A multi-station cooperative control method and system based on event triggering and forward-looking synchronization

Abstract

This invention provides a multi-station collaborative control method based on event triggering and look-ahead synchronization, comprising the following steps: S1, defining nominal motion parameters for each station; S2, calculating the cumulative time deviation up to the current station when a physical completion event is detected; S3, performing online optimization calculations within a prediction time domain including multiple future stations based on the cumulative time deviation to determine the optimal target runtime for compensating for the cumulative time deviation; S4, generating and issuing a new motion curve for the first station in the prediction time domain according to the optimal target runtime, and using this station as the new current station, repeatedly executing steps S2 to S4. This invention enables the system to proactively eliminate minor time deviations caused by uncertainties such as material differences and mechanical wear, avoiding the cumulative effect of errors.

Description

Technical Field

[0001] This invention relates to a multi-station control method and system, specifically to a multi-station collaborative control method and system based on event triggering and look-ahead synchronization, belonging to the field of intelligent manufacturing equipment control technology. Background Technology

[0002] High-speed paper cup machines and other automated equipment typically consist of multiple sequentially linked workstations, such as paper fan cutting, paper fan conveying, cup body rolling, cup bottom stamping, top bottom knurling, and rim forming. To achieve high-speed production, the actions of these workstations must be precisely synchronized and coordinated.

[0003] Currently, the mainstream control method is rigid synchronization. In this mode, all servo drive units at all workstations strictly follow a preset master clock curve based on a virtual spindle angle or a fixed time cycle. The fundamental flaw of this mode is that it is based on an idealized assumption that all mechanical parts and materials are in a perfect and constant state.

[0004] However, in actual high-speed production, minute changes in paper thickness, humidity, and stiffness, as well as minor wear or gaps in mechanical parts due to friction and temperature variations, can cause milliseconds or even microseconds of delay in the actual completion time of a certain workstation. In rigid synchronization mode, subsequent workstations cannot detect this deviation and will still execute actions according to the predetermined schedule. This tiny timing deviation accumulates and amplifies rapidly among multiple high-speed workstations, ultimately leading to quality problems such as inaccurate bonding positions, poor knurling, and misregistration in printing. In severe cases, it can even cause paper jams and machine collisions. To ensure yield, manufacturers have to reduce the operating cycle time of the equipment, which directly limits further improvements in paper cup production efficiency and prevents the full utilization of the performance of high-end servo systems. Summary of the Invention

[0005] Based on the above background, the purpose of this invention is to provide a multi-station collaborative control method and system based on event triggering and look-ahead synchronization, which can break free from the constraints of rigid clocks and actively compensate for small time deviations between stations, thereby significantly improving the collaborative accuracy between stations, yield, and equipment operation stability under higher production cycles.

[0006] To achieve the above-mentioned objectives, the present invention provides the following technical solution:

[0007] A multi-station collaborative control method based on event triggering and look-ahead synchronization includes the following steps:

[0008] S1. Define nominal motion parameters for each workstation, wherein the nominal motion parameters include a nominal motion curve and a physical completion event used to characterize the completion of the workstation's action;

[0009] S2. Monitor the operating status of the current workstation in real time, and when a physical completion event of the current workstation is detected, calculate the cumulative time deviation up to the current workstation.

[0010] S3. Based on the accumulated time deviation, perform online optimization calculations within the prediction time domain that includes multiple future workstations to determine the optimal target runtime for compensating the accumulated time deviation; wherein, the objective of the online optimization calculation is to minimize the comprehensive cost function formed by the predicted motion impact of all workstations and the total time deviation within the prediction time domain, while satisfying the total time compensation constraint.

[0011] S4. Based on the optimal target runtime, generate and issue a new motion curve for the first workstation in the predicted time domain, and use this workstation as the new current workstation to repeat steps S2 to S4.

[0012] Preferably, in step S2, a hardware interrupt signal is generated when a physical completion event of the current workstation is detected, the actual completion time of the workstation action is determined by capturing the hardware interrupt signal, and the cumulative time deviation is calculated accordingly.

[0013] Preferably, in step S2, the cumulative time deviation is calculated by adding the new time deviation generated at the current workstation to the cumulative time deviation transmitted from the previous workstation.

[0014] Preferably, in step S3, the predicted motion impact is determined based on a preset function representing the relationship between the target running time and the peak value of the required acceleration of the motion curve.

[0015] Preferably, in step S3, the comprehensive cost function is the sum of the weighted term for the predicted motion impact and the weighted term for the total time deviation, wherein the weight coefficients of the weighted terms are adjusted according to different priority requirements for motion smoothness or deviation compensation speed.

