Heterogeneous equipment intelligent scheduling and control method based on cloud edge collaboration

Abstract

The invention discloses an intelligent scheduling and control method for heterogeneous equipment based on cloud edge collaboration. The method comprises the following steps: S1, constructing a multi-stage redundancy control architecture and generating edge control topological structure description; s2, deploying a software-defined CPE (Customer Premise Equipment) component and loading a communication protocol template library; s3, identifying communication protocols and link states, and generating a communication protocol mapping relation table and a communication topological structure chart; s4, collecting state data of the PLC and the I / O module, and establishing a state synchronous cache; s5, executing a master control scheduling strategy and performing state mirror image synchronization to generate a master control state mapping table and a switching judgment result; s6, executing an I / O redundant channel selection and arbitration mechanism, and generating a signal channel mapping table and a control strategy; and S7, calling the CPE component to complete link lossless switching and outputting reconstruction configuration. The method has the advantages of being high in control reliability, high in protocol compatibility, flexible in link switching and the like.

Description

Technical Field

[0001] This invention relates to the field of edge computing and edge intelligence, and in particular to a method for intelligent scheduling and control of heterogeneous devices based on cloud-edge collaboration. Background Technology

[0002] In current industrial automation systems, multi-PLC architectures are widely used for control and assurance of critical tasks. However, traditional PLC master-slave switching mechanisms rely heavily on hardware redundancy modules. The switching process is complex and costly, and often experiences response delays or control interruptions during the switching process, failing to meet high real-time requirements.

[0003] Meanwhile, existing systems generally have weak fault tolerance for I / O modules. When a signal channel fails, manual switching is required, resulting in long average repair times and potential production line shutdowns or on-site interventions. Furthermore, there is a lack of automated and adaptive signal arbitration mechanisms.

[0004] At the communication level, in a network environment where heterogeneous PLCs and various I / O devices coexist, the communication protocols between different devices are inconsistent. Most existing technologies rely on static configuration, with fixed protocol stacks that lack dynamic loading and switching capabilities. This results in communication links being unable to be reconstructed in a timely manner when failures or protocol conflicts occur, seriously affecting the continuity and stability of the control system.

[0005] Other problems include the fact that traditional industrial control solutions are mainly based on central control and lack edge computing capabilities, making it difficult to achieve local rapid response and distributed intelligent collaboration. This is particularly prominent in key areas such as multi-device redundant control, state synchronization and link switching, becoming a technical bottleneck for system upgrades.

[0006] Therefore, how to provide intelligent scheduling and control methods for heterogeneous devices based on cloud-edge collaboration is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0007] One objective of this invention is to propose an intelligent scheduling and control method for heterogeneous devices based on cloud-edge collaboration. By utilizing an edge computing architecture and software-defined communication mechanism, a multi-level redundant PLC control system, dynamic protocol identification and link reconstruction mechanism are constructed to achieve intelligent access and highly reliable scheduling of heterogeneous industrial devices. This method has the advantages of fast response speed, strong communication self-adaptation capability and high fault self-healing capability.

[0008] The intelligent scheduling and control method for heterogeneous devices based on cloud-edge collaboration according to an embodiment of the present invention includes the following steps:

[0009] S1. Construct a multi-level redundant control architecture consisting of multiple physical PLCs, shadow PLCs and cloud virtual PLCs, configure the unique identifier, control object, communication interface and associated I / O module information of each PLC, and generate a description of the edge control topology of the multi-PLC system.

[0010] S2. Based on the edge control topology description, deploy software-defined CPE components in the edge computing nodes, initialize the dynamic protocol stack management module, load communication protocol templates supporting ModbusTCP, Profinet and EtherCAT, and generate a protocol template library.

[0011] S3. Based on the PLC and I / O module mapping information and protocol template library, identify the current communication protocol type and link status of heterogeneous devices, and construct a communication protocol mapping table and an initial communication topology diagram.

[0012] S4. Based on the communication topology diagram, collect the input and output status, link connection status and communication quality indicators of each PLC and I / O module, upload them to the edge computing node, generate a multi-device operation status dataset, merge and establish a status synchronization cache;

[0013] S5. Based on state synchronization cache, execute the PLC master-slave control scheduling strategy, use the state mirroring mechanism to synchronize the state of the master PLC to the shadow PLC and the cloud PLC in real time, and generate the master control state mapping table and the current master control switching judgment result.

