Robust compensation method for detecting data communication data packet loss

Abstract

The application provides a robust compensation method for detecting data communication data packet loss, an ALD device communication data packet transmission system and an electronic device, which are applied to the technical field of control or regulation. A control module obtains detection data sent by each detection module in an ALD device through an EtherCAT bus. In this way, the control module discovers the situation of data packet loss, directly generates predicted detection data according to the operation law of the ALD device, and corrects and compensates the predicted detection data by constructing a prediction error and performing weighted average of the actual detection data and the predicted detection data, so as to obtain a corrected detection value. Based on the corrected detection value, the ALD device is controlled in a state, which not only ensures the accuracy of the communication data by using the actual detection data, but also smoothly transitions the control by the correction method of the weighted average value, so that the ALD device can be more stably controlled.

Description

Technical Field

[0001] This application relates to the field of control or regulation technology, and in particular to a robust compensation method for detecting packet loss in data communication. Background Technology

[0002] In atomic layer deposition (ALD) equipment, the detection module often uses EtherCAT communication to transmit its measurement data to the control module for processing and control via the EtherCAT industrial Ethernet bus. For example, the detection instrument transmits measurement data to a programmable logic controller (PLC) or host computer via the EtherCAT industrial Ethernet bus for processing and control. While EtherCAT, as a high-speed real-time bus, offers advantages such as low latency and high reliability, it can still experience anomalies such as data packet loss, delays, or message verification failures under conditions of complex electromagnetic environments or network congestion.

[0003] Traditional solutions to data packet loss fall into two categories: retransmission mechanisms and previous-moment replacement mechanisms. Retransmission mechanisms have poor real-time performance but higher data accuracy, while previous-moment replacement mechanisms have high real-time performance but poor data accuracy. Neither solution can balance data transmission efficiency and accuracy, which can easily lead to poor stability in ALD device control. Summary of the Invention

[0004] In view of this, embodiments of this application provide a robust compensation method for detecting data packet loss in data communication, an ALD device communication data packet transmission system, and an electronic device, thereby reducing the problem of poor stability in ALD device control schemes based on existing data packet solutions.

[0005] In a first aspect, embodiments of this application provide a robust compensation method for detecting packet loss in data communication. The method is applied to a control module in an ALD device. The control module acquires detection data sent by various detection modules in the ALD device via an EtherCAT bus. The method includes: In response to the loss of the detection data packets, the number of data frames in which the data packets were lost, the operating pattern of the ALD device, the last detection data sent by the EtherCAT bus before the data packets were lost, and the number of actual detection data packets sent by the EtherCAT bus after communication was restored are determined. Based on the operating rules of the ALD device, several predicted detection data are determined for the data frame based on the last detection data. Based on several actual detection data and predicted detection data of each data frame, a weighted average of the prediction error is determined, wherein the prediction error is the difference between the actual detection data and the predicted detection data; The predicted detection data is corrected based on the weighted average of the prediction error to obtain the corrected detection value, and the ALD device is then controlled based on the corrected detection value.

[0006] Secondly, this application provides a robust compensation method for detecting packet loss in data communication, the method being applied to a detection module in an ALD device, the method comprising: The system acquires dynamic data from the ALD device and its fixed configuration parameters. The dynamic data includes the measurement value at the current time t. The actual physical quantity of the ALD device at the current time t Estimated physical quantities at the previous time t-1 And the pseudo-covariance matrix updated at the previous time t-1 for estimating the state at the current time t. The fixed configuration parameters include: a first differentiable function whose system model error of the ALD device is known. Second differentiable function Third differentiable function First model error influence term S t The second model error influence term T t and sensitivity penalty coefficient μ t ; The dynamically acquired data and the fixed configuration parameters are input into a preset robust state estimation algorithm with sensitivity penalty, and the physical quantity estimate at the current time t is calculated by the robust state estimation algorithm with sensitivity penalty. The robust state estimation algorithm with sensitivity penalty determines the degree of influence between each input quantity and the modeling error based on the input quantity, applies a penalty term according to the degree of influence of the input quantity that affects the modeling error, and calculates the physical quantity estimate at the current time t based on the corrected parameters. In response to the communication cycle of the EtherCAT bus, the estimated value of the physical quantity at the current time t is... The detection data is output to the control module of the ALD device via the EtherCAT bus, so that the control module of the ALD device executes the method described in the first aspect.

[0007] Thirdly, embodiments of this application provide an ALD device communication data packet transmission system, wherein the ALD device data packet transmission system includes: a detection module, an EtherCAT bus, and a control module, wherein: The detection module is used to acquire dynamic acquisition data from the ALD device and fixed configuration parameters of the ALD device. The dynamic acquisition data includes the measurement value at the current time t. The actual physical quantity of the ALD device at the current time t Estimated physical quantities at the previous time t-1 And the pseudo-covariance matrix updated at the previous time t-1 for estimating the state at the current time t. The fixed configuration parameters include: a first differentiable function whose system model error of the ALD device is known. Second differentiable function Third differentiable function First model error influence term S t The second model error influence term T t and sensitivity penalty coefficient μ t ; The dynamically acquired data and the fixed configuration parameters are input into a preset robust state estimation algorithm with sensitivity penalty, and the physical quantity estimate at the current time t is calculated by the robust state estimation algorithm with sensitivity penalty. ; In response to the communication cycle of the EtherCAT bus, the estimated value of the physical quantity at the current time t is... The control module of the ALD device is output via the EtherCAT bus; The control module is used to respond to the loss of the detection data packets, determine the number of data frames that have lost data packets, the operating rules of the ALD device, the last detection data sent by the EtherCAT bus before the data packets were lost, and the number of actual detection data packets sent by the EtherCAT bus after communication is restored. Based on the operating rules of the ALD device, several predicted detection data are determined for the data frame based on the last detection data. Based on several actual detection data and predicted detection data of each data frame, a weighted average of the prediction error is determined, wherein the prediction error is the difference between the actual detection data and the predicted detection data; The predicted detection data is corrected based on the weighted average of the prediction error to obtain the corrected detection value, and the ALD device is then controlled based on the corrected detection value.

