A multi-controller collaborative control method based on an industrial internet platform

Abstract

The application discloses a kind of based on industrial internet platform's multi-controller collaborative control method, it is related to industrial collaborative control technical field, including, to the joint determination of time sequence coincidence degree and communication connectivity of contract feasible corridor, obtain public feasible corridor, when public feasible corridor is established, generate collaborative execution information, when it is not established, carry out shrink and offset update, re-determine contract feasible corridor;According to collaborative execution information and global execution contract window, implement collaborative execution, and in the reserved micro time slot, execute trajectory correction for time delay drift and execution deviation, form update execution state.The application determines local rebinding result based on update execution state and carries out incremental reconstruction, and the adjustment result of controller, channel and micro time slot is linked to write back to global double contract window, forms the contract feasible corridor of continuous update, so that collaborative task maintains the continuity of constraint connection, time sequence coordination and resource allocation in dynamic running process.

Description

Technical Field

[0001] This invention relates to the field of industrial collaborative control technology, and in particular to a multi-controller collaborative control method based on an industrial internet platform. Background Technology

[0002] With the continuous application of industrial internet platforms in discrete manufacturing, process control and edge collaboration, multi-controller collaborative control is gradually evolving from single-point command interaction to a comprehensive control method oriented towards task execution, timing coordination and communication scheduling, by incorporating controller status awareness, channel collaborative allocation and task timing organization into a unified platform for control.

[0003] Existing methods in multi-controller collaboration typically lack a unified organization and dynamic linkage mechanism for execution constraints and communication constraints. This makes it difficult to form a continuous and consistent constraint transmission relationship between controller operating status, channel occupancy status and time slot allocation results. When operational deviations and time delay drift occur, it is difficult to continuously and stably reconstruct the executable collaboration interval. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a multi-controller collaborative control method based on an industrial internet platform to solve the problem of difficulty in unifying and dynamically coordinating execution constraints and communication constraints in multi-controller collaborative control under an industrial internet platform.

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

[0007] This invention provides a multi-controller collaborative control method based on an industrial internet platform, comprising: collecting collaborative description information of multiple controllers, determining the dynamic coupling collaborative relationship between controllers, and constructing a collaborative capability time-series channel map; determining execution constraints and communication constraints based on the collaborative capability time-series channel map, and generating a global execution contract window and a global communication contract window for rolling prediction boundaries, forming a global dual contract window; determining the local execution constraints and local communication constraints of each controller based on the global dual contract window, forming a contractually feasible corridor; jointly determining the temporal overlap degree and communication connectivity of the contractually feasible corridor to obtain a common feasible corridor; generating collaborative execution information when the common feasible corridor is established, and performing contract contracting and offset updates when it is not established, and re-determining the contractually feasible corridor; implementing collaborative execution based on the collaborative execution information and the global execution contract window, and performing trajectory correction for time delay drift and execution deviation within a reserved micro-time slot, forming an updated execution state; determining the local rebinding results of controllers, channels, and micro-time slots based on the updated execution state, the global execution contract window, and the global communication contract window, and performing incremental reconstruction, updating the global dual contract window, and re-determining the contractually feasible corridor, until the collaborative task is completed.

[0008] As a preferred embodiment of the multi-controller collaborative control method based on an industrial internet platform according to the present invention, the specific steps for determining the dynamic coupling and collaborative relationship between controllers are as follows:

[0009] Task collaboration data reflecting the collaboration process between controllers is extracted from the collaboration description information, and then sorted, mapped, recombined and coupled to obtain collaboration association data between controllers.

[0010] Based on the collaborative correlation data, cross-comparison, continuity analysis and dependency merging are performed on the data dependencies, time-series dependencies and channel dependencies among the controllers to obtain the dynamic coupling and collaborative relationship between the controllers.

[0011] As a preferred embodiment of the multi-controller collaborative control method based on an industrial internet platform described in this invention, the specific steps for constructing the collaborative capability time-series channel map are as follows:

[0012] Based on the dynamic coupling and collaboration relationship, obtain the collaborative operation data corresponding to each controller, and perform time alignment, identifier association, category merging and order rearrangement to obtain the collaborative capability time-series channel association data;

[0013] Based on the time-series channel association data of collaborative capabilities, the graph composition data is extracted, and the graph composition data is used to construct nodes, attach edge relationships, and reorganize hierarchical structures to generate a time-series channel graph of collaborative capabilities.

[0014] As a preferred embodiment of the multi-controller collaborative control method based on the industrial internet platform described in this invention, the specific steps for forming a global dual-contract window are as follows:

[0015] Obtain the task time-series data and associated pointing data corresponding to the controller in the collaborative capability time-series channel map, and perform time alignment, association pairing, conflict marking and order rearrangement to obtain the constraint candidate dataset;

[0016] Based on the constraint candidate dataset, dependency merging, sequence relationship sorting and conflict separation are performed on task time-series data and associated pointing data to obtain execution constraint data. In addition, occupancy interval extraction, connectivity relationship sorting and interference separation are performed on transmission time-series data and associated pointing data to obtain communication constraint data.

[0017] Sliding convergence, boundary extrapolation, and interval reorganization are performed on execution constraint data and communication constraint data to generate a global execution contract window and a global communication contract window with rolling prediction boundaries. Corresponding splicing, joint correction, and unified orchestration are then performed to obtain a global dual contract window.

[0018] As a preferred embodiment of the multi-controller collaborative control method based on an industrial internet platform described in this invention, the specific steps for forming a contractually feasible corridor are as follows:

[0019] Obtain the local constraint mapping data corresponding to each controller in the global dual contract window, and perform controller ownership splitting, time interval mapping, constraint boundary transformation and constraint item reorganization to obtain local execution constraint data and local communication constraint data;

[0020] Extract candidate passage data from local execution constraint data and local communication constraint data, and perform interval overlap filtering and continuity integration to obtain candidate passage interval data;

[0021] The candidate passage intervals in the candidate passage interval data are associated, aggregated, and their boundaries are connected to form a contractually feasible corridor.

[0022] As a preferred embodiment of the multi-controller collaborative control method based on the industrial internet platform described in this invention, the specific steps for obtaining the common feasible corridor are as follows:

[0023] Based on the joint decision input data corresponding to the contract feasible corridor, extract the executable interval data and channel reachable interval data corresponding to each controller, and perform time alignment, interval mapping and conflict elimination to obtain joint decision data;

[0024] The joint judgment data is cross-compared and connected to the executable and reachable ranges of each controller to generate a common feasible corridor.

[0025] As a preferred embodiment of the multi-controller collaborative control method based on the industrial internet platform described in this invention, the specific steps for re-determining the contractually feasible corridor are as follows:

[0026] The data on contract feasibility corridors and joint determination are marked with status, correlated and organized, and the results are merged to obtain corridor status data.

[0027] Based on corridor status data, when a public feasible corridor is established, the collaborative orchestration data of corridor-related data is combined and orchestrated to generate collaborative execution information. When a public feasible corridor is not established, the corridor update data of corridor-related data is shrunk and offset to update, and the contractual feasible corridor is re-determined.