[0016] Preferably, in step S3, the online optimization calculation is also constrained by the dynamic feasibility boundary of each station, so that the generated new motion curve does not exceed the preset maximum speed and maximum acceleration limits.

[0017] Preferably, in step S3, the online optimization calculation is performed using a sequential quadratic programming algorithm or an interior point method.

[0018] Preferably, step S4 further includes generating new motion curves for the remaining workstations (excluding the first workstation) in the predicted time domain based on the optimal target runtime, and preloading these curves as provisional curves.

[0019] Preferably, in step S4, the motion curve is an S-shaped acceleration / deceleration curve.

[0020] A multi-station collaborative control system based on event triggering and look-ahead synchronization includes multiple sensors disposed on multiple serially associated workstations, multiple servo drive units for driving the multiple serially associated workstations respectively, and a look-ahead synchronization controller electrically connected to the multiple sensors and the multiple servo drive units. The look-ahead synchronization controller is configured to run a multi-station collaborative control method based on event triggering and look-ahead synchronization as described above.

[0021] Compared with the prior art, the present invention has the following advantages:

[0022] This invention discloses a multi-station collaborative control method and system based on event triggering and look-ahead synchronization. By capturing the physical completion event of each station in real time to trigger subsequent actions, and using a look-ahead optimization algorithm to dynamically plan the optimal deviation compensation strategy in multiple stations in the future, a flexible and highly adaptable collaborative control method is achieved. This method enables the system to actively eliminate small time deviations caused by uncertainties such as material differences and mechanical wear, avoiding the cumulative effect of errors. Thus, without sacrificing the yield, the equipment can be stably operated at a higher production cycle, significantly improving production efficiency and equipment operation stability. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0024] Figure 1 This is a flowchart illustrating a multi-station collaborative control method based on event triggering and look-ahead synchronization according to the present invention.

[0025] Figure 2 This is a graph showing the functional relationship between the weighting coefficients in the comprehensive cost function of this invention and the current cumulative time deviation.

[0026] Figure 3 This is a graph showing the motion impact of the servo drive unit as a function of time in a multi-station collaborative control method based on event triggering and look-ahead synchronization, as well as a traditional rigid synchronization method, for deviation compensation. Detailed Implementation

[0027] The technical solution of the present invention will be further described in detail below through specific embodiments and in conjunction with the accompanying drawings. It should be understood that the implementation of the present invention is not limited to the following embodiments, and any modifications and / or alterations made to the present invention will fall within the protection scope of the present invention.

[0028] In this invention, unless otherwise specified, all parts and percentages are by weight, and the equipment and raw materials used are commercially available or commonly used in the art. Unless otherwise specified, the methods in the following embodiments are conventional methods in the art. Unless otherwise specified, the components or equipment in the following embodiments are general standard parts or components known to those skilled in the art, and their structures and principles can be learned by those skilled in the art through technical manuals or conventional experimental methods.

[0029] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings. In this detailed description, numerous specific details are set forth to facilitate explanation and provide a thorough understanding of the embodiments of the present invention. However, one or more embodiments may be practiced by those skilled in the art without these specific details.

[0030] This invention discloses a multi-station collaborative control method based on event triggering and look-ahead synchronization, applied in a multi-station collaborative control system, with a high-speed paper cup machine as a typical application scenario. The system hardware mainly includes a look-ahead synchronization controller as the control core, multiple servo drive units that drive each serially associated station of the paper cup machine, and high-frequency response sensors, such as fiber optic sensors or vision sensors, installed at the key action completion positions of each station.

[0031] like Figure 1 As shown, the implementation steps of this multi-station collaborative control method are as follows.

[0032] S1. Define nominal motion parameters for each workstation, wherein the nominal motion parameters include a nominal motion curve and a physical completion event used to characterize the completion of the workstation's action;

[0033] S2. Monitor the operating status of the current workstation in real time, and when a physical completion event of the current workstation is detected, calculate the cumulative time deviation up to the current workstation.

[0034] S3. Based on the accumulated time deviation, perform online optimization calculations within the prediction time domain that includes multiple future workstations to determine the optimal target runtime for compensating the accumulated time deviation; wherein, the objective of the online optimization calculation is to minimize the comprehensive cost function formed by the predicted motion impact of all workstations and the total time deviation within the prediction time domain, while satisfying the total time compensation constraint.

[0035] S4. Based on the optimal target runtime, generate and issue a new motion curve for the first workstation in the predicted time domain, and use this workstation as the new current workstation to repeat steps S2 to S4.