[0008] Fourthly, embodiments of this application provide an electronic device, wherein the electronic device includes: a processor; and a memory storing a program; wherein the program includes instructions, which, when executed by the processor, cause the processor to perform the robust compensation method for detecting data packet loss in data communication as described in the first aspect.

[0009] Fifthly, embodiments of this application provide a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute the robust compensation method for detecting data packet loss in data communication as described in the first aspect.

[0010] The beneficial effects of this application are: This application provides a robust compensation method for detecting packet loss in data communication, an ALD device communication data packet transmission system, and an electronic device. These are applied to a control module or detection module within an ALD device. The control module acquires detection data sent by various detection modules within the ALD device via an EtherCAT bus. Specifically, on the control module side, once it detects packet loss in the detection data sent by the detection modules, it immediately determines the number of data frames lost, the ALD device's operating pattern, the last detection data sent by the EtherCAT bus before the packet loss, and the actual detection data corresponding to each data frame number lost after communication is restored. Then, based on the ALD device's operating pattern, it predicts the predicted detection data corresponding to each data frame number based on the last detection data sent by the EtherCAT bus before the packet loss. Based on the actual detection data and the predicted detection data, it determines the weighted average of the prediction error for the packet loss location. The predicted detection data is then corrected based on this weighted average of the prediction error to obtain a corrected detection value. Finally, the ALD device's state is controlled based on this corrected detection value.

[0011] In the embodiment of this application, when the control module of the ALD device detects data packet loss during interaction with the detection module, it generates predictive detection data using the method provided in this application. However, since the accuracy of this predictive detection data is insufficient for the ALD device, this application corrects and compensates the predictive detection data by constructing a prediction error using actual detection data and predictive detection data, and then performing a weighted average to obtain a corrected detection value. Finally, the device status is controlled based on this corrected detection value. This approach uses actual detection data to ensure the accuracy of communication data and uses a weighted average to correct the data, resulting in smoother transition control and more stable control of the ALD device. Attached Figure Description

[0012] Further details, features, and advantages of this application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which: Figure 1 This application provides a schematic diagram illustrating the principle of a traditional EtherCAT data retransmission mechanism. Figure 2This application provides a schematic diagram illustrating the principle of a traditional EtherCAT data previous-moment replacement mechanism. Figure 3 This paper presents a flowchart illustrating a robust compensation method for packet loss in the detection data communication provided in this application. Figure 4 This paper illustrates another flowchart of the robust compensation method for packet loss in the detection data communication provided in this application. Figure 5 This paper illustrates another flowchart of the robust compensation method for packet loss in the detection data communication provided in this application. Figure 6 This application provides a schematic diagram of a system architecture for an ALD device communication data packet transmission system. Figure 7 A structural block diagram of an exemplary electronic device that can be used to implement embodiments of this application is shown. Detailed Implementation

[0013] Embodiments of this application will now be described in more detail with reference to the accompanying drawings. While some embodiments of this application are shown in the drawings, it should be understood that this application can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this application. It should be understood that the drawings and embodiments of this application are for illustrative purposes only and are not intended to limit the scope of protection of this application.

[0014] It should be understood that the steps described in the method embodiments of this application may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this application is not limited in this respect.

[0015] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the following description. It should be noted that the concepts of "first", "second", etc., mentioned in this application are used only to distinguish different devices, modules, or units, and are not intended to limit the order of functions performed by these devices, modules, or units or their interdependencies.

[0016] It should be noted that the terms "a" and "a plurality of" used in this application are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0017] As described in the background section, EtherCAT communication can experience anomalies such as data packet loss, delays, or message verification failures in complex electromagnetic environments or under network congestion. Specifically, EtherCAT's handling principles for data anomalies can be categorized as follows: Figure 1 The retransmission mechanism shown and as Figure 2 The previous time step replacement mechanism is shown. Figure 1 as well as Figure 2 The specific meanings of the parameters in the table are: L1, L2, ..., L n The detection device detects a certain type of actual physical quantity, such as temperature, humidity, pressure, etc., of device 1, device 2, ..., device n. 'n' is used to identify the device number. In the scenario of temperature detection, L1, L2, ..., L... n The temperature detected by the temperature sensor can be understood as L1, L2, ... L n Physical quantities of the same type, the physical quantity Ln of the i-th device at time t is encoded into It is then sent to the PLC via EtherCAT communication.

[0018] Among them, such as Figure 1 The retransmission mechanism shown can be understood as the PLC detecting data sent from EtherCAT after receiving it. If the data in the second field is lost, EtherCAT should be notified to resend the data. Data in the next field When applied to ALD devices, after the testing instrument sends data via the EtherCAT bus, it needs to wait for the PLC to receive an acknowledgment signal. If no acknowledgment signal is received, it can be determined that a packet loss has occurred, and the testing instrument will resend the same set of data until the PLC replies with an acknowledgment.

[0019] However, because the manufacturing process of ALD equipment requires millisecond-level response—for example, gas flow needs to be adjusted in real time, and retransmission takes time, even if only a few milliseconds—it's like the machines on the production line are waiting for data to guide them, but there are no instructions yet. This can easily lead to a disruption in the process rhythm of the ALD equipment. For instance, if the gas dosage is not adjusted in time, the film thickness will be uneven. If continuous packet loss occurs during this process, the new data detected by the testing instrument will be unable to be transmitted due to the retransmission of old data. In severe cases, this can even cause the ALD equipment to shut down and the semiconductor wafers produced by the ALD equipment to be scrapped.

[0020] like Figure 2 The previous time-of-flight replacement mechanism shown can be understood as the PLC detecting data sent from EtherCAT after receiving the data. If data in the next field is lost, then the data from the previous time point for that field will be used. Replace the lost packet data and continue with subsequent operations.

[0021] like Figure 2 The solution shown eliminates the need to wait for the testing instrument to retransmit data, thus offering advantages over other solutions. Figure 1 The proposed solution offers better real-time performance, which can be visualized as continuing wafer production based on currently known data without affecting the wafer production schedule. However, since parameters such as gas flow rate and temperature within the ALD equipment are dynamically changing rather than fixed, if the data collected at the previous moment contains errors, continuing to use that data for process control at the current moment will lead to error accumulation. If continuous packet loss occurs, the deviation between the actual physical quantities inside the ALD equipment and the physical quantities used by the PLC for actual control becomes immeasurably large. This can easily cause over-reaction of the semiconductor wafer, affecting the process quality. In severe cases, it may even trigger safety alarms and damage the process chamber.