[0028] As a preferred embodiment of the multi-controller collaborative control method based on an industrial internet platform according to the present invention, the specific steps for forming and updating the execution state are as follows:

[0029] Extract collaborative execution information and execution-related data from the global execution contract window, and perform time-segment matching, sequence arrangement, and controller association to obtain collaborative execution data;

[0030] Based on collaborative execution data, the execution feedback data corresponding to each controller is obtained, and alignment comparison, deviation identification and drift positioning are performed to obtain time delay drift data and execution deviation data.

[0031] By utilizing latency drift data and execution deviation data, the reserved micro-time slots are reorganized and allocated, and the collaborative execution data is corrected, written, and updated to form an updated execution state.

[0032] As a preferred embodiment of the multi-controller collaborative control method based on the industrial internet platform described in this invention, the controller adjustment results, channel switching results, and micro-time slot migration results are collectively referred to as local rebinding results. The controller adjustment results, channel switching results, and micro-time slot migration results are obtained by corresponding matching, combination rearrangement, and binding conversion of controller occupancy relationships, channel correspondence relationships, and micro-time slot allocation relationships.

[0033] As a preferred embodiment of the multi-controller collaborative control method based on an industrial internet platform described in this invention, the specific steps until the collaborative task is completed are as follows:

[0034] Based on the update execution status, global execution contract window, and global communication contract window, obtain resource usage data, and perform time alignment, status association, and conflict screening to obtain local data to be rebound;

[0035] Extract the rebinding adjustment data of the local data to be rebounded, and perform corresponding matching, combination rearrangement and binding transformation to obtain the local rebinding results and incremental reconstruction data;

[0036] Based on the local rebinding results and incremental reconstruction data, the global execution contract window and the global communication contract window are partially replaced, their boundaries adjusted, and their timing reorganized to obtain the updated global dual contract window. Then, based on the updated global dual contract window, feasible domain mapping, overlap filtering, and result write-back are performed to redetermine the contract feasible corridor until the collaborative task is completed.

[0037] The beneficial effects of this invention are as follows: by determining the local rebinding result based on the updated execution state and performing incremental reconstruction, the adjustment results of the controller, channel and micro-time slot are linked and written back to the global dual contract window, forming a continuously updated contract feasible corridor, so that the collaborative task maintains the continuity of constraint connection, timing coordination and resource allocation during dynamic operation. Attached Figure Description

[0038] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a flowchart of a multi-controller collaborative control method based on an industrial internet platform.

[0040] Figure 2 A flowchart for constructing a time-series channel map of collaborative capabilities.

[0041] Figure 3 This is a flowchart illustrating the formation of the global dual contract window and the contract feasibility corridor.

[0042] Figure 4 A flowchart for collaborative execution and incremental reconfiguration of public feasible corridors. Detailed Implementation

[0043] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0044] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0045] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0046] Reference Figures 1-4 This is one embodiment of the present invention, which provides a multi-controller collaborative control method based on an industrial internet platform, including the following steps:

[0047] S1: Collect collaborative description information from multiple controllers, determine the dynamic coupling and collaborative relationship between controllers, and construct a time-series channel map of collaborative capabilities.

[0048] S1.1: Extract task collaboration data reflecting the collaboration process between controllers from the collaboration description information, and perform time-series sorting, correspondence mapping, association reorganization and coupling aggregation to obtain collaboration association data between controllers.

[0049] Furthermore, task collaboration data reflecting the collaboration process between controllers is extracted from the collaboration description information. The task collaboration data is sorted in time sequence to obtain task collaboration data arranged according to the order of priority. The task collaboration data arranged in time sequence is mapped to obtain task collaboration data that is related between controllers. The task collaboration data that is related between controllers is recombined to obtain task collaboration data that is recombined according to data dependency, time dependency and channel dependency. The task collaboration data that is recombined according to data dependency, time dependency and channel dependency is coupled and aggregated to obtain collaboration association data between controllers.

[0050] S1.2: Based on the collaborative correlation data, cross-compare, perform continuity analysis and dependency merging on the data dependencies, time-series dependencies and channel dependencies among the controllers to obtain the dynamic coupling and collaborative relationship between the controllers.

[0051] Furthermore, the collaborative data are paired up according to the controller identifier to form a set of controller pairs to be analyzed. For each controller pair, the data items output by the preceding controller, the data items received by the following controller, the start and end times of the corresponding task, and the channel occupancy intervals corresponding to message sending and receiving are extracted as dependency identification input data.

[0052] The data items output by the preceding controller are matched with the data items input by the following controller at the field level. When the output data items and input data items meet at least the corresponding relationship in task identifier, data type, source pointer and calling relationship, it is determined that there is a data dependency relationship between the preceding controller and the following controller. For data items that cannot establish a corresponding relationship, they are marked as non-dependent data items and removed from the current dependency chain analysis process.

[0053] The completion time, completion interval, or completion event of the preceding controller task is compared sequentially with the trigger time, start interval, or response event of the following controller task. When the triggering sequence of the following controller is after the completion of the preceding controller, and there are no reverse order conflicts or invalid gaps that disrupt the cooperative chain, a temporal dependency relationship is determined. When there is a time reversal, excessively long breaks, or sequence mismatch caused by the cross insertion of multiple tasks, the corresponding relationship is marked as a temporal discontinuity relationship.

[0054] The message sending interval of the preceding controller and the message receiving interval of the following controller are mapped onto the same channel timing axis. The sending channel, receiving channel and corresponding occupied interval are cross-compared. When the sending interval and the receiving interval correspond to the same reachable channel, and are consecutive in time sequence, consistent in controller correspondence, reachable in channel connection status, and there are no link interruptions, duplicate occupations, connection mismatches and unreachable states in the corresponding interval, it is determined that there is a channel dependency relationship between the preceding controller and the following controller. When the channel interval is broken, overlapped, or fails to connect, it is marked as an invalid channel dependency relationship.

[0055] After identifying data dependencies, time-series dependencies, and channel dependencies, a continuity analysis is performed on various dependencies to determine whether the same controller maintains consistent dependency direction, continuous task delivery chain, and stable channel connection state within adjacent time slices. Dependencies that meet the continuous delivery conditions are retained, while dependencies that are only valid locally and instantaneously but cannot continue into the next collaborative time period are downweighted and eliminated.

[0056] The retained dependencies are merged according to the task chain direction, controller association direction, and time sequence. Data dependencies, time dependencies, and channel dependencies belonging to the same collaborative task path are combined into a unified coupling relationship combination to obtain the dynamic coupling and collaborative relationship between controllers.

[0057] S1.3: Based on the dynamic coupling and coordination relationship, obtain the coordination operation data corresponding to each controller, and perform time alignment, identifier association, category merging and order rearrangement to obtain the coordination capability time-series channel association data.

