At any given time and the actual number of products is System control input signals at that time This is used to indicate that the target reentrant manufacturing system has a completion level of [missing information]. The preset system delivery output at that time The dynamic model used to represent the system output error in Time and completion rate System output error at that time The state scaling gain function with respect to the time variable is used to represent the system response error model. The system response error model is used to represent the system response error model in Time and completion rate System response error at that time The system control gain matrix used to represent the target reentrant manufacturing system. The system disturbance observer model is used to represent the system disturbance observer model in Time and completion rate The estimated external disturbances to the system at that time. Among them, " "This refers to the system interference compensation item," "This refers to the theoretical output control item."

[0112] Based on this, according to the above-mentioned state feedback control law correlation, and combined with the product manufacturing requirements where the system response error model converges to zero within a specified product delivery time limit, the model stability analysis of the system output error dynamics model can be performed to obtain the expected control gain matrix of the target reentrant manufacturing system at the current moment.

[0113] Alternatively, please refer to Figure 4 , Figure 4 yes Figure 2The flowchart of step S240 includes the sub-steps. In the embodiments of this application, step S240 may include sub-steps S241 to S243 to solve for the desired control gain matrix required for the target reentrant manufacturing system to achieve system output control function under the state feedback control mechanism.

[0114] Sub-step S241: Construct the second Lyapunov function of the system response error model with respect to the system response error.

[0115] In this embodiment, the second Lyapunov function of the system response error model can be represented by the following functional expression:

[0116] ;

[0117] Furthermore, the stability condition of the second Lyapunov function is expressed by the following inequality:

[0118] ;

[0119] in, Used to indicate product completion level Used to represent time variables This is used to indicate the starting point of operation in the target reentrant manufacturing system. Used to indicate the preset product delivery cycle. Used to indicate that the target reentrant manufacturing system is in Time and completion rate System response error at that time for The transpose of the matrix, Used to indicate that the product has not yet begun processing. Used to indicate that the product has been processed. The second Lyapunov function is used to represent the system response error model. The symmetric positive definite matrix used for the second Lyapunov function This is used to represent the state scaling gain function of the target reentrant manufacturing system with respect to the time variable. For positive integers, The time variable of the second Lyapunov function The first derivative.

[0120] Sub-step S242: Based on the correlation of the state feedback control law, the function stability conditions of the system output error dynamic model and the second Lyapunov function are jointly and equivalently characterized to obtain the model stability convergence conditions involving the system control gain matrix.

[0121] In this embodiment, the stability analysis of the system output error dynamics model can be performed by combining the correlation of the state feedback control law and the function stability condition of the second Lyapunov function, thereby obtaining the model stability convergence condition related to the system output control function. This model stability convergence condition can be expressed by the following matrix inequality:

[0122] ;

[0123] in, , , The symmetric positive definite matrix used for the second Lyapunov function For positive integers, for The inverse matrix, The control input coefficient matrix used to represent the target reentrant manufacturing system This matrix represents the dynamic coupling relationships between all reentrant production lines in the target reentrant manufacturing system. The system control gain matrix used to represent the target reentrant manufacturing system. for The transpose of the matrix, for The transpose of the matrix, for The transpose of .

[0124] Sub-step S243: Based on the dynamic coupling relationship matrix and control input coefficient matrix of the target reentrant manufacturing system, solve the inequality for the model's stability convergence condition to obtain the desired control gain matrix.

[0125] In this embodiment, both sides of the first inequality in the above model's stability and convergence condition can be multiplied by a matrix. The stability and convergence conditions of the above model are transformed into control gain constraints that enable the system output error dynamic model to meet the product order delivery requirements. These control gain constraints can then be expressed using the following matrix inequalities:

[0126] ;

[0127] in, , , The symmetric positive definite matrix used for the second Lyapunov function For positive integers, for The inverse matrix, The control input coefficient matrix used to represent the target reentrant manufacturing system This matrix represents the dynamic coupling relationships between all reentrant production lines in the target reentrant manufacturing system. The system control gain matrix used to represent the target reentrant manufacturing system. for The transpose of the matrix, for The transpose of the matrix, for The transpose of .

[0128] Therefore, based on the dynamic coupling relationship matrix and control input coefficient matrix of the target reentrant manufacturing system, as well as the symmetric positive definite matrix of the second Lyapunov function, the inequalities of the above control gain constraints can be solved to obtain the desired control gain matrix required to realize the system output control function under the state feedback control mechanism.

[0129] Therefore, this application can solve for the desired control gain matrix required for the target reentrant manufacturing system to achieve system output control function under the state feedback control mechanism by executing the above sub-steps S241 to S243.

[0130] Step S250: Based on the actual system output error, system disturbance estimate, actual system response error, and desired control gain matrix, construct a desired system control input signal that conforms to the state feedback control law correlation for the target reentrant manufacturing system.