[0036] The following provides a detailed explanation of each step.

[0037] Step S1: Define nominal motion parameters for each workstation. The nominal motion parameters include nominal motion curves and physical completion events used to characterize the completion of workstation actions.

[0038] Before the system is put into production or during the parameter setting stage, each workstation i (i=1,2,...,N) is defined offline with specific parameters as follows.

[0039] Nominal motion curve S i,nom (t): An idealized motion curve that describes the positional relationship of the servo drive unit of station i from the starting position to the ending position over time under perfect conditions without any interference. This curve is usually designed as a smooth S-shaped acceleration and deceleration curve.

[0040] Nominal runtime T i,nom After executing the nominal motion curve S i,nom (t) Total time required.

[0041] Physical Completion Event Ei: A definite physical state that can be captured by sensors, indicating that the core action of station i has been truly completed. For example, for a punching station, this event could be the punch moving to the top dead center. For a paper fan conveying station, this event could be the edge of the paper fan triggering a fiber optic sensor at a specified location.

[0042] Dynamic feasibility boundary: Calibrate and set the physical limits of each servo drive unit, including the maximum speed V. i,max Maximum acceleration A i,max and maximum jerk J i,max This serves as a security constraint for subsequent online optimization.

[0043] S2. Monitor the operating status of the current workstation in real time, and calculate the cumulative time deviation up to the current workstation when a physical completion event is detected at the current workstation.

[0044] At the start of a production cycle, the look-ahead synchronous controller instructs the servo drive unit at station 1 to follow its nominal motion curve S. i,nom (t) begins to move.

[0045] Meanwhile, the look-ahead synchronous controller monitors the status of workstation 1 in real time via a connected high-frequency response sensor. Once the sensor detects the occurrence of physical completion event E1, a hardware interrupt signal is triggered. The look-ahead synchronous controller captures this hardware interrupt signal and records the precise moment of occurrence of the event, denoted as the actual completion time T of workstation 1. 1,actual .

[0046] Then, the look-ahead synchronous controller calculates the cumulative time deviation ΔT up to the current workstation (which is workstation 1 at this time). acc,1 The calculation process is as follows:

[0047] Calculate the new time deviation generated by the current workstation:

[0048]

[0049] Update the cumulative time deviation. For the first workstation, ΔT acc,1 =ΔT1. For subsequent workstation i, the formula for calculating the cumulative time deviation is:

[0050]

[0051] in, It is the cumulative time deviation carried over from the previous workstation. It is the optimized target runtime used when workstation i is executed.

[0052] S3. Based on the accumulated time deviation, perform online optimization calculations within the predicted time domain that includes multiple future workstations to determine the optimal target runtime for compensating for the accumulated time deviation.

[0053] The online optimization calculation performed by the look-ahead synchronous controller uses the predictive time-domain impact optimization algorithm. This algorithm does not immediately address the deviation; instead, it looks ahead to H workstations (H≥2, where H can be called the prediction time-domain length) and finds the optimal solution among these H workstations to absorb the accumulated time deviation ΔT. acc,1 .

[0054] Specifically, the optimization algorithm for predicting time-domain shocks is constructed and the following optimization problem is solved:

[0055] Optimization variable: A vector consisting of the new target runtimes for the next H workstations. .

[0056] Comprehensive cost function: The goal is to find This makes the comprehensive cost function defined below... To reach the minimum.

[0057]

[0058] The following are descriptions of the various aspects of this function.

[0059] First item This is the cost item for motion impact. It is a pre-calibrated or calculated function that describes the runtime of station k when it is set to... The peak value of the maximum acceleration that must be reached for its S-shaped motion curve. The physical meaning of this term is the duration. The greater the compression or stretching, the greater the impact and the higher the cost. This is the weighting coefficient for that item.

[0060] Furthermore, in order to improve the speed and accuracy of the optimization solution, This can be derived based on the kinematic principles of S-shaped acceleration and deceleration curves. For a given stroke D... k Under typical conditions that satisfy the maximum speed and maximum acceleration constraints, its runtime is... and maximum jerk The mathematical relationship between them can be approximated as:

[0061]

[0062] Second item This is the cost item for time deviation. It represents the sum of the nominal working hours for the next H workstations. The physical meaning of this term is that the greater the deviation between the new total working hours and the nominal total working hours, the higher the cost. This is the weighting coefficient for that item.

[0063] It can be seen that the purpose of this function is to find a balance point, which aims to make the movement of each station as smooth as possible, while also hoping that the system will return to the nominal total time trajectory as quickly as possible. This is achieved by adjusting... and The relative size of the system can control the behavioral characteristics of the system.