[0058] Furthermore, based on the dynamic coupling and collaboration relationship, the collaborative operation data corresponding to each controller with data dependency, time dependency and channel dependency is acquired, and then aggregated according to the controller relationship, time relationship and channel relationship corresponding to the dynamic coupling and collaboration relationship. The acquired collaborative operation data is time aligned so that the collaborative operation data forms a corresponding relationship under a unified time series.

[0059] The collaborative operation data that is aligned with the completion time is identified and associated, and a corresponding mapping relationship is formed between the controller identifier, task identifier, and channel identifier.

[0060] The collaborative operation data that has been identified and associated is categorized and merged. The collaborative operation data of the same type are categorized and integrated according to controller, time sequence and channel. The collaborative operation data that has been categorized and merged is rearranged in order. The collaborative operation data is arranged in the order corresponding to the dynamic coupling collaborative relationship to obtain the collaborative capability time sequence channel association data.

[0061] S1.4: Based on the time-series channel association data of collaborative capabilities, extract the graph composition data, construct nodes, attach edge relationships and reorganize the hierarchy of the graph composition data to generate a time-series channel graph of collaborative capabilities.

[0062] Furthermore, controller coordination capability data, timing connection data, and channel connection data are extracted as graph composition data. The graph composition data is then used to construct nodes according to the correspondence between controllers, timing, and channels. Controller coordination capability data is constructed into controller coordination capability nodes, timing connection data is constructed into timing connection nodes, and channel connection data is constructed into channel connection nodes.

[0063] Based on the correspondence between controllers, timing and channels in the collaborative capability timing channel association data, edge relationships are attached to controller collaborative capability nodes, timing connection nodes and channel connection nodes to form the associated edge relationships between controller collaborative capability nodes and timing connection nodes, as well as the associated edge relationships between timing connection nodes and channel connection nodes.

[0064] After the edge relationships are attached, the controller collaborative capability nodes, timing connection nodes, channel connection nodes and corresponding edge relationships are hierarchically reorganized. The hierarchical organization is completed according to the association order of the controller layer, timing layer and channel layer to generate a collaborative capability timing channel map.

[0065] S2: Determine execution constraints and communication constraints based on the collaborative capability time-series channel map, and generate a global execution contract window and a global communication contract window for the rolling prediction boundary, forming a global dual contract window.

[0066] S2.1: Obtain the task time-series data and associated pointing data corresponding to the controller in the collaborative capability time-series channel map, and perform time alignment, association pairing, conflict marking and order rearrangement to obtain the constraint candidate dataset.

[0067] Furthermore, the task start time, task end time, task trigger time, task succession relationship, and channel pointing relationship corresponding to each controller are extracted from the collaborative capability time sequence channel map to form task time sequence data and associated pointing data, respectively.

[0068] Time alignment is performed on the task timing data corresponding to each controller, mapping the start time, end time, and trigger time of tasks on the local time axis of different controllers to a unified global time base, so that the originally scattered task timings between different controllers can form a comparable correspondence on the same time scale.

[0069] Based on the preceding task pointing relationship, subsequent task acceptance relationship, controller correspondence relationship and channel connection relationship recorded in the associated pointing data, the time sequence data of tasks that are related between different controllers are associated and paired to form a task association combination that includes the task initiator, task acceptor, corresponding time period and associated path.

[0070] Conflict marking is performed on task association combinations to identify whether there are overlapping task execution times, contradictory task order, the same task being repeatedly pointed to by multiple paths, or multiple tasks competing for the same controller resources and channel resources. For task association combinations that exist, they are marked as conflict association combinations, and for task association combinations that do not have conflicts, they are marked as valid association combinations.

[0071] After completing the conflict marking, the effective associated units are rearranged according to the order of task execution time, the order of succession of tasks, and the associated pointing path. For task association combinations with conflict marking, the arrangement position is adjusted and the current candidate sequence is removed according to the conflict location and conflict type to form a constraint candidate dataset of execution constraints and communication constraints.

[0072] S2.2: Based on the constraint candidate dataset, the task time-series data and associated pointing data are subjected to dependency merging, sequence relationship sorting and conflict separation to obtain execution constraint data. The transmission time-series data and associated pointing data are subjected to occupancy interval extraction, connectivity relationship sorting and interference separation to obtain communication constraint data.

[0073] Furthermore, the task start time, task end time, task trigger time, task succession relationship, and the association relationship between tasks corresponding to each controller are extracted from the constraint candidate dataset and used as input data for execution constraint analysis.

[0074] Based on the correspondence between preceding and subsequent tasks represented in the association relationship, the time sequence data of tasks that point to the same collaborative task chain and have call, trigger and response associations are classified and merged. The associated tasks that were originally scattered on different controller sides are organized into a continuous organization according to the same execution link, thus completing the dependency merging.

[0075] Within the task set after dependency merging, the execution order of preceding tasks, transitional tasks, and subsequent tasks is sorted out according to the corresponding relationship between the start time, trigger time, and end time of the tasks. The start order, response order, and completion order of each task are clarified to form a task sequence for constraint judgment.

[0076] Conflict identification is performed on the sequence of tasks to determine whether there are overlapping task execution times, reversed order, duplicate targeting of the same task, or multiple tasks competing for the same controller execution resources. For tasks with related content, they are marked as conflicting task items and separated from the continuous execution chain. Tasks with no conflict and clear order are retained to obtain execution constraint data.

[0077] Interference identification is performed on the channel occupancy intervals after the connectivity relationship is sorted out to determine whether there are overlapping channel occupancy times, cross connection paths, link interruptions, duplicate occupancy, and multiple controllers competing for the same channel resources. For channel intervals with interference, they are marked as interference intervals and separated. Channel intervals with continuous links, clear occupancy, and no mutual interference are retained to obtain communication constraint data.

[0078] S2.3: Perform sliding convergence, boundary extrapolation and interval reorganization on execution constraint data and communication constraint data to generate a global execution contract window and a global communication contract window with rolling prediction boundaries, and perform corresponding splicing, joint correction and unified arrangement to obtain a global dual contract window.

[0079] Furthermore, the time intervals corresponding to the execution constraint data and the time intervals corresponding to the communication constraint data are first slid-converged separately. By continuously converging adjacent time intervals and overlapping time intervals, continuous intervals corresponding to the execution constraint data and continuous intervals corresponding to the communication constraint data are formed.

[0080] Next, boundary extrapolation and interval reorganization are performed on the continuous intervals corresponding to the execution constraint data and the continuous intervals corresponding to the communication constraint data, respectively, to generate a global execution contract window and a global communication contract window with rolling prediction boundaries. Then, the global execution contract window and the global communication contract window are spliced ​​together according to the time correspondence, and the interval relationship after splicing is jointly corrected. The boundary misalignment and interval conflict between the global execution contract window and the global communication contract window are adjusted. The globally dual contract window is then uniformly arranged after joint correction.