[0131] In this embodiment, the actual system output error, system disturbance estimate, actual system response error, and desired control gain matrix of the target reentrant manufacturing system at the current moment can be substituted into the " In this way, the corresponding desired system control input signal can effectively eliminate the negative impact of external interference on the system capacity while driving the target reentrant manufacturing system to perform product manufacturing operations according to the specified product delivery time limit and the specified system delivery output. This ensures that the target reentrant manufacturing system can respond normally to market demand within the specified product delivery time limit and complete the product delivery operation of the specified system delivery output, thereby improving the system reliability and control robustness of the target reentrant manufacturing system.

[0132] Therefore, by executing the above steps S210 to S250, this application can accurately estimate external disturbances to the system during the product manufacturing process of any reentrant manufacturing system according to the specified product delivery time limit and the specified system delivery output by using a system disturbance observer within a preset disturbance estimation time period before the specified product delivery time limit. By utilizing a state feedback control mechanism, it can simultaneously take into account the system output control function and the system external disturbance impact elimination function, so as to ensure that the corresponding reentrant manufacturing system can respond to market demand within the specified product delivery time limit, complete the product delivery operation of the specified system delivery output, and eliminate the negative impact of external disturbances on the system capacity, thereby improving the system reliability and control robustness of the reentrant manufacturing system.

[0133] The above descriptions are merely various embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for controlling production capacity by pre-set time disturbance observation in a reentrant manufacturing system, characterized in that, The method includes: The system output error dynamics model and system response error model of the target reentrant manufacturing system are obtained under external interference environment, which are matched with the preset product delivery cycle and preset system delivery output, as well as the system interference observer model matched with the preset interference estimation time, wherein the preset interference estimation time is less than the preset product delivery cycle. The system output error dynamics model and the system response error model are used to calculate the current actual system output error and actual system response error of the target reentrant manufacturing system, respectively. The system interference is estimated by calling the system interference observer model to obtain the current system interference estimate of the target reentrant manufacturing system; Based on the state feedback control law correlation between the system output error dynamic model, the system disturbance observer model, and the system response error model, a model stability analysis is performed on the system output error dynamic model to obtain the current expected control gain matrix of the target reentrant manufacturing system. Based on the actual system output error, the system disturbance estimate, the actual system response error, and the desired control gain matrix, a desired system control input signal conforming to the state feedback control law correlation is constructed for the target reentrant manufacturing system.

2. The method according to claim 1, characterized in that, The system output error dynamic model is represented by the following hyperbolic partial differential equation: ； in, Used to indicate product completion level. Used to represent time variables Used to indicate that the product has not yet begun processing. Used to indicate that the product has been processed. This is used to indicate the starting point of operation in the target reentrant manufacturing system. Used to indicate the preset product delivery cycle. Used to indicate that the target reentrant manufacturing system is in Time and completion rate The actual number of products produced at that time Used to indicate product processing speed This matrix represents the dynamic coupling relationships between all reentrant production lines in the target reentrant manufacturing system. The control input coefficient matrix used to represent the target reentrant manufacturing system Used to indicate that the target reentrant manufacturing system is in Time and completion rate External interference at that time Used to indicate that the target reentrant manufacturing system is in At any given time and the actual number of products is System control input signals at that time This is used to indicate that the target reentrant manufacturing system has a completion level of [missing information]. The preset system delivery output at that time Used to indicate that the target reentrant manufacturing system is in Time and completion rate System output error at that time.

3. The method according to claim 1, characterized in that, The system response error model is represented by the following function: ； in, Used to indicate product completion level Used to represent time variables This is used to indicate the starting point of operation in the target reentrant manufacturing system. Used to indicate the preset product delivery cycle. This is used to indicate that the target reentrant manufacturing system is in Time and completion rate System output error at that time The state scaling gain function with respect to the time variable is used to represent the system response error model. This is used to indicate that the target reentrant manufacturing system is in Time and completion rate The system response error at that time.

4. The method according to claim 1, characterized in that, The system disturbance observer model is represented by the following partial differential equation: ； in, Used to indicate product completion level Used to represent time variables Used to indicate that the product has not yet begun processing. Used to indicate that the product has been processed. This is used to indicate the starting point of operation in the target reentrant manufacturing system. Used to represent the preset interference estimation duration, Used to indicate that the target reentrant manufacturing system is in Time and completion rate The actual number of products produced at that time The system disturbance observer model is used to represent the system disturbance observer model in Time and completion rate At the time The estimated value, The system disturbance observer model is used to represent the system disturbance observer model in Time and completion rate Production forecast error at that time Used to indicate that the target reentrant manufacturing system is in At any given time and the actual number of products is System control input signals at that time Used to indicate product processing speed This matrix represents the dynamic coupling relationships between all reentrant production lines in the target reentrant manufacturing system. The control input coefficient matrix used to represent the target reentrant manufacturing system The system disturbance observer model is used to represent the system disturbance observer model in Time and completion rate Estimated external disturbances to the system at that time The system disturbance observer model is used to represent the system disturbance observer model in Time and completion rate Production forecast error at that time The disturbance effect transformation gain function with respect to the time variable is used to represent the disturbance observer model of the system. Used to represent symbolic functions, Used to indicate the rate of maximum interference effect. It is a positive number.