[0064] Furthermore, to ensure the system is stable with small deviations and agile with large deviations, the aforementioned weighting coefficients are designed to be the current cumulative time deviation. The function.

[0065] for ,

[0066]

[0067] in, It is the basic weight. It is the gain coefficient. The physical meaning of this design is that when the absolute value of the accumulated time deviation... When the deviation is very small, the system tends to remain stable, but when the deviation increases significantly, it tends to remain stable. As the time deviation increases, the optimization objective becomes more focused on eliminating the time deviation as quickly as possible.

[0068] for , set as with They are inversely proportional.

[0069] Figure 2 This illustrates the weighting adjustment mechanism, where the system adjusts the focus of its control strategy as the accumulated time deviation increases, transitioning from pursuing stability to pursuing timeliness and dynamics. In the figure, the upward-sloping line represents... The values ​​that change with the absolute value of the cumulative time deviation are represented by the downward sloping line. The value that varies with the absolute value of the cumulative time deviation.

[0070] Constraints: Total time compensation constraint and dynamic feasibility boundary constraint.

[0071] The total time compensation constraint requires that the sum of the new durations for the next H workstations must exactly absorb the current accumulated time deviation, i.e.:

[0072]

[0073] The dynamic feasibility boundary constraint is that, for any duration to be optimized... Its value must be within a safe range, which is determined by the movement of station k and its maximum speed V. k,max Maximum acceleration A k,max The calculation was limited.

[0074] The look-ahead synchronous controller employs a sequential quadratic programming algorithm or an interior-point method to solve the aforementioned constrained optimization problem online within milliseconds, obtaining a set of optimal target runtimes. .

[0075] S4. Based on the optimal target runtime, generate and issue a new motion curve for the first workstation in the predicted time domain, and use this workstation as the new current workstation to repeat steps S2 to S4.

[0076] The look-ahead synchronous controller, based on the optimization results The first element To generate a new runtime for the first workstation (i.e., workstation i+1) in the prediction time domain, a runtime of... The S-shaped acceleration and deceleration curve is generated, and this new curve is sent to the servo drive unit at workstation i+1 and instructed to start execution.

[0077] The look-ahead synchronization controller can also adjust based on the optimization results. The remaining elements also generate corresponding motion curves for the remaining stations (i.e., stations i+2 to i+H) in the prediction time domain, except for the first station, and preload them as provisional curves into the cache of their respective servo drive units so that they can respond faster on the next trigger.

[0078] Next, set workstation i+1 as the new current workstation and wait for its physical completion event E. i+1 Once this occurs, steps S2 to S4 are executed again in a loop to begin a new round of deviation calculation, forward optimization, and rolling execution.

[0079] Figure 3 The figure shows the curves of motion impact (i.e., jerk) of the servo drive unit generated for deviation compensation in a multi-station collaborative control method based on event triggering and look-ahead synchronization and a traditional rigid synchronization method when the same external disturbance occurs at a certain workstation, as a function of time. In the figure, the dashed line represents the curve of the traditional rigid synchronization method, and the solid line represents the curve of the method in this embodiment.

[0080] It can be seen that when the disturbance occurs, the system using the traditional rigid synchronization method exhibits typical stress-induced compensation behavior. Immediately after t=2ms, the system generates an extremely sharp positive impulse pulse, with its peak instantaneously reaching +20 m / s. 3 Then, to stop the motion, a similarly intense reverse impact pulse is generated at t=2.5ms, with a peak speed of -20 m / s. 3 This forces servo motors to output extremely high acceleration instantaneously, and this impact is the main source of vibration, noise, mechanical wear, and even fatigue fracture of parts in high-speed automated equipment. To avoid these problems, the equipment has to reduce its operating speed, thus limiting production efficiency.

[0081] In contrast, the multi-station collaborative control method based on event triggering and look-ahead synchronization produces a smooth and continuous waveform after detecting a disturbance at t=2ms, with a maximum positive peak impact of only about +6 m / s². 3 The maximum reverse peak value is only about -4 m / s. 3 The peak impact of this embodiment is less than 1 / 3 of that of the traditional method, achieving a significant reduction in motion impact. The root cause of this smooth curve is that the method in this embodiment does not attempt to eliminate all deviations in the next instant, but instead utilizes its predictive time-domain capabilities to unevenly distribute the compensation task to multiple future workstations. One of the objectives of its comprehensive cost function is to minimize the predicted motion impact, which directly results in the final execution impact curve exhibiting a smooth, peak-shaving and valley-filling shape.