[0081] Specifically, sliding convergence, boundary extrapolation, and interval reorganization refer to first organizing discrete time intervals into continuously usable windows, then scanning execution constraint intervals and communication constraint intervals segment by segment along a unified time axis with step sizes, merging temporally adjacent, boundary-connected, and overlapping intervals to form continuous intervals. This is then combined with the end time of the preceding task, the expected start time of the subsequent task, the link holding time, and the rolling prediction cycle to appropriately extend the start and end boundaries of the continuous intervals forward and backward. Finally, according to the controller identifier, task chain sequence, channel identifier, and time sequence, the extrapolated intervals are rearranged, merging mergeable intervals, connecting sequential intervals, and splitting and retaining conflicting intervals.

[0082] Corresponding splicing, joint correction, and unified arrangement refer to mapping execution windows and communication windows into a unified sequence. First, based on controller identifiers, task acceptance relationships, correspondence between sender and receiver, and time position relationships, a correspondence is established between execution intervals and communication intervals that can support the execution process. Then, it is checked whether there are misalignments of start and end boundaries, insufficient interval coverage, inconsistent acceptance order, or channel occupation conflicts. Adjustable parts are corrected by moving the boundary inward, expanding the boundary outward, shortening the interval, and extending it locally. Conflicting intervals that cannot be eliminated are split, extended, or moved out. Finally, according to the order of collaborative task advancement, controller participation, and channel call, the corrected execution intervals and communication intervals are sorted as a whole on the same time axis and organized hierarchically to form a global dual-contract window with seamless connection, coordinated boundaries, and consistent resource allocation.

[0083] S3: Determine the local execution constraints and local communication constraints of each controller based on the global dual contract window to form a contract feasible corridor.

[0084] S3.1: Obtain the local constraint mapping data corresponding to each controller in the global dual contract window, and perform controller ownership splitting, time interval mapping, constraint boundary transformation and constraint item reorganization to obtain local execution constraint data and local communication constraint data.

[0085] Furthermore, the execution constraints and communication constraints related to each controller are extracted from the global dual-contract window to form local constraint mapping input data. Based on the controller identifier, task affiliation, and channel association relationship corresponding to each constraint item in the global dual-contract window, the constraint content that was originally in a globally unified orchestration state is split item by item, and each execution constraint and communication constraint is assigned to the corresponding controller name to form a local constraint subset that is independent for each controller, thus completing the controller affiliation split. For constraint items involving the collaborative association of two or more controllers, they are attached separately according to the correspondence between the main execution controller, cooperating controller, and channel association controller, so that the corresponding mapping relationship of the same constraint item is retained on different controller sides.

[0086] Time interval mapping is performed on the time arrangements in the local constraint subsets corresponding to each controller. The global execution time interval and global communication time interval in the global dual contract window are converted according to the start and end time periods, response time periods, and channel usage time periods of the local tasks corresponding to the controller. Each constraint content falls into the local time axis of the corresponding controller, forming the constraint time interval of each controller at the local time scale. For multiple consecutive and overlapping constraint intervals under the same controller, they are arranged and linked in order according to the time sequence and interval coverage relationship.

[0087] Constraint boundaries are transformed for each constraint mapped to the local timeline. Based on the start boundary, end boundary, executable boundary of each controller's local task and the available boundary of the corresponding channel, the start position, end position, and interval coverage of each constraint item in the global dual contract window are locally adjusted to keep the execution constraint boundary consistent with the controller's local execution cycle and the communication constraint boundary consistent with the controller's local channel occupancy range. For constraint items whose boundaries exceed the local task time period and the local channel available time period, the excess part is truncated, shrunk, and the boundary is shifted inward to retain the actual valid local constraint range.

[0088] After completing the constraint boundary transformation, the local constraint content corresponding to each controller is reorganized. The constraint items after controller affiliation splitting, time interval mapping and constraint boundary transformation are classified and organized according to execution side constraints and communication side constraints. Constraint items related to task execution order, execution time period, task acceptance relationship and local execution resource occupation are merged to form local execution constraint data, and constraint items related to message transmission time period, channel occupation relationship, link connection status and local communication resource occupation are merged to form local communication constraint data.

[0089] S3.2: Extract candidate passage data from local execution constraint data and local communication constraint data, and perform interval overlap filtering and continuity integration to obtain candidate passage interval data.

[0090] Furthermore, the executable time period, allowed start and end interval of the task, and available interval of execution resources are extracted from the local execution constraint data corresponding to each controller, and the communicable time period, available interval of the channel, and link maintenance interval are extracted from the local communication constraint data to form candidate passage analysis input data.

[0091] Each execution interval corresponding to the local execution constraint data and each communication interval corresponding to the local communication constraint data are mapped to the local time axis of the same controller. A correspondence is established according to the time start point, end point and interval coverage. The mapped execution interval and communication interval are compared segment by segment to identify the parts that overlap in time. For time periods where the execution interval and communication interval have a common coverage, the common coverage part is retained as a passable candidate interval. Time periods that only meet the execution conditions but not the communication conditions, or only meet the communication conditions but not the execution conditions, are eliminated to complete the interval overlap screening.

[0092] The selected passable candidate intervals are continuously integrated in chronological order. For two consecutive candidate intervals that are arranged consecutively in chronological order, whose time interval between their boundaries does not exceed the continuous connection time range jointly defined by the controller's local control cycle, communication scheduling cycle, task switching buffer time, and reserved micro-time slot length, and whose corresponding controller relationship, task acceptance relationship, and channel reachability relationship are consistent, the two consecutive candidate intervals are merged into a continuous passable interval.

[0093] If the time interval between two consecutive candidate intervals exceeds the continuous connection time range, or if there are changes in the controller correspondence, interruption of task acceptance, changes in channel connectivity status, or inability to continuously connect interval coverage even though the time interval does not exceed the continuous connection time range, it is determined that there is a time break between the consecutive intervals.

[0094] A significant time gap refers to a non-continuous time period between two consecutive candidate intervals that is sufficient to disrupt the continuous passage relationship. This is manifested as the interval between the end of the previous interval and the start of the next interval, which exceeds the allowable connection range for continuous execution of the controller, continuous acceptance of tasks, and continuous accessibility of the channel. Execution conditions and communication conditions cannot be met simultaneously within the interval.

[0095] For candidate intervals with obvious time breaks, the segments are kept independent and not spliced ​​continuously. For multiple continuous passage intervals formed under the same controller, they are rearranged according to interval length, interval position and connection order to form an ordered sequence of candidate passage intervals. After interval overlap screening and continuity integration, candidate passage interval data is obtained.

[0096] S3.3: Connect and aggregate candidate passage intervals from the candidate passage interval data and establish boundaries to form a contractually feasible corridor.

[0097] Furthermore, candidate passageways are associated according to the controller correspondence, task acceptance order, and time sequence. Candidate passageways belonging to the same controller and the same collaborative task chain, with continuous task acceptance and consistent channel reachability, are grouped into the same association group to complete the association aggregation.