[0014] S6. Based on the master control switching judgment result and the equipment operation status data set, execute the redundant channel selection and signal path arbitration mechanism of the I / O module, and generate the I / O module signal channel mapping table and arbitration control strategy;

[0015] S7. Based on the signal channel mapping table and arbitration control strategy, combined with the communication protocol mapping table, the software-defined CPE component is called to dynamically adjust the communication link port and IP binding relationship, realize lossless switching of communication links, and output the link reconstruction configuration result.

[0016] Optionally, step S1 specifically includes:

[0017] S11. Obtain the hardware configuration list of multiple physical PLC devices, shadow PLC devices and cloud virtual PLCs involved in the heterogeneous control system, including the model, processing capacity, network interface parameters, supported protocol types and control object identification information of each PLC.

[0018] S12. Configure a one-to-one mapping between the physical PLC and its controlled I / O modules, establish a logical association table between the PLC and the I / O modules, and record the control channel number, the I / O module identifier and the channel type corresponding to each PLC.

[0019] S13. Assign a unique edge node address, system control identifier and link priority parameters to each PLC, and configure its communication interface binding information, including Ethernet port address, list of switchable ports and redundant link support status.

[0020] S14. Construct a control architecture description model in the edge computing unit to structurally express the master-slave relationship, redundancy hierarchy, control path priority, and link dependency relationship among multiple PLCs. The model includes:

[0021] The system comprises the following components: a control node set (representing all registered physical PLCs, shadow PLCs, and cloud PLCs, with each node labeled with its role type, computing capability identifier, bound I / O module list, and status synchronization interface identifier); a control relationship set (identifying redundant mapping relationships between control nodes, supporting a master-slave configuration, and specifying the takeover trigger conditions and path switching direction for the master PLC and its corresponding shadow PLC and cloud PLC); a status mirror mapping table (recording the synchronization mapping path and caching strategy of the master PLC's input / output status in backup nodes, achieving status consistency management); a control path set (defining all possible valid control links, with each link associated with its priority value, communication protocol type, link bound port range, and path failure transfer rules); a control domain coverage table (identifying the I / O module range, signal channel type, and dynamic channel mapping flags covered by each control path, serving as the data support structure for the arbitration mechanism); and a redundant role switching parameter set (defining the trigger threshold, execution lock strategy, and switching stability waiting period for control switching between roles, ensuring the integrity and consistency of the control migration process).

[0022] Ultimately, this control architecture description model serves as the foundational data model for describing the edge control topology, providing unified structural support for master control scheduling strategies, link switching configurations, and I / O redundancy arbitration.

[0023] S15. Mark the control priority, control range, and associated I / O device list for each control path, and summarize them to form a main control link set for subsequent redundancy scheduling.

[0024] S16. Based on the priority relationship and control redundancy strategy of each control path, the physical PLC, shadow PLC and cloud PLC are divided into primary, backup and emergency roles, and finally the edge control topology description of the multi-PLC system is output.

[0025] Optionally, step S2 specifically includes:

[0026] S21. Based on the edge control topology description, deploy software-defined CPE components in the edge computing nodes and load core functional modules for protocol identification and link control, including dynamic protocol stack management module and link binding control module;

[0027] S22. Establish a communication protocol template library, which includes various industrial protocol templates such as ModbusTCP, Profinet and EtherCAT. Each template includes a protocol identification field, frame structure definition, parameter mapping rules and parsing priority flag.

[0028] S23. Perform protocol compatibility analysis on the historical communication behavior of each PLC node and I / O module, extract feature information such as interface type, communication rate, and data frame format, and match them with the communication protocol template library;

[0029] S24. Configure the protocol loading strategy for each edge device, determine its default enabled protocol type, supported protocol switching mode and link port binding method, and form a set of protocol loading configuration items;

[0030] S25. Based on the protocol loading configuration item set, initialize the runtime environment of the communication protocol template library, and register the parsing function entry, link monitoring interface and dynamic switching control instruction set for each protocol;

[0031] S26. Complete the link establishment and protocol loading initialization between the CPE component and the PLC / I / O device, and output the protocol template library structure and CPE control interface instance set that can be used for subsequent communication identification.

[0032] Optionally, step S3 specifically includes:

[0033] S31. Obtain the port configuration, communication protocol identifier and link binding information of each PLC node and its associated I / O module, and establish an initial device connection relationship table based on the edge control topology description;

[0034] S32. Based on the protocol template library, call the communication protocol templates that have been loaded in it, identify the protocol type of the communication behavior between each group of devices, match the communication feature fields, frame structure and rate parameters, and determine the actual type of communication protocol used.