[0082] Therefore, this compensation method greatly reduces the impact load on the mechanical transmission, effectively suppresses equipment vibration, and extends the service life of key components. More importantly, because it can efficiently absorb deviations while maintaining stable operation, the equipment can operate stably at a production cycle time much higher than traditional methods, thereby steadily improving production efficiency.

[0083] Embodiments of the present invention also disclose a multi-station collaborative control system based on event triggering and look-ahead synchronization. This multi-station collaborative control system includes multiple sensors disposed on multiple serially associated workstations, multiple servo drive units for driving the multiple serially associated workstations respectively, and a look-ahead synchronization controller electrically connected to the multiple sensors and the multiple servo drive units. The look-ahead synchronization controller is configured to run the multi-station collaborative control method based on event triggering and look-ahead synchronization as described above.

[0084] This article uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. It should be noted that those skilled in the art can make several improvements and modifications to the present invention without departing from the principles of the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

Claims

1. A multi-station collaborative control method based on event triggering and look-ahead synchronization, characterized in that: The multi-station collaborative control method includes the following steps: S1. Define nominal motion parameters for each workstation, wherein the nominal motion parameters include a nominal motion curve and a physical completion event used to characterize the completion of the workstation's action; S2. Monitor the operating status of the current workstation in real time, and when a physical completion event of the current workstation is detected, calculate the cumulative time deviation up to the current workstation. S3. Based on the accumulated time deviation, perform online optimization calculations within the prediction time domain that includes multiple future workstations to determine the optimal target runtime for compensating the accumulated time deviation; wherein, the objective of the online optimization calculation is to minimize the comprehensive cost function formed by the predicted motion impact of all workstations and the total time deviation within the prediction time domain, while satisfying the total time compensation constraint. S4. Based on the optimal target runtime, generate and issue a new motion curve for the first workstation in the predicted time domain, and use this workstation as the new current workstation to repeat steps S2 to S4.

2. The multi-station collaborative control method based on event triggering and look-ahead synchronization according to claim 1, characterized in that: In step S2, a hardware interrupt signal is generated when a physical completion event of the current workstation is detected. The actual completion time of the workstation action is determined by capturing the hardware interrupt signal, and the cumulative time deviation is calculated accordingly.

3. The multi-station collaborative control method based on event triggering and look-ahead synchronization according to claim 1, characterized in that: In step S2, the cumulative time deviation is calculated by adding the new time deviation generated at the current workstation to the cumulative time deviation transmitted from the previous workstation.

4. The multi-station collaborative control method based on event triggering and look-ahead synchronization according to claim 1, characterized in that: In step S3, the predicted motion impact is determined based on a preset function representing the relationship between the target running time and the peak value of the required acceleration of the motion curve.

5. The multi-station collaborative control method based on event triggering and look-ahead synchronization according to claim 1, characterized in that: In step S3, the comprehensive cost function is the sum of the weighted term for the predicted motion impact and the weighted term for the total time deviation, wherein the weight coefficients of the weighted terms are adjusted according to different priority requirements for motion smoothness or deviation compensation speed.

6. The multi-station collaborative control method based on event triggering and look-ahead synchronization according to claim 1, characterized in that: In step S3, the online optimization calculation is also constrained by the dynamic feasibility boundary of each station, so that the generated new motion curve does not exceed the preset maximum speed and maximum acceleration limits.

7. The multi-station collaborative control method based on event triggering and look-ahead synchronization according to claim 1, characterized in that: In step S3, the online optimization calculation is solved using a sequential quadratic programming algorithm or an interior point method.

8. The multi-station collaborative control method based on event triggering and look-ahead synchronization according to claim 1, characterized in that: Step S4 further includes generating new motion curves for the remaining workstations (excluding the first workstation) in the predicted time domain based on the optimal target runtime, and preloading these curves as provisional curves.

9. The multi-station collaborative control method based on event triggering and look-ahead synchronization according to claim 1, characterized in that: In step S4, the motion curve is an S-shaped acceleration / deceleration curve.

10. A multi-station collaborative control system based on event triggering and look-ahead synchronization, characterized in that: The multi-station collaborative control system includes multiple sensors disposed on multiple serially associated workstations, multiple servo drive units for driving the multiple serially associated workstations respectively, and a look-ahead synchronization controller electrically connected to the multiple sensors and the multiple servo drive units. The look-ahead synchronization controller is configured to run a multi-station collaborative control method based on event triggering and look-ahead synchronization as described in any one of claims 1-9.

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