[0022] Therefore, how to ensure the accuracy of data transmission between the detection module and the control module of the atomic layer deposition equipment while stably controlling the ALD equipment has become a technical problem that urgently needs to be solved to improve the wafer manufacturing process precision of the ALD equipment.

[0023] Firstly, this application provides a robust compensation method for detecting packet loss in data communication. The method is applied to a control module in an ALD device. The control module acquires detection data sent by each detection module in the ALD device via an EtherCAT bus. The detection data sent by the detection module is processed using the method provided in the second aspect. In some possible embodiments, it can be as follows: Figure 3 As shown, the method includes the following steps S31~S34: S31. In response to the loss of the detection data, determine the number of data frames that were lost, the operating rules of the ALD device, the last detection data sent by the EtherCAT bus before the data packet loss, and the number of actual detection data frames sent by the EtherCAT bus after communication is restored. S32. Based on the operating rules of the ALD device, determine several predicted detection data for the data frame based on the last detection data; S33. Based on the actual detection data and predicted detection data of each data frame, determine the weighted average value of the prediction error, wherein the prediction error is the difference between the actual detection data and the predicted detection data; S34. The predicted detection data is corrected based on the weighted average of the prediction error to obtain the corrected detection value, and the ALD device is controlled based on the corrected detection value.

[0024] In the embodiment of this application, when the control module of the ALD device detects data packet loss during interaction with the detection module, it generates predictive detection data using the method provided in this application. However, since the accuracy of this predictive detection data is insufficient for the ALD device, this application corrects and compensates the predictive detection data by constructing a prediction error using actual detection data and predictive detection data, and then performing a weighted average to obtain a corrected detection value. Finally, the device status is controlled based on this corrected detection value. This approach uses actual detection data to ensure the accuracy of communication data and uses a weighted average to correct the data, resulting in smoother transition control and more stable control of the ALD device.

[0025] In this embodiment, the control module is primarily a functional module responsible for process control within the ALD (Automatic Level Display) equipment, and can be a Programmable Logic Controller (PLC). The detection module is a detection device within the ALD equipment responsible for collecting various physical quantities. After collecting data through built-in sensors, the detection device encodes the sensor data according to the EtherCAT protocol encoding requirements and outputs it to the PLC controller via the EtherCAT bus. The PLC can control the process flow of the ALD equipment based on the data output from the EtherCAT bus. For example, the detection module can be a temperature detection device. After collecting the measured temperature value inside the reaction chamber of the ALD equipment through a temperature sensor (such as a thermocouple), the temperature detection device estimates the true temperature value inside the reaction chamber based on the measured temperature value. The estimated true temperature value is then encoded according to the EtherCAT protocol encoding rules and output to the PLC controller of the ALD equipment via the EtherCAT bus. The PLC controller controls the power of the heating device in the ALD equipment based on the received true temperature value, thereby ensuring the stability of the process temperature within the ALD equipment.

[0026] In this application embodiment, there can be multiple detection modules, each responsible for acquiring one physical quantity. The physical quantities that may be involved in the ALD equipment manufacturing process include temperature, pressure, gas flow rate, etc. Therefore, the number and type of detection modules can be flexibly set according to the process requirements, and this application does not impose strict limitations. The robust compensation method for packet loss in the detection data communication in this application is divided into a robust compensation method applied to the control module end and a robust compensation method applied to the detection module end, depending on the two ends of the communication interaction. Detection data refers to the data acquired and output to the EtherCAT bus by the detection module. Packet loss in detection data communication refers to the situation where the data acquired and output to the EtherCAT bus by the detection module cannot be accurately received at the other end of the EtherCAT bus due to communication interference or failure. Robustness is a term used in engineering to evaluate the ability of a target object to withstand uncertainty. In this application, robust compensation for packet loss in detection data communication can be understood as ensuring accuracy and stability under uncertainties such as inaccurate modeling, data packet loss, and external interference.

[0027] Whether packet loss has occurred is determined by the receiving PLC control module based on the received data. Therefore, before executing step S31, the robust compensation method provided in this application may further include the following steps: It receives detection data from the EtherCAT bus and determines whether packet loss has occurred based on the preset EtherCAT packet loss judgment logic.

[0028] The pre-defined EtherCAT packet loss detection logic includes three mechanisms for detecting packet loss: The timeout detection mechanism stipulates that the PLC must receive data from the detection module within each cycle by setting a preset communication cycle threshold. If no data is received within the communication cycle threshold, it indicates that a data packet loss has occurred.

[0029] The frame counting continuous mechanism allows the detection module to write a continuously increasing sequence number into the count field of the frame header of each data frame sent to identify the data frame. After receiving the data, the PLC can compare the sequence number of the data frame. If the sequence number of the current frame is not equal to the sequence number of the previous frame + 1, it indicates that a data packet loss has occurred.

[0030] The data integrity verification mechanism involves the detection module calculating the Cyclic Redundancy Check (CRC) code of the data segment when sending data and writing the CRC code to the end of the data frame. After receiving the data frame, the PLC verifies the CRC code at the end of the frame. If the verification results are inconsistent, it indicates that the data frame is corrupted, which means that a data packet has been lost.

[0031] At this time, the control module executes step S31, and in response to the occurrence of data packet loss, immediately determines the number of data frames that have been lost, the operating rules of the ALD device, the last detection data sent by the EtherCAT bus before the data packet loss, and the actual detection data corresponding to the several data frames that have been lost and sent by the EtherCAT bus after communication is restored.

[0032] In this application, the number of data frames that experience packet loss is defined as parameter n. t When executing step S31, the number of data frames that were lost during the time period from the valid time corresponding to the last valid value to the current time can be used as n. t The value of n. Specifically, the time interval between the last valid PLC value and the current packet loss can be determined as the number of data frames n that were lost. t .

[0033] If the PLC control module detects n t A value ≥1 indicates continuous packet loss in EtherCAT communication. In this case, step S32 is executed directly to enter the system model using the ALD device for multi-step prediction. However, continuous packet loss cannot be allowed to continue indefinitely. As one implementation method, if the PLC control module detects n... t If the packet loss exceeds the preset limit n_TH, an alarm will be triggered, and the current semiconductor process flow of the ALD device will be suspended.