[0035] S33. Collect the current connection status, communication quality indicators, data packet integrity rate and link fault records of each communication link, and construct a communication link status mapping set by combining the physical connection relationship between devices;

[0036] S34. Analyze the link status mapping set and protocol type identification results to generate a communication protocol mapping table, which is used to identify the protocol adaptation method and communication channel binding relationship between each pair of PLC and I / O modules.

[0037] S35. Construct a communication topology diagram in the edge computing unit, representing the protocol interaction paths, link availability status, and switching feasibility between all PLCs and I / O modules, and marking the protocol type and port binding information of each link;

[0038] S36. Output the communication protocol mapping table and communication topology diagram as the basic structural data for subsequent status data collection and dynamic link adjustment.

[0039] Optionally, step S4 specifically includes:

[0040] S41. Based on the communication topology diagram, activate the communication link between all PLC nodes and their connected I / O modules, start the status acquisition process and initialize the status recording buffer.

[0041] S42. Real-time acquisition of multi-source status data of each PLC and I / O module, including input status, output status, communication port connection status, link quality indicators and equipment fault event logs, and additional standardized timestamp information;

[0042] S43. Based on multi-source state data, perform preprocessing, including format unification, anomaly removal and time alignment, to generate a set of structured state data records;

[0043] S44. Index and divide the structured status data according to device identifier, data type and communication direction, and construct a status cache block organized by device dimension;

[0044] S45. Establish a synchronization mapping index for each state buffer block, identify its corresponding master PLC, shadow PLC and cloud PLC synchronization path, and indicate whether the state mirroring mechanism is enabled.

[0045] S46. Encapsulate the state cache block and the set of synchronization mapping indices into a state synchronization cache, and output the data input object for subsequent master control scheduling and I / O arbitration.

[0046] Optionally, step S5 specifically includes:

[0047] S51. Based on the running status and synchronization status of multiple PLC nodes recorded in the status synchronization cache, determine whether the master PLC meets the continuous control conditions and link integrity requirements, and generate the current master control evaluation result.

[0048] S52. Based on the master control evaluation results, the preset master control scheduling strategy is invoked. The master control scheduling strategy includes: determining whether the master PLC needs to be switched based on the stability of the PLC link, the integrity of the control state synchronization and the response delay threshold; selecting a shadow PLC or a cloud PLC as a candidate takeover node according to a preset priority; completing the control transfer and state mirror consistency verification; determining whether the master-standby switchover mechanism is triggered; and selecting a candidate shadow PLC or a cloud PLC as a new master control node candidate.

[0049] S53. Start the status mirroring synchronization mechanism, copy the input and output status of the current master PLC to the candidate master control node, and verify the mirroring consistency simultaneously.

[0050] S54. After completing the image consistency verification, perform the master control transfer operation, including releasing the original master node control lock, activating the candidate node control channel, and registering the instruction receiving interface and response mechanism.

[0051] S55. Record the timestamp, participating nodes, triggering reason and switching path of this control switch event, and update the master control status mapping table;

[0052] S56. Output the updated master control status mapping table and the current master control switching determination result, which are used to drive subsequent I / O module channel selection and link reconstruction.

[0053] Optionally, step S6 specifically includes:

[0054] S61. Based on the master control status mapping table and the device operation status data set, identify the valid communication links, activation status and binding relationship of the master control node for all I / O modules, and construct a redundant channel availability table.

[0055] S62. Evaluate the communication quality of multiple signal channels for each I / O module, collect its response time, packet loss rate, channel stability and historical fault records, and generate channel health score results.

[0056] S63. Based on the current control path priority of the master control node, the channel health score of each I / O module, and the signal real-time requirements, a redundant channel selection algorithm is executed based on multi-dimensional communication performance indicators to determine the primary signal channel and backup signal channel for each I / O module; the redundant channel selection algorithm is used to optimize and allocate alternative channels among multiple available channels, specifically including:

[0057] The channel health score is calculated by weighting four indicators: communication latency, packet loss rate, response consistency, and historical failure frequency, to obtain a score reflecting the channel's reliability. Based on the control path priority of the master node and the real-time performance level of the I / O module tasks, a weighting adjustment factor is set to dynamically adjust the influence coefficients of each evaluation dimension. Candidate channels for each I / O module are sorted according to their scores, with the channel with the highest score selected as the primary signal channel and the second-highest score channel as the backup signal channel. A switching trigger rule is set between the primary and backup channels; when the real-time score of the primary channel falls below a preset health threshold, or when link interruption or abnormal response latency is detected, the system automatically switches to the backup channel.