[0098] For adjacent candidate passage intervals within the same associated group, boundary connection is performed. If there is only a gap between the termination boundary of the preceding interval and the starting boundary of the following interval that does not affect the continuity of execution and accessibility, the preceding and following intervals are connected to form a continuous interval. If there are gaps between the preceding and following intervals that cannot be continuously connected or cannot maintain accessibility, boundary connection is not performed. After association convergence and boundary connection, the formed continuous intervals are arranged in chronological order to obtain the contract feasible corridor.

[0099] S4: Jointly determine the temporal overlap and communication connectivity of the contractual feasible corridor to obtain the common feasible corridor. When the common feasible corridor is established, generate collaborative execution information; when it is not established, perform shrinkage and offset updates to redetermine the contractual feasible corridor.

[0100] S4.1: Based on the joint decision input data corresponding to the contract feasible corridor, extract the executable interval data and channel reachable interval data corresponding to each controller, and perform time alignment, interval mapping and conflict elimination to obtain joint decision data.

[0101] Furthermore, from the joint decision input data corresponding to the contract feasible corridor, the executable time period, task start and end allowed interval, execution resource available interval, and corresponding channel reachable time period, link maintenance interval, and channel occupancy status interval corresponding to each controller under the current collaborative task are extracted to form joint decision analysis input data. For the executable interval data and channel reachable interval data under the same controller, their controller identifier, task identifier, start time, end time, associated channel identifier, and interval status information are retained as the corresponding basis for joint decision.

[0102] Time alignment is performed on the executable interval data and channel reachable interval data corresponding to each controller. Various interval data from different controllers, different task stages, and different communication links are uniformly mapped to the same collaborative time base. The start time, end time, and duration of each interval are uniformly converted and sorted. The execution activities and channel status corresponding to each controller within the same collaborative cycle are compared on the same time scale. For interval data with local time offset, sampling granularity differences, and inconsistent feedback times, corrections are made according to the unified time base to maintain a comparable state on the same time axis.

[0103] The executable interval data and channel reachable interval data corresponding to each controller are mapped to the time interval corresponding to the contract feasible corridor according to the controller identifier, task succession relationship and execution stage position. At the same time, the corresponding channel reachable intervals are mapped to the corresponding time positions in the same contract feasible corridor according to the sending end controller, receiving end controller and channel connection relationship. The execution side interval and the communication side interval are formed into corresponding interval relationships in the same corridor interval. For task chains involving continuous collaboration of multiple controllers, the executable intervals and channel reachable intervals corresponding to adjacent controllers are sequentially connected according to the succession relationship between the preceding controller and the following controller to form a joint judgment interval correspondence chain.

[0104] The system identifies whether there are time misalignments, interval breaks, boundary inconsistencies, channel interruptions, link mismatches, and resource conflicts that cannot be simultaneously achieved between the executable interval and the channel reachable interval. For intervals with conflicts, the system removes, truncates, and segments them. Only valid corresponding intervals that meet both the controller execution condition and the channel reachable condition within the same time range are retained. For intervals that remain time-continuous, have a clear controller correspondence, and have a valid channel connectivity after conflict removal, they are retained as valid intervals for joint determination, and joint determination data is obtained.

[0105] S4.2: Perform cross-comparison and connectivity filtering on the joint decision data in the executable range and reachable range of each controller to generate a common feasible corridor.

[0106] Furthermore, the effective executable intervals and effective channel reachable intervals corresponding to each controller in the joint judgment data are organized according to controller identifier, task acceptance relationship, channel connection relationship and time sequence to form a judgment correspondence combination of executable intervals and channel reachable intervals. For task chains involving multiple controllers working together, the executable intervals and channel reachable intervals of adjacent controllers should be connected in series according to the task connection relationship between the preceding controller and the following controller to form an interval correspondence chain for the entire process of collaborative tasks, which serves as the basis for the determination of common feasible corridors.

[0107] The executable intervals and channel reachable intervals within the same time range are compared segment by segment to determine whether the controller simultaneously meets the task execution conditions and channel communication conditions within the corresponding time period. If the executable interval and the channel reachable interval have a common overlap in the start time, end time, or interval coverage, the time period covered by the common overlap is extracted as a candidate common interval. If there are only intervals where execution is successful but the channel is unreachable, or where the channel is reachable but the execution conditions are not met, they are determined to be invalid corresponding intervals and are removed. If there is a collaborative relationship between multiple controllers, the execution completion interval of the preceding controller, the execution start interval of the following controller, and the channel reachable interval are compared to see if they form an effective connection within the same collaborative time chain. If no effective connection is formed, the corresponding interval is not included in the candidate common interval.

[0108] Check whether each candidate common interval maintains continuity in time sequence, consistency in controller correspondence, and connectivity without interruption in channel connection status. For candidate common intervals with adjacent interval boundaries, intervals within allowable range, and consistent controller correspondence and channel connectivity status, they are retained and considered as continuously connectable intervals. For candidate common intervals with time breaks, controller connection mismatch, link interruption, channel switching failure, interval jumps, and conflict residues, the corresponding intervals are removed, truncated, or segmented and not treated as continuous common intervals. For multiple continuous candidate common intervals formed under the same controller link, they are combined and organized in chronological order to form an ordered sequence of connected intervals.

[0109] Retain consecutive valid intervals that simultaneously meet the execution overlap condition and communication connectivity condition, and associate and aggregate these consecutive valid intervals according to controller collaboration relationship, task acceptance order and time boundary to generate a common feasible corridor.

[0110] The formula for determining a public feasible corridor is: ; in, This indicates the result of the public feasible corridor determination. = This indicates the generation of publicly feasible corridors. = This indicates that no publicly feasible corridors will be generated. This indicates the result of the timing coincidence determination. It's not the overlap length between the executable interval and the reachable channel interval itself, but rather a judgment value obtained by comprehensively judging the executable interval data and the reachable channel interval data corresponding to each controller after time alignment, interval mapping, and conflict elimination, combined with the coverage of the overlapping interval and the continuous duration required to support the completion of the current collaborative action. When the time sequence overlap meets the collaborative execution requirements and the overlap interval length is sufficient to support the completion of the current collaborative action, it is considered a valid judgment value. = ,otherwise = , This indicates the channel connectivity determination result. When the corresponding channel remains continuously reachable within the overlapping interval, and there are no link interruptions, collisions, or connection mismatches, = ,otherwise = A common feasible corridor is generated only when the timing coincidence determination and the communication connectivity determination are both met.

[0111] It should be noted that when the reachable range data for each controller's channel is filtered to maintain channel connectivity, = When the reachable range data for each controller's corresponding channel contains channel interruptions, range breaks, or residual conflicts after connectivity filtering, = .

[0112] S4.3: Perform status marking, correlation organization, and result merging on the contract feasibility corridor and joint determination data to obtain corridor status data.