[0034] Specifically, the last detection data sent by the EtherCAT bus before data packet loss is the previous valid value, and the n data sent by the EtherCAT bus after communication is restored is the last valid value. t The actual detection data of each data frame refers to the n... t The detection data for which no data packet loss occurred in the n data frames is as follows: t The raw detection data sent in each data frame.

[0035] The method provided in this application determines the ALD equipment control parameters at each location where data packet loss occurs based on the current moment. For the current moment, the PLC control module determines the predicted detection data for ALD equipment process control by executing step S32. Theoretically, the control module should directly use this n... t Using the raw detection data of the data frame for ALD equipment process control is the most accurate method. However, due to the time (n) during which data packet loss occurs, the PLC control module may encounter errors. tDuring the corresponding time interval, the process control of the ALD equipment was not stopped. Instead, predictive detection data was used for ALD equipment control. Since there may be a large data deviation between the predictive detection data and the actual detection data, directly using the original detection data for ALD equipment process control is like a vehicle suddenly switching from a recommended route to a navigation route under real road conditions. The equipment needs to quickly adjust its own state according to the sudden jump in data. Therefore, directly using the original detection data for ALD equipment process control is not conducive to the stable operation of the equipment and the service life of the equipment.

[0036] In this application, the operating rules of the ALD device are specifically represented by the control system model of the ALD device. As one implementation method, the operating rules of the ALD device are represented by the system matrix A. j This indicates that the system matrix A j This was obtained through system modeling of the ALD device. Among them, A... j Let A represent the system matrix at time j. This system matrix describes how the system state changes from time j-1 to time j. For example, assuming control is applied to the physical quantity of gas flow rate, it can be achieved through A. j (0) The increasing coefficients in the matrix indicate that the gas flow rate increases linearly with time. The details regarding system modeling of the ALD device will be explained in detail later; they will not be elaborated upon here.

[0037] As one implementation method, step S32 essentially involves multi-step prediction. This can be understood as not simply using a single prediction detection data point to make up the numbers, but rather continuously generating multiple sets of prediction detection data according to the device's operating rules, covering the entire packet loss period n. t In this way, the process of ALD equipment is not affected, and the generated predictive detection data can closely follow the actual detection data. Compared with the previous replacement mechanism, the multi-step prediction method, which uses multiple sets of predictive detection data for control, is more accurate and does not require too much time.

[0038] The control module PLC can automatically extract the operating trend of the equipment based on the valid detection data sent by the EtherCAT bus before packet loss. For example, the PLC can detect that the gas flow rate is increasing at a constant rate and then stabilizing based on the gas flow rate detection data sent by EtherCAT before packet loss. At this time, it will continue to change according to the fixed process stage. For example, the flow rate must increase from 5L / min to 8L / min in a certain stage. The flow rate increases by 0.1 per frame to generate a predicted gas flow rate value, and the gas flow rate status of the ALD equipment at the current moment is controlled according to the predicted gas flow rate value.

[0039] In one implementation method, when performing multi-step prediction in step S32, the control module can generate n based on the following formula (1). t Predictive detection data : (1) Among them, A j (0) represents the system matrix at time j, where, As a generalization of prior estimation, this formula can also be simplified to: Where A is the system matrix.

[0040] Since the data packet loss occurs when there is interference or a fault on the EtherCAT bus, this situation can be understood as a communication failure. However, because the EtherCAT bus uses the EtherCAT communication protocol, which is designed to withstand transient faults, any interference or fault in EtherCAT is likely due to short-term interference or transient load fluctuations, and normal communication will quickly resume after the interference disappears. During the time interval between the EtherCAT bus packet loss and communication recovery, the control module in this application can directly use predictive detection data. The detection data that has been lost is used to control the status of the ALD equipment. However, there is an error between the predicted detection data and the actual detection data. If the predicted detection data is used directly for the status control of the ALD equipment, it will easily lead to poor detection data accuracy and affect the process production of the ALD equipment.

[0041] Furthermore, because communication can be quickly restored throughout the process, it is possible to obtain the information in milliseconds regarding the loss of data packets sent by the EtherCAT bus after communication is restored. t Each data frame corresponds to actual detection data. However, as described above, directly using actual detection data for state control can easily lead to poor stability of the ALD process due to data abrupt changes. Therefore, it is necessary to continue executing step S33 to combine actual detection data with predicted detection data to determine the prediction error of the control module. Control based on the prediction error can effectively solve the problem of state jumps during data recovery, making the entire detection data compensation process smoother and the ALD equipment process more stable and accurate.

[0042] In some possible embodiments, step S33 described above can be performed through the following steps: For communication recovery time t, backtrack to obtain the prediction error at N acquisition cycles, where the prediction error is the difference between the predicted detection data and the actual detection data; The weighted average of the N prediction errors is obtained by averaging them.

[0043] It is understood that in this embodiment, firstly, the prediction error can be obtained by calculating the difference between the predicted detection data and the actual detection data. As one implementation method, this prediction error can also be called the residual. As an example, the prediction error at time t can be calculated using the following formula (2). : (2) in, This refers to the actual detection data received at the current time t after communication is restored. This represents the predicted detection data corresponding to the current time t.

[0044] Then, the calculated prediction errors are applied backwards using a sliding window approach, automatically backtracking through a sliding window of length N to obtain N prediction errors. This yields a prediction error range that includes data from the previous time step. arrive The historical prediction error sequence of N prediction errors can be represented by the following formula (3): (3) In this application, each prediction error data point in the historical prediction error sequence is referred to as a residual data point. Therefore, the historical prediction error sequence contains N historical residual data points. The value of N is flexibly set according to practical experience. As a preferred implementation, the value range of N is [3,6]. Since the historical prediction error sequence itself is noisy data, it needs to be processed before the system deviation information of the ALD device can be extracted. Therefore, the weighted average value of the prediction error can be obtained by averaging the N prediction errors. Specifically, the weighted average value of the prediction error at the current time t is obtained through parameters. This can be calculated using the following formula (4): (4) in, This refers to the i-th prediction error in the aforementioned historical prediction error sequence. The weighting coefficients representing the historical prediction errors can be determined as follows, as one implementation method: According to the preset linear decreasing weight allocation strategy, a weight coefficient is assigned to each prediction error. In the linear decreasing weight allocation strategy, the prediction error that is closer to the communication recovery time t is assigned a larger weight coefficient.

