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CN-121995774-A - Automatic cooperative adjustment system for discrete manufacturing production process

CN121995774ACN 121995774 ACN121995774 ACN 121995774ACN-121995774-A

Abstract

The invention relates to the technical field of discrete manufacturing production flow control and discloses an automatic collaborative adjustment system of the discrete manufacturing production flow, which comprises node control units and collaborative control resolving units distributed at process nodes, wherein the collaborative control resolving units convert node operation beats into time axis distribution parameters in a time sequence logic association model, calculate target adjustment vectors based on the parameters, and superimpose compensation pulses on the output front edge of the target adjustment vectors by utilizing a feedforward shaping mechanism to enable adjustment signals to break through a physical execution dead zone of a bottom layer driving execution unit.

Inventors

  • ZHENG XINHUA
  • HUANG QIANG
  • CHEN XING

Assignees

  • 浙江兴达讯软件股份有限公司

Dates

Publication Date
20260508
Application Date
20260409

Claims (10)

  1. 1. An automated collaborative adjustment system for discrete manufacturing production processes, comprising: the system comprises a plurality of groups of node control units and cooperative control resolving units, wherein the node control units and the cooperative control resolving units are distributed at process nodes; the node control unit is used for collecting physical state data of the corresponding process node; The cooperative control resolving unit is used for converting the operation beats of all process nodes into time axis distribution parameters in the time sequence logic association model, and executing the following steps of S101, calculating a synchronous deviation energy function of the time sequence logic association model based on the time axis distribution parameters, extracting time sequence logic interference quantity among the process nodes, S102, calling the length of a logic queue to be processed corresponding to the process nodes, setting a dynamic constraint boundary of the process beats, resolving optimal time axis distribution characteristics with the minimum synchronous deviation energy function as a target to generate a target adjusting vector, S103, calling a dead zone feedforward shaping sub-module, acquiring a static start energy threshold of a bottom driving executing unit, carrying out waveform shaping on the target adjusting vector according to the static start energy threshold, enabling the energy integral of a issued adjusting signal on the time axis to meet the resistance overcoming requirement of a bottom driving executing unit through superposition of compensation pulses at the output front edge of the target adjusting vector, enabling transient power generated by an adjusting system to break through the physical execution dead zone of the bottom driving executing unit, and sending the shaped target adjusting vector to the corresponding node control unit by the cooperative control resolving unit.
  2. 2. The automated collaborative adjustment system of discrete manufacturing process according to claim 1, wherein the collaborative control solution unit defines a logical coupling relationship of process nodes as node transfer weights in a temporal logical association model when executing step S101, and extracts structural feature values of the temporal logical association model using a laplace operator to determine a system out-of-step risk that characterizes a synchronization bias energy function.
  3. 3. The automated collaborative adjustment system of a discrete manufacturing process according to claim 1, wherein the collaborative control solution unit uses a length of the logic queue to be processed as a proportional gain factor for a dynamic constraint boundary when executing step S102, and contracts an adjustment tolerance window of a process beat to inhibit cascading transfer of the sequential logic interferometry within the sequential logic correlation model when the length of the logic queue to be processed exceeds a preset stacking threshold.
  4. 4. The automated collaborative adjustment system of a discrete manufacturing process according to claim 1, wherein the collaborative control solution unit, when executing step S102, searches for adjustment paths within dynamic constraint boundaries that converge the synchronous deviation energy function using a gradient descent algorithm and converts a time axis stretch of a temporal logic correlation model to a frequency control parameter in a target adjustment vector.
  5. 5. The automated collaborative adjustment system of discrete manufacturing process according to claim 1, wherein the dead zone feedforward shaping sub-module calculates the shaped output signal amplitude The following rules are followed: , wherein, For the amplitude of the shaped output signal, The original magnitude of the vector is adjusted for the target, For a feedforward compensation amplitude determined based on a static start energy threshold.
  6. 6. The automated collaborative adjustment system of discrete manufacturing process according to claim 1, wherein the dead zone feedforward shaping submodule performs an energy conservation constraint to synchronously reduce a duty cycle of the target adjustment vector during a single adjustment cycle while increasing the feedforward compensation magnitude to maintain a constant overall power consumption of a single adjustment event.
  7. 7. The automated collaborative adjustment system of a discrete manufacturing process according to claim 1, wherein the collaborative control solution unit defines a time-dependent change in amplitude of the compensation pulse using an exponential decay law when performing waveform shaping, so that the compensation pulse smoothly reverts to an original level of the target adjustment vector after instantaneously breaking through a physical execution dead zone.
  8. 8. The automated collaborative adjustment system of a discrete manufacturing process according to claim 1, wherein the collaborative control resolution unit is configured to monitor a rate of change of a temporal logic interferometry, wherein when the rate of change exceeds a predetermined slope threshold within 10ms, performing an advance compensation adjustment of a logic latency of a downstream process node by a dynamic constraint boundary.
  9. 9. The automated collaborative adjustment system of discrete manufacturing process according to claim 1 wherein the floor drive actuator comprises a conveyor drive motor and an assembly actuator, wherein the static start energy threshold is stored in a memory of the dead zone feed forward shaping sub-module and is modified based on a degree of deviation of the operating frequency of the floor drive actuator from 50Hz to 60 Hz.
  10. 10. The automated collaborative adjustment system of a discrete manufacturing process of claim 1, wherein the collaborative control resolution unit further comprises a system stability evaluation module configured to reconstruct a logical connection path of the temporal logic correlation model to isolate process nodes that generate the temporal logic interferometry when the synchronization bias energy function exceeds a predetermined safety threshold.