[0058] S64. Establish signal path arbitration relationships between selected channels, construct an arbitration control rule set, and define the competition priority, conflict resolution method, and fault switching threshold between channels.

[0059] S65. Generate an I / O module signal channel mapping table, identify the binding information of the currently active main channel and backup channel of each module, and record the corresponding control path and master control node identifier;

[0060] S66, Output signal channel mapping table and arbitration control rule set, are used to drive subsequent link reconstruction and control command distribution.

[0061] Optionally, step S7 specifically includes:

[0062] S71. Based on the signal channel mapping table and arbitration control rule set, extract the target communication path and current channel binding status between each PLC and I / O module, and generate a list of links to be reconstructed.

[0063] S72. Based on the communication protocol mapping table, determine the communication protocol type, communication frame structure and corresponding port configuration requirements required for the link to be reconstructed, and establish a set of link reconstruction parameters.

[0064] S73. Invoke the link control module in the software-defined CPE component to perform a communication link switching operation. This module includes a port binding control submodule and an IP reallocation submodule, used to activate the target port, release the original port, and reconfigure the device IP address to achieve dynamic reconstruction of the communication path.

[0065] S74. Perform protocol consistency verification on the switched communication path to ensure that the protocol template type, parameter mapping method and parsing priority used by both communicating parties are consistent.

[0066] S75. After a successful link switchover, record the timestamp of the link reconfiguration event, port information before and after the switchover, and configuration changes, and update the current communication topology diagram and protocol mapping table.

[0067] S76 outputs the link reconfiguration results and updated communication control parameters, which are used to drive subsequent master control scheduling refresh, I / O channel mapping adjustment and remote control strategy synchronization.

[0068] The beneficial effects of this invention are:

[0069] First, by constructing a multi-level redundant control architecture consisting of physical PLCs, shadow PLCs, and cloud PLCs, this invention effectively solves the problem of relying on hardware redundancy modules for switching between primary and backup PLCs in traditional industrial systems. It enables rapid takeover and uninterrupted control in the event of primary control failure, thereby improving the continuity and reliability of the system.

[0070] Secondly, this invention designs a state mirroring synchronization and master control scheduling mechanism to ensure that the state data between each control node is consistent during the master-slave switchover process, thereby realizing the safe transfer of control and data synchronization and effectively avoiding operational conflicts and control failures during the switchover process.

[0071] Furthermore, this invention addresses the signal channel fault and conflict issues of I / O modules by proposing a redundant channel selection algorithm based on multi-dimensional index scoring and path priority judgment, which improves the intelligence and response speed of signal channel switching and enhances the system's fault tolerance and self-healing capabilities.

[0072] Finally, this invention introduces a software-defined CPE component, which supports dynamic identification and template loading of multiple industrial communication protocols. Combined with real-time monitoring and reconfiguration control of communication link status, it realizes lossless switching of cross-protocol links and adaptive access of devices, significantly improving the communication flexibility and overall resilience of the edge control system. Attached Figure Description

[0073] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0074] Figure 1 This is an overall flowchart of the cloud-edge collaborative intelligent scheduling and control method for heterogeneous devices proposed in this invention;

[0075] Figure 2 This is a schematic diagram of the multi-level redundant PLC control structure and main control scheduling mechanism in this invention;

[0076] Figure 3 This is a structural diagram of the link reconfiguration and communication protocol adaptation mechanism supported by the software-defined CPE in this invention. Detailed Implementation

[0077] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, illustrating only the basic structure of the invention, and therefore only show the components relevant to the invention.

[0078] refer to Figure 1-3 A cloud-edge collaborative intelligent scheduling and control method for heterogeneous devices includes the following steps:

[0079] S1. Construct a multi-level redundant control architecture consisting of multiple physical PLCs, shadow PLCs and cloud virtual PLCs, configure the unique identifier, control object, communication interface and associated I / O module information of each PLC, and generate a description of the edge control topology of the multi-PLC system.

[0080] S2. Based on the edge control topology description, deploy software-defined CPE components in the edge computing nodes, initialize the dynamic protocol stack management module, load communication protocol templates supporting ModbusTCP, Profinet and EtherCAT, and generate a protocol template library.

[0081] S3. Based on the PLC and I / O module mapping information and protocol template library, identify the current communication protocol type and link status of heterogeneous devices, and construct a communication protocol mapping table and an initial communication topology diagram.