[0045] This linear decreasing weight allocation strategy assumes that the prediction error closer to the moment of data packet loss more accurately reflects the system's deviation. As one implementation method, this linear decreasing weight allocation strategy satisfies the constraint of the following formula (5): (5) Thus, setting i=1 corresponds to The larger the weighting coefficient of the prediction error for the last data frame before packet loss, the more significant the difference between i=N. The smaller the weighting coefficient of the prediction error corresponding to the data frame furthest from the time of packet loss, the better.

[0046] Furthermore, step S34 involves calculating the weighted average of the predicted errors. For predictive detection data The correction is performed to obtain the corrected detection data, which is referred to as the corrected detection value in this paper. .

[0047] In this application, the correction of the predicted detection data can be broken down into two steps: Step 1: Correct backwards, that is, correct backwards from the current time. This can be done by summing the weighted average of the prediction error obtained by formula (4) with the predicted detection data obtained by formula (1) to correct the predicted detection data. Specifically, the correction can be made according to the following formula (6) for t- The predicted detection data at each time point is corrected: (6) As one implementation method, the corrected detection value calculated by formula (6) can be directly used as the input of the PLC control module's state control algorithm for PLC logic state control. This method is more robust than... Figure 1 , Figure 2 The robustness shown is good, but it does not combine the actual detection value. It is a kind of control using historical static values. There is still a certain amount of parameter jump or stagnation between it and the current actual detection data. Therefore, this scheme of directly using the corrected detection data calculated by formula (6) to control the equipment status cannot accurately judge the current real-time process change requirements and is not the best detection data compensation scheme.

[0048] Based on this, further, in some possible embodiments, the ALD device can be controlled in terms of device status according to the corrected detection value through the following steps.

[0049] The weighted average of the prediction error is input into the control algorithm of the ALD device in a decayed manner. The control algorithm of the ALD device smooths the corrected detection value based on the weighted average of the prediction error and the decay factor to generate the target detection value at the location where the data packet loss occurred. The ALD device is controlled according to the target detection value.

[0050] It is understood that in this embodiment, after communication is restored, the predicted detection value during packet loss is gradually transitioned to the actual detection value after communication is restored by using an attenuation factor combined with a weighted average of the prediction error. In other words, a controllable, small-amplitude adjustment is used instead of a direct jump to the actual detection value, thereby making the process control of the entire ALD equipment more stable and smooth.

[0051] Specifically, as one implementation method, the attenuation factor preset in the control logic algorithm of the ALD device can be obtained. The attenuation factor and the weighted average of the prediction error calculated in step S33 are then input into the detection data transition equation shown in formula (7) to obtain the detection data input to the control logic algorithm at time k. : (7) Where M is the number of injection cycles.

[0052] It is understandable that predictive detection data is used for ALD device state control at the current time and at the time of data packet loss, while detection data calculated using formula (7) above is used from time k onwards for ALD device state control. In formula (7), the attenuation factor... The attenuation factor has a value range of (0,1). As a preferred implementation, this attenuation factor... The value can be 0.5. Among them, Similar to the aforementioned formula (1), it is a system matrix based on devices. Similarly, the basic prediction detection data is calculated. Same here. Let k be the state estimation covariance matrix. Let k be the measurement matrix at time k. Let be the sensor measurement noise matrix at time k. This is the measurement value at time k.

[0053] Combining formulas (5), (6), and (7) above, it can be understood that the packet loss joint compensation logic provided in this application can be based on the following formula for joint compensation:

[0054] Through the exponent term in the formula This allows the impact of deviation compensation to decrease exponentially with the increase of the time step. After several cycles k, the impact of the prediction error gradually becomes negligible, and the system gradually transitions to actual detection data for ALD equipment status control. It can be understood that after communication is restored, the above formula (7) is automatically executed once in each control cycle until the impact of the smoothing attenuation term can be ignored. Engineering practice has shown that a smooth transition to actual detection data for equipment status control can usually be achieved after 3 to 5 cycles.

[0055] The robust compensation method for data packet loss in the detection data communication provided in this application can achieve stable and accurate compensation for data packet loss by improving the software in the control module without changing the hardware structure. It can be adapted to various types and models of ALD devices and has better engineering applicability and promotion value.

[0056] Secondly, this application provides a robust compensation method for detecting packet loss in data communication. This method is applied to the detection module in an ALD device, and in some possible embodiments, it can be as follows: Figure 4 The method described includes steps S41 to S43, whereby the detection module executes steps S41 to S43 and then sends the estimated physical quantity values ​​of the ALD device at the current time t as detection data to the control module in the ALD device: S41. Obtain the dynamic acquisition data of the ALD device and the fixed configuration parameters of the ALD device; The dynamically acquired data includes: the measurement value at the current time t. The actual physical quantity of the ALD device at the current time t Estimated physical quantities at the previous time t-1 And the pseudo-covariance matrix updated at the previous time t-1 for estimating the state at the current time t. ; The fixed configuration parameters include: a first differentiable function whose system model error of the ALD device is known. Second differentiable function Third differentiable function First model error influence term S t The second model error influence term T t and sensitivity penalty coefficient μ t ; S42. Input the dynamically acquired data and the fixed configuration parameters into a preset robust state estimation algorithm with sensitivity penalty, and calculate the physical quantity estimate at the current time t obtained by the robust state estimation algorithm with sensitivity penalty; wherein, the robust state estimation algorithm with sensitivity penalty determines the degree of influence between each input quantity and the modeling error based on the input quantity, applies a penalty term according to the degree of influence of the input quantity that affects the modeling error, and calculates the physical quantity estimate at the current time t based on the corrected parameters; The estimated value of the physical quantity at the current time t can be denoted as: .

[0057] S43. In response to the communication cycle of the EtherCAT bus, the estimated value of the physical quantity at the current moment is output to the control module of the ALD device through the EtherCAT bus, so that the control module of the ALD device executes the method described in the first aspect.