Description

Automatic cooperative adjustment system for discrete manufacturing production process Technical Field The invention relates to an automatic cooperative regulation system for a production flow of a discrete manufacturing industry, and belongs to the technical field of production flow control of the discrete manufacturing industry. Background The current discrete manufacturing production process is composed of a plurality of process nodes which are mutually related, each process node usually operates independently according to a preset beat, materials and information flow among the nodes according to a fixed time sequence to form a production link, the control mode is established on the basis that each process node strictly follows a predefined process blueprint, in an actual working condition, control logic of a single process node only pays attention to local parameter feedback, matches own physical parameters with a static process threshold value, is difficult to perceive global state evolution of a production chain, when an upstream node generates random disturbance, a downstream node is limited by an isolated control domain, cannot learn upstream state deviation, the static and non-cooperative control logic enables tiny time sequence deviation to generate cascade amplification among the nodes, finally triggers pipeline shutdown or material blockage, and conventional improvement thinking absorbs disturbance by adding a physical buffer area or reducing global reference beat. Further analysis shows that the core contradiction faced by the prior art is that impedance mismatch exists between an ideal control signal in a mathematical layer and a bottom mechanical executing mechanism, when a control system outputs an adjusting instruction aiming at micro disturbance, a driving device generates execution retardation due to static friction dead zone and electromagnetic inertia hysteresis, so that the adjusting instruction is lost in a physical conversion process; although the industry attempts to improve the information transmission speed by introducing a high-speed communication network, the method is limited by the industrial inertia of separation of design and execution, a control system still cannot directly converge physical disturbance into a parameter frame of an information processing space, the limitation of design philosophy makes real-time opposite impact of a bottom layer physical shock difficult to be obtained in a logic dimension, so that the system presents stability deficiency when facing complex working conditions, the Chinese patent application with publication number CN117875664A discloses a multi-task sequence collaborative automation control method and device, a quality characteristic parameter relation model is constructed, a target optimization model is utilized to adjust a time dimension sequence of a manufacturing process, the technical scheme essentially belongs to macroscopic logic dimension scheduling optimization, the technology is established on the premise that a bottom layer executing mechanism completely reproduces a logic instruction in a lossless manner, in the real working conditions of discrete manufacturing industry, a bottom layer driving unit such as a conveyor motor and an assembly executing mechanism generally has dead zone of static friction force and electromagnetic induction lag, the prior art only screens in a data space sequence, ignores dynamic impedance difference between an ideal mathematical control law and a rough physical executing mechanism, instruction energy cannot penetrate physical execution, the optimal solution is caused to occur in a physical execution, the real-time response of the control instruction and the real-time opposite impact of the physical shock is difficult to be carried out on the bottom layer real-time opposite impact characteristics of physical shock in a real-time, timing dead zones cannot be eliminated, and full-line systematic logic deadlock is easily induced due to feedback distortion. Therefore, how to construct a cross-node dynamic cooperative adjustment mechanism, under the working condition limited by the mechanical characteristics of a physical execution mechanism, eliminates a time sequence logic dead zone between working procedures, and inhibits cascade amplification of time sequence deviation becomes the technical problem to be solved by the invention. Disclosure of Invention In order to solve the problems in the background technology, the technical scheme of the invention is as follows, an automatic collaborative adjustment system of a discrete manufacturing production process comprises: the system comprises a plurality of groups of node control units and cooperative control resolving units, wherein the node control units and the cooperative control resolving units are distributed at process nodes; the node control unit is used for collecting physical state data of the corresponding process node; The cooperative control reso