[0082] S4. Based on the communication topology diagram, collect the input and output status, link connection status and communication quality indicators of each PLC and I / O module, upload them to the edge computing node, generate a multi-device operation status dataset, merge and establish a status synchronization cache;

[0083] S5. Based on state synchronization cache, execute the PLC master-slave control scheduling strategy, use the state mirroring mechanism to synchronize the state of the master PLC to the shadow PLC and the cloud PLC in real time, and generate the master control state mapping table and the current master control switching judgment result.

[0084] S6. Based on the master control switching judgment result and the equipment operation status data set, execute the redundant channel selection and signal path arbitration mechanism of the I / O module, and generate the I / O module signal channel mapping table and arbitration control strategy;

[0085] S7. Based on the signal channel mapping table and arbitration control strategy, combined with the communication protocol mapping table, the software-defined CPE component is called to dynamically adjust the communication link port and IP binding relationship, realize lossless switching of communication links, and output the link reconstruction configuration result.

[0086] This invention proposes an intelligent scheduling and control method for heterogeneous devices based on cloud-edge collaboration. It constructs a multi-level redundant control architecture consisting of physical PLCs, shadow PLCs, and cloud PLCs. Software-defined CPE components are deployed in edge computing nodes and multi-protocol templates are loaded to realize communication protocol identification, status data acquisition and synchronous caching, master control scheduling and control switching, I / O module redundant channel arbitration and link reconstruction operations. This forms an edge intelligent closed-loop control system that runs through perception, scheduling and switching, and has comprehensive innovative advantages such as communication self-adaptation, dynamic transfer of control rights and fault self-healing.

[0087] In this embodiment, step S1 specifically includes:

[0088] S11. Obtain the hardware configuration list of multiple physical PLC devices, shadow PLC devices and cloud virtual PLCs involved in the heterogeneous control system, including the model, processing capacity, network interface parameters, supported protocol types and control object identification information of each PLC.

[0089] S12. Configure a one-to-one mapping between the physical PLC and its controlled I / O modules, establish a logical association table between the PLC and the I / O modules, and record the control channel number, the I / O module identifier and the channel type corresponding to each PLC.

[0090] S13. Assign a unique edge node address, system control identifier and link priority parameters to each PLC, and configure its communication interface binding information, including Ethernet port address, list of switchable ports and redundant link support status.

[0091] S14. Construct a control architecture description model in the edge computing unit to structurally express the master-slave relationship, redundancy hierarchy, control path priority, and link dependency relationship among multiple PLCs. The model includes:

[0092] The system comprises the following components: a control node set (representing all registered physical PLCs, shadow PLCs, and cloud PLCs, with each node labeled with its role type, computing capability identifier, bound I / O module list, and status synchronization interface identifier); a control relationship set (identifying redundant mapping relationships between control nodes, supporting a master-slave configuration, and specifying the takeover trigger conditions and path switching direction for the master PLC and its corresponding shadow PLC and cloud PLC); a status mirror mapping table (recording the synchronization mapping path and caching strategy of the master PLC's input / output status in backup nodes, achieving status consistency management); a control path set (defining all possible valid control links, with each link associated with its priority value, communication protocol type, link bound port range, and path failure transfer rules); a control domain coverage table (identifying the I / O module range, signal channel type, and dynamic channel mapping flags covered by each control path, serving as the data support structure for the arbitration mechanism); and a redundant role switching parameter set (defining the trigger threshold, execution lock strategy, and switching stability waiting period for control switching between roles, ensuring the integrity and consistency of the control migration process).

[0093] Ultimately, this control architecture description model serves as the foundational data model for describing the edge control topology, providing unified structural support for master control scheduling strategies, link switching configurations, and I / O redundancy arbitration.

[0094] S15. Mark the control priority, control range, and associated I / O device list for each control path, and summarize them to form a main control link set for subsequent redundancy scheduling.

[0095] S16. Based on the priority relationship and control redundancy strategy of each control path, the physical PLC, shadow PLC and cloud PLC are divided into primary, backup and emergency roles, and finally the edge control topology description of the multi-PLC system is output.

[0096] This step involves structured configuration of a multi-PLC system, proposing an edge control topology description method that includes role division, communication interface parameters, logic mapping, control path priority, and state synchronization rules. It constructs a control architecture description model and refines the control node set, mirror mapping table, and master-slave relationship set, providing an executable data structure foundation for redundant control scheduling, master migration, and edge determination mechanisms, thereby enhancing the system's redundancy flexibility and control reliability.