5. The method according to claim 4, characterized in that, The step of calling the system interference observer model to perform system interference estimation and obtaining the current system interference estimate of the target reentrant manufacturing system includes: Construct the first Lyapunov function of the system disturbance observer model with respect to the production prediction error, and determine the disturbance influence rate constraint condition of the system production error dynamic model; Based on the interference impact rate constraint and the function stability condition of the first Lyapunov function, the system interference observer model and the system output error dynamics model are jointly solved to obtain the current system interference estimate of the target reentrant manufacturing system.

6. The method according to claim 5, characterized in that, The first Lyapunov function of the system interference observer model is represented by the following function: ； The stability condition of the first Lyapunov function is expressed by the following inequality: ； The disturbance influence rate constraint condition of the system output error dynamic model is expressed by the following inequality: ； in, The first Lyapunov function used to represent the system disturbance observer model. for The transpose of the matrix, Used to indicate that the target reentrant manufacturing system is in Time and completion rate The rate of change of external disturbances at that time For positive integers, For the time variable of the first Lyapunov function The first derivative.

7. The method according to any one of claims 1-6, characterized in that, The step of performing model stability analysis on the system output error dynamics model based on the state feedback control law correlation between the system output error dynamics model, the system disturbance observer model, and the system response error model, and obtaining the current desired control gain matrix of the target reentrant manufacturing system, includes: Construct the second Lyapunov function of the system response error model with respect to the system response error; Based on the correlation of the state feedback control law, the function stability conditions of the system output error dynamic model and the second Lyapunov function are jointly and equivalently characterized to obtain the model stability convergence conditions involving the system control gain matrix. Based on the dynamic coupling relationship matrix and control input coefficient matrix of the target reentrant manufacturing system, the inequality of the model's stability convergence condition is solved to obtain the desired control gain matrix.

8. The method according to claim 7, characterized in that, The second Lyapunov function of the system response error model is represented by the following function: ； The stability condition of the second Lyapunov function is expressed by the following inequality: ； The stability and convergence condition of the model is expressed by the following matrix inequality: ； in, , , Used to indicate product completion level Used to represent time variables This is used to indicate the starting point of operation in the target reentrant manufacturing system. Used to indicate the preset product delivery cycle. Used to indicate that the target reentrant manufacturing system is in Time and completion rate System response error at that time for The transpose of the matrix, Used to indicate that the product has not yet begun processing. Used to indicate that the product has been processed. The second Lyapunov function is used to represent the system response error model. The symmetric positive definite matrix used for the second Lyapunov function This is used to represent the state scaling gain function of the target reentrant manufacturing system with respect to the time variable. For positive integers, The time variable of the second Lyapunov function The first derivative, for The inverse matrix, The control input coefficient matrix used to represent the target reentrant manufacturing system This matrix represents the dynamic coupling relationships between all reentrant production lines in the target reentrant manufacturing system. The system control gain matrix used to represent the target reentrant manufacturing system. for The transpose of the matrix, for The transpose of the matrix, for The transpose of .

9. The method according to any one of claims 1-6, characterized in that, The correlation of the state feedback control law is represented by the following functional expression: ； in, Used to indicate product completion level Used to represent time variables Used to indicate that the product has not yet begun processing. Used to indicate that the product has been processed. This is used to indicate the starting point of operation in the target reentrant manufacturing system. Used to indicate the preset product delivery cycle. Used to indicate that the target reentrant manufacturing system is in Time and completion rate The actual number of products produced at that time Used to indicate that the target reentrant manufacturing system is in At any given time and the actual number of products is System control input signals at that time This is used to indicate that the target reentrant manufacturing system has a completion level of [missing information]. The preset system delivery output at that time The dynamic model used to represent the system output error in Time and completion rate System output error at that time The state scaling gain function with respect to the time variable is used to represent the system response error model. The system response error model is used to represent the system response error model in Time and completion rate System response error at that time The system control gain matrix used to represent the target reentrant manufacturing system. The system disturbance observer model is used to represent the system disturbance observer model in Time and completion rate The estimated amount of external disturbances to the system at that time.

10. A computer device, characterized in that, The system includes a processor and a memory, the memory storing a computer program executable by the processor, which executes the computer program to implement the preset time disturbance observation capacity control method for a reentrant manufacturing system as described in any one of claims 1-9.

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