[0113] Furthermore, the time intervals in the contract feasible corridor are aligned with the executable interval data and channel reachable interval data in the joint judgment data according to the controller correspondence. Data with overlapping intervals after cross-comparison and channel reachability after connectivity filtering are marked as having a common feasible corridor status. Data with interval separation after cross-comparison and channel reachability not satisfied after connectivity filtering are marked as having a common feasible corridor status.

[0114] Based on the established and non-established states of public feasible corridors, the time interval correspondence, controller correspondence, and channel reachability correspondence between contractual feasible corridors and joint judgment data are correlated and organized. Data with consistent time intervals and correspondences under the same state are merged to obtain corridor status data.

[0115] S4.4: Based on corridor status data, when a public feasible corridor is established, the collaborative orchestration data of the corridor-related data is combined and orchestrated to generate collaborative execution information. When a public feasible corridor is not established, the corridor update data of the corridor-related data is shrunk and offset to update, and the contractual feasible corridor is re-determined.

[0116] Furthermore, when a public feasible corridor is established, collaborative orchestration data is extracted from the corridor association data and combined and orchestrated according to the correspondence between overlapping time period data, controller corresponding data and channel matching data to generate collaborative execution information. When a public feasible corridor is not established, corridor update data is extracted from the corridor association data and processed for shrinkage and offset update according to the correspondence between conflict section data, boundary position data and offset direction data to obtain the updated contractual feasible corridor and redetermine the contractual feasible corridor.

[0117] Specifically, the contraction amount is based on the start and end positions of the conflict segment. Corridor boundaries that overlap with or are affected by the conflict segment and cannot simultaneously meet the execution conditions and channel accessibility conditions are contracted inward until the contracted interval avoids the conflict segment. The offset amount is moved along the time axis of the contracted corridor interval in a direction that still meets the controller execution continuity, task acceptance continuity, and channel connectivity. The updated corridor boundary falls back into the common coverage area of ​​the executable interval and the channel accessibility interval. If there is no space for further offset on one side, it is offset to the other side. If neither side meets the continuous acceptance conditions, the segmented state is retained and the contractual feasible corridor is re-determined.

[0118] S5: Implement collaborative execution based on collaborative execution information and the global execution contract window, and perform trajectory correction for time delay drift and execution deviation within the reserved micro-slots to form an updated execution status.

[0119] S5.1: Extract collaborative execution information and execution-related data from the global execution contract window, and perform time period matching, sequence arrangement, and controller association to obtain collaborative execution data.

[0120] Furthermore, overlapping time period data, controller corresponding data, and channel matching data are extracted from the collaborative execution information. Execution time interval data corresponding to each controller is extracted from the global execution contract window. The overlapping time period data, controller corresponding data, channel matching data, and execution time interval data are then correlated and organized to obtain execution-related data.

[0121] The execution time intervals corresponding to each controller in the execution association data are matched by time periods to determine the execution time periods corresponding to each controller in the common feasible corridor. The execution time periods of each controller that have completed time period matching are arranged in order according to the execution sequence to form the time sequence arrangement result corresponding to each controller. Then, the time sequence arrangement result is associated with the corresponding data of the controller to form the correspondence between each controller and the execution time interval, and the collaborative execution data is obtained.

[0122] S5.2: Based on the collaborative execution data, obtain the execution feedback data corresponding to each controller, perform alignment comparison, deviation identification and drift positioning, and obtain delay drift data and execution deviation data.

[0123] Furthermore, based on the task arrangement information, execution timing information, resource allocation information, and controller association relationships corresponding to each controller in the collaborative execution data, the execution feedback data generated by each controller during the actual execution process is extracted, and a correspondence is established between the execution feedback data and the execution interval and task arrangement content in the collaborative execution data to form the execution feedback analysis input data.

[0124] The actual start time, actual end time, and feedback occurrence time in the execution feedback data are mapped to the predetermined execution time axis corresponding to the collaborative execution data. The actual execution process of each controller is made comparable under the same time reference. According to the controller identifier, task identifier, execution stage, and resource correspondence, the actual execution feedback is matched with the predetermined execution arrangement item by item. The consistency between the actual execution time period and the predetermined execution time period, the consistency between the actual task progress order and the predetermined task arrangement order, and the consistency between the actual resource occupation and the resource allocation are compared. For data items with missing feedback, misaligned time, or unclear correspondence, they are supplemented, corrected, and marked as items to be verified according to the controller association relationship.

[0125] Based on the differences between the actual execution results and the planned execution results, identify whether there are deviations in task initiation, task termination, execution order, action completion, and resource usage. For the parts where there are inconsistencies between the actual execution results and the planned execution results in terms of execution content, execution order, completion status, and resource usage status, mark them as execution deviation items and record the corresponding controller identifier, task identifier, deviation occurrence range, and deviation type. For the parts where the actual execution results are consistent with the planned execution results, mark them as normal execution items and retain them.

[0126] The actual feedback time position in the execution feedback data is compared with the start boundary, end boundary, and intermediate timing nodes of the predetermined execution interval in the collaborative execution data to determine the position and magnitude of whether the actual execution occurs earlier or later than the predetermined execution, and the duration of the shift. If the actual feedback time lags behind the predetermined execution position, it is identified as a time delay shift; if the actual feedback time is earlier than the predetermined execution position, it is identified as an early shift; if the actual execution duration exceeds or is shorter than the predetermined execution interval, it is identified as an interval shift. The time position of the shift, the corresponding controller, the corresponding task, and the shift amount are recorded. After alignment comparison, deviation identification, and shift location, time delay shift data and execution deviation data are obtained.

[0127] S5.3: Utilize delay drift data and execution deviation data to reorganize and allocate reserved micro-time slots, and correct, write, and update the status of collaborative execution data to form an updated execution status.

[0128] Furthermore, the drift positions corresponding to the latency drift data and the deviation positions corresponding to the execution deviation data are compared with the execution timing data, controller task data, and resource allocation data in the collaborative execution data to determine the execution intervals where latency drift and execution deviation occur. Then, the execution intervals where latency drift and execution deviation occur are mapped to the time intervals corresponding to the reserved micro-time slots, and the reserved micro-time slots corresponding to each execution interval are determined. The reserved micro-time slots are reorganized and allocated, and each reserved micro-time slot is respectively assigned to the execution intervals where latency drift and execution deviation occur. After the reorganization and allocation are completed, the correction content corresponding to the latency drift data and execution deviation data is written into the corresponding execution timing data, controller task data, and resource allocation data in the collaborative execution data. The time period matching, sequence arrangement, and controller association information in the collaborative execution data are updated to form an updated execution state.

[0129] S6: Determine the local rebinding results of controllers, channels, and micro-time slots based on the updated execution status, global execution contract window, and global communication contract window, and perform incremental reconstruction, update the global dual contract window, and redetermine the contract feasible corridor until the collaborative task is completed.

[0130] S6.1: The controller adjustment results, channel switching results, and micro-timeslot migration results are collectively referred to as local rebinding results. The controller adjustment results, channel switching results, and micro-timeslot migration results are obtained by matching, rearranging, and converting the controller occupancy relationship, channel correspondence relationship, and micro-timeslot allocation relationship.