[0058] As described above, the detection module is a device within the ALD (Alternating Current Display) equipment responsible for collecting various physical quantities. After acquiring data through built-in sensors, the detection device encodes the sensor data according to the EtherCAT protocol and outputs it to the PLC controller via the EtherCAT bus. During the physical quantity acquisition process, factors such as sensor errors, equipment aging, and environmental interference can cause deviations between the acquired physical quantities and the actual physical quantities within the ALD equipment's reaction chamber. To eliminate these deviations, related technologies propose mathematical modeling of the detection module, incorporating various influencing factors into the data acquisition process. This allows the resulting mathematical model to estimate the physical quantities of the ALD equipment, ensuring that the estimated quantities approximate the actual physical quantities within the ALD equipment's reaction chamber. For example, a Kalman filter algorithm can be used to model the ALD equipment's reaction chamber. However, modeling errors still exist during this process. This Kalman filter algorithm only considers interference and reading errors, neglecting modeling errors. Therefore, significant discrepancies still exist between the estimated and actual physical quantities within the ALD equipment.

[0059] In this embodiment of the application, the dynamically acquired data and fixed configuration parameters of the ALD device are input into a preset robust state estimation algorithm with sensitivity penalty. This algorithm determines the degree of influence between each input quantity and the modeling error based on the input quantity, applies a penalty term to the input quantity according to the degree of influence of the input quantity on the modeling error, and finally calculates the estimated physical quantity at the current time t based on the corrected parameters. This reduces the impact of model error on the estimated physical quantity, making the calculated estimated physical quantity at the current time t closer to the actual physical quantity, further improving the accuracy of the detection data sent by the detection module to the EtherCAT bus, thereby improving the overall process accuracy of the ALD device.

[0060] The following will provide a detailed explanation of steps S41 to S43 with specific examples: The dynamically acquired data refers to various physical quantities within the ALD device collected by the detection module through sensors, such as temperature, pressure, and gas flow rate. The entire method estimates a single type of physical quantity. For example, the method provided in this application estimates the actual gas flow rate within the ALD device, calculating the estimated physical quantity value at the current time t. This is the estimated gas flow rate inside the reaction chamber of the ALD device at the current moment.

[0061] Fixed configuration parameters refer to the parameters involved in the constructed sensitivity-penalized robust estimation algorithm, which are manually configured by process engineers in the algorithm logic. Specifically, they may include the first possible function with known errors in the system model constructed during ALD equipment modeling. Second differentiable function Third differentiable function The first model error influence term St, the second model error influence term Tt, and the sensitivity penalty coefficient μ t The first model error impact term is used to evaluate which parameters in the current system model affect the modeling error. The most sensitive. For example, taking the estimation of gas flow rate as an example, the degree of influence of the deviation of the gas valve opening parameter on the gas flow rate estimation result can be judged by the first model error influence term. If the valve opening parameter deviation is 1%, the gas flow rate estimation value will deviate by 5%, which indicates that the valve opening parameter is more sensitive to modeling error and has higher sensitivity.

[0062] Among them, the first differentiable function, the second differentiable function, and the third differentiable function are used to describe the physical operation law of the ALD device, and can be obtained by fitting through calibration experiments. As one implementation method, the system model of the ALD device can be modeled to obtain the system model used by the detection module as shown in the following formula (8): (8); in, The measurement value at the current time t. This represents the actual physical quantity of the ALD device at the current time t, i.e., the actual state value within the ALD device. The process noise at time t, Let be the measurement noise at time t. For a by l The uncertain component corresponding to each actual scalar Composition, and assuming this l There are several uncertain components, where h = 1, 2, 3... l .

[0063] In this embodiment, the white noise follows a normal distribution, therefore the initial value of the system state is... Process noise and measuring noise For the independent random variables, their respective means correspond to the following formula (9): (9) in, , as well as They are ), as well as The covariance.

[0064] Based on this, a cost function can be constructed for the detection module in the ALD device when performing robust state estimation. This cost function is shown in the following formula (10): (10) in, The design parameter is set by the designer based on experience, and its value range is (0,1]. When its value is 1, the robust state estimation degenerates into the traditional Kalman filter algorithm. This means that when its value is 1, the estimation accuracy is consistent with the accuracy of the traditional Kalman filter estimation algorithm.

[0065] in, The following formula (11) is used to calculate: (11) In this embodiment of the application, the first model error influence term S t The second model error influence term T t It plays a crucial role in the parameter correction process of the system model, among which the first model error influence term S t and the second model error influence term T tThe matrix used to represent the impact of model errors, during parameter correction, is shown below:

[0066]

[0067] Among them, the first model error influence term The matrix elements in are The matrix elements It is calculated using the following formula (12): (12) The second model error term T t The matrix elements in are The matrix elements It is calculated using the following formula (13): (13) Where h = 1, 2, 3... l .

[0068] Wherein, the sensitivity penalty coefficient μ t It is calculated using the following formula (14): (14) Based on the aforementioned fixed configuration parameters and dynamically acquired data, in some possible embodiments, when executing step S42, the dynamically acquired data and the fixed configuration parameters are input into a preset robust state estimation algorithm with sensitivity penalty, and the physical quantity estimate value at the current time t obtained by the robust state estimation algorithm with sensitivity penalty is calculated. ,include: Initialize the various parameters involved in the system model of the ALD device, mainly initializing: system estimated state values. pseudo-covariance matrix Specifically, the initialization should be performed according to the following formula (15): (15) in, It is calculated using the following formula (16): (16) Furthermore, the sensitivity penalty coefficient μ is used. t The system model of the ALD device is modified according to the following formula (17): (17) in, The pseudo-covariance matrix of the state estimate of the corrected ALD device. This is the inverse matrix of the error influence term of the first model. The corrected system matrix, The corrected process noise covariance matrix is... This is the coefficient matrix of the process noise. The corrected input matrix, I It is the identity matrix; Based on the corrected system model parameters, the pseudo-covariance matrix of the state estimate at the next time step is obtained according to the following formula (18). And the actual physical quantities of the ALD device at the next moment. Perform state estimation: (18) Where t represents the current time and t+1 represents the next time. For the system matrix, The transpose of the system matrix For the measurement matrix at the next time step, Let the prior covariance matrix be for the next time step. Let be the posterior covariance matrix at the next time step. For the equivalent sensor measurement noise matrix, The inverse matrix of the equivalent sensor measurement noise matrix. Let be the covariance matrix of the process noise; The corrected process noise covariance matrix is... This is the measurement value at the next moment.

[0069] in, as well as It is a pseudo-covariance matrix, and as well as .

[0070] The estimated value of the physical quantity at the current time t is calculated based on the above formula (18). Then, the estimated value of the physical quantity at the current time t is... The data is sent to the control module through the EtherCAT communication port according to the communication cycle specified by the EtherCAT protocol. When a data packet is lost, the control module executes the method described in the first aspect to assist the control module in smoothly and accurately controlling the status of the ALD device.

[0071] By choosing the embodiments of this application, the estimation bias caused by system modeling errors is effectively suppressed. While maintaining the same computational efficiency as Kalman filtering, the sensitivity to model uncertainty is significantly reduced, and the estimation accuracy under non-ideal modeling conditions is improved.

[0072] Thirdly, this application provides an ALD device communication data packet transmission system, in some possible embodiments, such as Figure 6 As shown, the system 60 includes the following components: a detection module 601, an EtherCAT bus 602, and a control module 603; wherein: Detection module 601 is used to acquire dynamic acquisition data of the ALD device and fixed configuration parameters of the ALD device. The dynamic acquisition data includes: the measurement value at the current time t. The actual physical quantity of the ALD device at the current time t Estimated physical quantities at the previous time t-1 And the pseudo-covariance matrix updated at the previous time t-1 for estimating the state at the current time t. The fixed configuration parameters include: a first differentiable function whose system model error of the ALD device is known. Second differentiable function Third differentiable function First model error influence term S t The second model error influence term T t and sensitivity penalty coefficient μ t ; The dynamically acquired data and the fixed configuration parameters are input into a preset robust state estimation algorithm with sensitivity penalty, and the physical quantity estimate at the current time t is calculated by the robust state estimation algorithm with sensitivity penalty. The robust state estimation algorithm with sensitivity penalty determines the degree of influence between each input quantity and the modeling error based on the input quantity, applies a penalty term according to the degree of influence of the input quantity that affects the modeling error, and calculates the physical quantity estimate at the current time t based on the corrected parameters. In response to the communication cycle of the EtherCAT bus, the estimated value of the physical quantity at the current time t is... The control module of the ALD device is output via the EtherCAT bus; Control module 603 is used to respond to the loss of data packets in the detection data, determine the number of data frames in which data packets were lost, the operating rules of the ALD device, the last detection data sent by the EtherCAT bus before the data packets were lost, and the number of actual detection data frames sent by the EtherCAT bus after communication was restored. Based on the operating rules of the ALD device, several predicted detection data are determined for the data frame based on the last detection data. Based on several actual detection data and predicted detection data of each data frame, a weighted average of the prediction error is determined, wherein the prediction error is the difference between the actual detection data and the predicted detection data; The predicted detection data is corrected based on the weighted average of the prediction error to obtain the corrected detection value, and the ALD device is then controlled based on the corrected detection value.

[0073] The specific execution logic of the detection module 601 and the control module 603 mentioned above is described in the method descriptions of the first and second aspects, and will not be repeated here.

[0074] The names of the messages or information exchanged between multiple devices in the embodiments of this application are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0075] Fourthly, exemplary embodiments of this application also provide an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor. The memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to cause the electronic device to perform a method according to an embodiment of this application.

[0076] Fifthly, exemplary embodiments of this application also provide a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a computer's processor, is used to cause the computer to perform a method according to an embodiment of this application.

[0077] In a sixth aspect, exemplary embodiments of this application also provide a computer program product, including a computer program, wherein, when executed by a processor of a computer, the computer program is used to cause the computer to perform a method according to an embodiment of this application.

[0078] refer to Figure 7 The present invention describes a structural block diagram of an electronic device 700 that can serve as a server or client of this application, which is an example of a hardware device that can be applied to various aspects of this application. The electronic device is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the application described and / or claimed herein.

[0079] like Figure 7 As shown, the electronic device 700 includes a computing unit 701, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 702 or a computer program loaded into a random access memory (RAM) 703 from a storage unit 708. The RAM 703 may also store various programs and data required for the operation of the electronic device 700. The computing unit 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output interface (I / O interface) 705 is also connected to the bus 704.

[0080] Multiple components in electronic device 700 are connected to I / O interface 705, including: input unit 706, output unit 707, storage unit 708, and communication unit 709. Input unit 706 can be any type of device capable of inputting information to electronic device 700. Input unit 706 can receive input digital or character information and generate key signal inputs related to user settings and / or function control of electronic device. Output unit 707 can be any type of device capable of presenting information and may include, but is not limited to, a display, speaker, video / audio output terminal, vibrator, and / or printer. Storage unit 708 may include, but is not limited to, disk and optical disk. Communication unit 709 allows electronic device 700 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers, and / or chipsets, such as Bluetooth™ devices, WiFi devices, WiMax devices, cellular communication devices, and / or the like.

[0081] The computing unit 701 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 701 performs the various methods and processes described above. For example, in some embodiments, the aforementioned robust compensation method for detecting data communication packet loss can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 708. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 700 via ROM 702 and / or communication unit 709. In some embodiments, the computing unit 701 can be configured to perform the aforementioned robust compensation method for detecting data communication packet loss by any other suitable means (e.g., by means of firmware).

[0082] The program code used to implement the methods of this application may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0083] In the context of this application, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0084] As used in this application, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, device, and / or apparatus (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including machine-readable media that receive machine instructions as machine-readable signals. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0085] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0086] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0087] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other.

Claims

1. A robust compensation method for detecting packet loss in data communication, characterized in that, The method is applied to the control module in an ALD device, wherein the control module acquires detection data sent by each detection module in the ALD device via an EtherCAT bus, and the method includes: In response to the loss of the detection data packets, the number of data frames in which the data packets were lost, the operating pattern of the ALD device, the last detection data sent by the EtherCAT bus before the data packets were lost, and the number of actual detection data packets sent by the EtherCAT bus after communication was restored are determined. Based on the operating rules of the ALD device, several predicted detection data are determined for the data frame based on the last detection data. Based on several actual detection data and predicted detection data of each data frame, a weighted average of the prediction error is determined, wherein the prediction error is the difference between the actual detection data and the predicted detection data; The predicted detection data is corrected based on the weighted average of the prediction error to obtain the corrected detection value, and the ALD device is then controlled based on the corrected detection value.