[0131] Based on the update execution status, global execution contract window, and global communication contract window, resource usage data is obtained, and time alignment, status association, and conflict screening are performed to obtain local data to be rebound.

[0132] Furthermore, controller usage data, channel usage data, and micro-timeslot usage data are extracted from the updated execution status to form resource usage data. The resource usage data is then time-aligned with the execution time interval in the global execution contract window and the communication time interval in the global communication contract window to determine the time interval positions corresponding to the controller usage data, channel usage data, and micro-timeslot usage data, respectively.

[0133] After time alignment is completed, the controller occupancy data is associated with the corresponding execution time interval, and the channel occupancy data and micro-timeslot usage data are associated with the corresponding communication time interval to obtain the corresponding occupancy relationship of controller, channel and micro-timeslot in each time interval. Then, the corresponding occupancy relationship in each time interval is screened for conflicts. The controller occupancy data, channel occupancy data and micro-timeslot usage data with overlapping occupancy, misaligned occupancy and inconsistent association are filtered out and merged to obtain local data to be rebound.

[0134] S6.2: Extract the rebinding adjustment data of the local data to be rebounded, and perform corresponding matching, combination rearrangement and binding transformation to obtain the local rebinding results and incremental reconstruction data.

[0135] Furthermore, based on the local rebinding data, controller adjustment data, channel switching data, and micro-timeslot migration data are extracted to form rebinding adjustment data. The rebinding adjustment data is matched accordingly, and the controller adjustment data and channel switching data are aligned by time and associated by state to determine the correspondence. Then, the micro-timeslot migration data is matched with the controller adjustment data and channel switching data according to the conflict position determined by conflict screening.

[0136] After completing the matching, the controller adjustment data, channel switching data, and micro-timeslot migration data are combined and rearranged according to their time sequence, conflict location, and switching order. After the combination and rearrangement is completed, the rearranged controller adjustment data, channel switching data, and micro-timeslot migration data are bound and transformed. The controller occupancy relationship, channel correspondence relationship, and micro-timeslot allocation relationship are converted into controller adjustment results, channel switching results, and micro-timeslot migration results, respectively, to obtain local rebinding results. Incremental reconstruction data is then formed based on the time location, interval boundary, and relationship changes corresponding to the local rebinding results.

[0137] Specifically, the local rebinding result refers to the controller re-occupancy arrangement, channel reconnection arrangement, and micro-timeslot reallocation arrangement formed after corresponding matching, combination rearrangement, and binding transformation for controller occupancy relationships, channel correspondence relationships, and micro-timeslot allocation relationships that exist in the local rebinding data and have overlapping occupancy, misaligned occupancy, and inconsistent association.

[0138] S6.3: Based on the local rebinding results and incremental reconstruction data, perform local replacement, boundary adjustment and timing reorganization on the global execution contract window and the global communication contract window to obtain the updated global dual contract window. Then, based on the updated global dual contract window, perform feasible domain mapping, overlap filtering and result write-back to redetermine the contract feasible corridor until the collaborative task is completed.

[0139] Furthermore, based on the local rebinding results and incremental reconstruction data, the execution intervals in the global execution contract window affected by the controller adjustment results are partially replaced, and the communication intervals in the global communication contract window affected by the channel switching results and micro-timeslot migration results are partially replaced. In combination with the position changes corresponding to the controller adjustment results, channel switching results, and micro-timeslot migration results, the execution boundary is adjusted and the timing is reassembled to obtain the updated global dual contract window.

[0140] Based on the updated global dual contract window, feasible domain mapping is performed. The time intervals and channel intervals corresponding to the updated global execution contract window and the updated global communication contract window are mapped to traversable intervals. Then, the traversable intervals are filtered for overlap, and the traversable intervals that meet the overlap relationship are retained. The traversable intervals are then written back to the corresponding intervals of the updated global dual contract window to redetermine the contract feasible corridor. If the contract feasible corridor has not completed the collaborative task, the process of local replacement, boundary adjustment, time sequence reorganization, feasible domain mapping, overlap filtering, and result writing back continues to be repeated based on the updated execution status, global execution contract window, and global communication contract window until the collaborative task is completed.

[0141] The formula for determining the update result of local rebinding is: ; in, This indicates that the global dual contract window update judgment result is being performed. This indicates the number of controller conflicts in the controller adjustment results. This indicates the number of overlapping or interfering channel connections in the channel switching results. This indicates the number of micro-slot allocation misalignments in the micro-slot migration results; when , and When the sum equals zero, a global dual-contract window update is performed. , and If the sum is greater than zero, it is determined that the global dual-contract window update will not be executed. = This indicates that the local rebinding results and incremental reconstruction data meet the conditions for updating the global dual contract window. = This indicates that the results of local rebinding and incremental reconstruction do not meet the conditions for updating the global dual contract window.

[0142] For example, on an assembly line managed by an industrial internet platform, controller A is responsible for material loading, controller B for material handling, and controller C for assembly. Initially, the industrial internet platform has already formed a global execution contract window and a global communication contract window based on the collaborative relationship between controllers A, B, and C, and combined them into a global dual contract window.

[0143] During collaborative execution, the handling action corresponding to controller B is delayed, resulting in an updated execution state. This causes a misalignment between the original execution time interval of controller B and the original assembly time interval of controller C. At the same time, the channel interval corresponding to the handling completion information sent by controller B to controller C overlaps with the communication intervals occupied by other controllers. The originally allocated micro-time slots can no longer meet the current communication arrangements. The contractual feasible corridor is re-determined. When the re-determined contractual feasible corridor still cannot guarantee that controllers A, B, and C can continuously complete the loading, handling, and assembly, the process of local replacement, boundary adjustment, timing reorganization, feasible domain mapping, overlap screening, and result write-back continues until the collaborative task is completed.

[0144] Feasible domain mapping refers to mapping the execution time interval in the updated global execution contract window to an execution feasible interval according to the controller correspondence, task acceptance order, and time boundary, and mapping the communication time interval in the updated global communication contract window to a communication feasible interval according to the correspondence between the sender and receiver, channel connection relationship, and time boundary, thus forming a correspondence between the execution side interval and the communication side interval on the same collaborative time axis.

[0145] Overlap filtering retains intervals that overlap in time range, maintain continuity in controller connection, remain reachable in channel connectivity, and do not have resource conflicts, while eliminating intervals that only meet execution conditions but not communication conditions, only meet communication conditions but not execution conditions, and intervals that overlap in time but cannot maintain continuity in connection and reachability in the link.

[0146] Result writeback refers to writing the valid overlapping intervals retained after filtering, along with their corresponding controller relationships, channel relationships, and time boundaries, back to the corresponding positions in the updated global execution contract window and global communication contract window.

[0147] In summary, this invention determines the local rebinding result based on the updated execution state and performs incremental reconstruction, and writes back the adjustment results of the controller, channel and micro-time slot to the global dual contract window in a linked manner, forming a continuously updated contract feasible corridor, so that the collaborative task maintains the continuity of constraint connection, timing coordination and resource allocation during dynamic operation.

[0148] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A multi-controller collaborative control method based on an industrial internet platform, characterized in that, include: Collect collaborative description information from multiple controllers, determine the dynamic coupling and collaborative relationship between controllers, and construct a time-series channel map of collaborative capabilities; Based on the collaborative capability time-series channel map, execution constraints and communication constraints are determined, and global execution contract windows and global communication contract windows for rolling prediction boundaries are generated, forming a global dual contract window; Based on the global dual contract window, the local execution constraints and local communication constraints of each controller are determined to form a contract feasible corridor; The contract feasible corridor is jointly determined by the temporal overlap and communication connectivity to obtain the public feasible corridor. When the public feasible corridor is established, collaborative execution information is generated. When it is not established, shrinkage and offset updates are performed to redetermine the contract feasible corridor. Collaborative execution is carried out based on collaborative execution information and the global execution contract window, and trajectory correction for time delay drift and execution deviation is performed within the reserved micro-time slots to form an updated execution status; Based on the updated execution status, the global execution contract window, and the global communication contract window, determine the local rebinding results of the controller, channel, and micro-time slot, perform incremental reconstruction, update the global dual contract window, and redetermine the contract feasible corridor until the collaborative task is completed.

2. The multi-controller collaborative control method based on an industrial internet platform as described in claim 1, characterized in that, The specific steps for determining the dynamic coupling and coordination relationship between controllers are as follows: Task collaboration data reflecting the collaboration process between controllers is extracted from the collaboration description information, and then sorted, mapped, recombined and coupled to obtain collaboration association data between controllers. Based on the collaborative correlation data, cross-comparison, continuity analysis and dependency merging are performed on the data dependencies, time-series dependencies and channel dependencies among the controllers to obtain the dynamic coupling and collaborative relationship between the controllers.

3. The multi-controller collaborative control method based on an industrial internet platform as described in claim 2, characterized in that, The specific steps for constructing the collaborative capability time-series channel map are as follows: Based on the dynamic coupling and collaboration relationship, obtain the collaborative operation data corresponding to each controller, and perform time alignment, identifier association, category merging and order rearrangement to obtain the collaborative capability time-series channel association data; Based on the time-series channel association data of collaborative capabilities, the graph composition data is extracted, and the graph composition data is used to construct nodes, attach edge relationships, and reorganize hierarchical structures to generate a time-series channel graph of collaborative capabilities.

4. The multi-controller collaborative control method based on an industrial internet platform as described in claim 1, characterized in that, The specific steps for forming a global dual-contract window are as follows: Obtain the task time-series data and associated pointing data corresponding to the controller in the collaborative capability time-series channel map, and perform time alignment, association pairing, conflict marking and order rearrangement to obtain the constraint candidate dataset; Based on the constraint candidate dataset, dependency merging, sequence relationship sorting and conflict separation are performed on task time-series data and associated pointing data to obtain execution constraint data. In addition, occupancy interval extraction, connectivity relationship sorting and interference separation are performed on transmission time-series data and associated pointing data to obtain communication constraint data. Sliding convergence, boundary extrapolation, and interval reorganization are performed on execution constraint data and communication constraint data to generate a global execution contract window and a global communication contract window with rolling prediction boundaries. Corresponding splicing, joint correction, and unified orchestration are then performed to obtain a global dual contract window.

5. The multi-controller collaborative control method based on an industrial internet platform as described in claim 4, characterized in that, The specific steps for forming a feasible contract corridor are as follows: Obtain the local constraint mapping data corresponding to each controller in the global dual contract window, and perform controller ownership splitting, time interval mapping, constraint boundary transformation and constraint item reorganization to obtain local execution constraint data and local communication constraint data; Extract candidate passage data from local execution constraint data and local communication constraint data, and perform interval overlap filtering and continuity integration to obtain candidate passage interval data; The candidate passage intervals in the candidate passage interval data are associated, aggregated, and their boundaries are connected to form a contractually feasible corridor.

6. The multi-controller collaborative control method based on an industrial internet platform as described in claim 1, characterized in that, The specific steps to obtain a publicly feasible corridor are as follows: Based on the joint decision input data corresponding to the contract feasible corridor, extract the executable interval data and channel reachable interval data corresponding to each controller, and perform time alignment, interval mapping and conflict elimination to obtain joint decision data; The joint judgment data is cross-compared and connected to the executable and reachable ranges of each controller to generate a common feasible corridor.

7. The multi-controller collaborative control method based on an industrial internet platform as described in claim 6, characterized in that, The specific steps for redetermining the contractually feasible corridor are as follows: The data on contract feasibility corridors and joint determination are marked with status, correlated and organized, and the results are merged to obtain corridor status data. Based on corridor status data, when a public feasible corridor is established, the collaborative orchestration data of corridor-related data is combined and orchestrated to generate collaborative execution information. When a public feasible corridor is not established, the corridor update data of corridor-related data is shrunk and offset to update, and the contractual feasible corridor is re-determined.

8. The multi-controller collaborative control method based on an industrial internet platform as described in claim 1, characterized in that, The specific steps to establish the update execution state are as follows: Extract collaborative execution information and execution-related data from the global execution contract window, and perform time-segment matching, sequence arrangement, and controller association to obtain collaborative execution data; Based on collaborative execution data, the execution feedback data corresponding to each controller is obtained, and alignment comparison, deviation identification and drift positioning are performed to obtain time delay drift data and execution deviation data. By utilizing latency drift data and execution deviation data, the reserved micro-time slots are reorganized and allocated, and the collaborative execution data is corrected, written, and updated to form an updated execution state.

9. The multi-controller collaborative control method based on an industrial internet platform as described in claim 1, characterized in that, The controller adjustment results, channel switching results, and micro-timeslot migration results are collectively referred to as local rebinding results. The controller adjustment results, channel switching results, and micro-timeslot migration results are obtained by matching, rearranging, and converting the controller occupancy relationship, channel correspondence relationship, and micro-timeslot allocation relationship.

10. The multi-controller collaborative control method based on an industrial internet platform as described in claim 9, characterized in that, The specific steps until the collaborative task is completed are as follows: Based on the update execution status, global execution contract window, and global communication contract window, obtain resource usage data, and perform time alignment, status association, and conflict screening to obtain local data to be rebound; Extract the rebinding adjustment data of the local data to be rebounded, and perform corresponding matching, combination rearrangement and binding transformation to obtain the local rebinding results and incremental reconstruction data; Based on the local rebinding results and incremental reconstruction data, the global execution contract window and the global communication contract window are partially replaced, their boundaries adjusted, and their timing reorganized to obtain the updated global dual contract window. Then, based on the updated global dual contract window, feasible domain mapping, overlap filtering, and result write-back are performed to redetermine the contract feasible corridor until the collaborative task is completed.

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