2. The method according to claim 1, characterized in that, The process of controlling the ALD device's status based on the corrected detection value includes: The weighted average of the prediction error is input into the control algorithm of the ALD device in a decayed manner. The control algorithm of the ALD device smooths the corrected detection value based on the weighted average of the prediction error and the decay factor to generate the target detection value at the location where the data packet loss occurred. The ALD device is controlled according to the target detection value.

3. The method according to claim 1, characterized in that, The operating rules of the ALD device are determined by system matrix A. j The system matrix A represents... j This was obtained by performing a system modeling of the ALD device.

4. The method according to claim 1, characterized in that, The step of determining the weighted average of the prediction error based on several actual detection data and predicted detection data in each data frame includes: For communication recovery time t, backtrack to obtain the prediction error at N acquisition cycles, where the prediction error is the difference between the predicted detection data and the actual detection data; The weighted average of the N prediction errors is obtained by averaging them.

5. The method according to claim 1 or 4, characterized in that, When performing the step of determining the weighted average of the prediction error based on several actual detection data and predicted detection data of each data frame, the method further includes: According to the preset linear decreasing weight allocation strategy, a weight coefficient is assigned to each prediction error. In the linear decreasing weight allocation strategy, the prediction error that is closer to the communication recovery time t is assigned a larger weight coefficient.

6. A robust compensation method for detecting packet loss in data communication, characterized in that, The method is applied to the detection module in an ALD device, and the method includes: The system acquires dynamic data from the ALD device and its fixed configuration parameters. The dynamic data includes the measurement value at the current time t. The actual physical quantity of the ALD device at the current time t Estimates of physical quantities at the previous time t-1 And the pseudo-covariance matrix updated at the previous time t-1 for estimating the state at the current time t. The fixed configuration parameters include: a first differentiable function whose system model error of the ALD device is known. Second differentiable function Third differentiable function First model error influence term S t The second model error influence term T t and sensitivity penalty coefficient μ t ; The dynamically acquired data and the fixed configuration parameters are input into a preset robust state estimation algorithm with sensitivity penalty, and the physical quantity estimate at the current time t is calculated by the robust state estimation algorithm with sensitivity penalty. The robust state estimation algorithm with sensitivity penalty determines the degree of influence between each input quantity and the modeling error based on the input quantity, applies a penalty term according to the degree of influence of the input quantity that affects the modeling error, and calculates the physical quantity estimate at the current time t based on the corrected parameters. In response to the communication cycle of the EtherCAT bus, the estimated value of the physical quantity at the current time t is... The detection data is output to the control module of the ALD device via the EtherCAT bus, so that the control module of the ALD device can execute the method as described in any one of claims 1 to 5.

7. The method according to claim 6, characterized in that, The dynamically acquired data and the fixed configuration parameters are input into a preset robust state estimation algorithm with sensitivity penalty, and the physical quantity estimate at the current time t is calculated by the robust state estimation algorithm with sensitivity penalty. ,include: Using the aforementioned sensitivity penalty coefficient μ t The system model parameters of the ALD device are corrected as follows: ； in, The pseudo-covariance matrix of the state estimate of the corrected ALD device. This is the first model error factor. This is the second model error influence term. The corrected system matrix, The corrected process noise covariance matrix is... This is the coefficient matrix of the process noise. This is the coefficient matrix of the corrected process noise. I It is the identity matrix; Based on the corrected system model parameters, the pseudo-covariance matrix of the state estimate for the next time step. And the actual physical quantities of the ALD device at the next moment. Perform state estimation: ； Where t represents the current time and t+1 represents the next time. For the system matrix, This is the transpose of the system matrix. For the measurement matrix at the next time step, Let the prior covariance matrix be for the next time step. Let be the posterior covariance matrix for the next time step. For the equivalent sensor measurement noise matrix, The inverse matrix of the equivalent sensor measurement noise matrix. Let be the covariance matrix of the process noise; The corrected process noise covariance matrix is... This is the measurement value at the next moment.

8. An ALD device communication data packet transmission system, characterized in that, The ALD device data packet transmission system includes: a detection module, an EtherCAT bus, and a control module, wherein: The detection module is used to acquire dynamic acquisition data from the ALD device and fixed configuration parameters of the ALD device. The dynamic acquisition data includes the measurement value at the current time t. The actual physical quantity of the ALD device at the current time t Estimates of physical quantities at the previous time t-1 And the pseudo-covariance matrix updated at the previous time t-1 for estimating the state at the current time t. The fixed configuration parameters include: a first differentiable function whose system model error of the ALD device is known. Second differentiable function Third differentiable function First model error influence term S t The second model error influence term T t and sensitivity penalty coefficient μ t ; The dynamically acquired data and the fixed configuration parameters are input into a preset robust state estimation algorithm with sensitivity penalty, and the physical quantity estimate at the current time t is calculated by the robust state estimation algorithm with sensitivity penalty. ; In response to the communication cycle of the EtherCAT bus, the estimated value of the physical quantity at the current time t is... The control module of the ALD device is output via the EtherCAT bus; The control module is used to respond to the loss of the detection data packets, determine the number of data frames that have lost data packets, the operating rules of the ALD device, the last detection data sent by the EtherCAT bus before the data packets were lost, and the number of actual detection data packets sent by the EtherCAT bus after communication is restored. Based on the operating rules of the ALD device, several predicted detection data are determined for the data frame based on the last detection data. Based on several actual detection data and predicted detection data of each data frame, a weighted average of the prediction error is determined, wherein the prediction error is the difference between the actual detection data and the predicted detection data; The predicted detection data is corrected based on the weighted average of the prediction error to obtain the corrected detection value, and the ALD device is then controlled based on the corrected detection value.

9. An electronic device, characterized in that, The electronic device includes: a processor and a memory storing a program; wherein the program includes instructions that, when executed by the processor, cause the processor to perform the method according to any one of claims 1-5 or 6-7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-5 or 6-7.

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