[0097] In this embodiment, step S2 specifically includes:

[0098] S21. Based on the edge control topology description, deploy software-defined CPE components in the edge computing nodes and load core functional modules for protocol identification and link control, including dynamic protocol stack management module and link binding control module;

[0099] S22. Establish a communication protocol template library, which includes various industrial protocol templates such as ModbusTCP, Profinet and EtherCAT. Each template includes a protocol identification field, frame structure definition, parameter mapping rules and parsing priority flag.

[0100] S23. Perform protocol compatibility analysis on the historical communication behavior of each PLC node and I / O module, extract feature information such as interface type, communication rate, and data frame format, and match them with the communication protocol template library;

[0101] S24. Configure the protocol loading strategy for each edge device, determine its default enabled protocol type, supported protocol switching mode and link port binding method, and form a set of protocol loading configuration items;

[0102] S25. Based on the protocol loading configuration item set, initialize the runtime environment of the communication protocol template library, and register the parsing function entry, link monitoring interface and dynamic switching control instruction set for each protocol;

[0103] S26. Complete the link establishment and protocol loading initialization between the CPE component and the PLC / I / O device, and output the protocol template library structure and CPE control interface instance set that can be used for subsequent communication identification.

[0104] This step involves deploying software-defined CPE components at edge nodes, building a dynamically loadable protocol template library, and combining edge device communication behavior analysis with protocol feature field matching to complete communication protocol type identification and adaptation initialization. This forms a dynamic binding mechanism between communication interfaces and protocol templates, enabling unified access and flexible switching of multi-protocol heterogeneous devices in industrial sites, and laying the protocol foundation for subsequent link control and communication topology construction.

[0105] In this embodiment, step S3 specifically includes:

[0106] S31. Obtain the port configuration, communication protocol identifier and link binding information of each PLC node and its associated I / O module, and establish an initial device connection relationship table based on the edge control topology description;

[0107] S32. Based on the protocol template library, call the communication protocol templates that have been loaded in it, identify the protocol type of the communication behavior between each group of devices, match the communication feature fields, frame structure and rate parameters, and determine the actual type of communication protocol used.

[0108] S33. Collect the current connection status, communication quality indicators, data packet integrity rate and link fault records of each communication link, and construct a communication link status mapping set by combining the physical connection relationship between devices;

[0109] S34. Analyze the link status mapping set and protocol type identification results to generate a communication protocol mapping table, which is used to identify the protocol adaptation method and communication channel binding relationship between each pair of PLC and I / O modules.

[0110] S35. Construct a communication topology diagram in the edge computing unit, representing the protocol interaction paths, link availability status, and switching feasibility between all PLCs and I / O modules, and marking the protocol type and port binding information of each link;

[0111] S36. Output the communication protocol mapping table and communication topology diagram as the basic structural data for subsequent status data collection and dynamic link adjustment.

[0112] This step addresses the issues of communication path identification and topology modeling by proposing a link identification mechanism that combines device configuration and protocol templates. It collects link quality and communication status, constructs a communication protocol mapping table and a communication topology diagram, and enables dynamic perception and path modeling of the communication structure at the edge. This improves the system's protocol management and link visualization capabilities in complex industrial network environments.

[0113] In this embodiment, step S4 specifically includes:

[0114] S41. Based on the communication topology diagram, activate the communication link between all PLC nodes and their connected I / O modules, start the status acquisition process and initialize the status recording buffer.

[0115] S42. Real-time acquisition of multi-source status data of each PLC and I / O module, including input status, output status, communication port connection status, link quality indicators and equipment fault event logs, and additional standardized timestamp information;

[0116] S43. Based on multi-source state data, perform preprocessing, including format unification, anomaly removal and time alignment, to generate a set of structured state data records;

[0117] S44. Index and divide the structured status data according to device identifier, data type and communication direction, and construct a status cache block organized by device dimension;

[0118] S45. Establish a synchronization mapping index for each state buffer block, identify its corresponding master PLC, shadow PLC and cloud PLC synchronization path, and indicate whether the state mirroring mechanism is enabled.

[0119] S46. Encapsulate the state cache block and the set of synchronization mapping indices into a state synchronization cache, and output the data input object for subsequent master control scheduling and I / O arbitration.

[0120] This step focuses on the real-time acquisition and structured caching of equipment operation information, and designs a process for generating status synchronization cache. It covers multi-source data acquisition, standardization conversion, organization of cache by device dimension and establishment of primary and backup path mapping relationship, providing reliable edge data support for dynamic judgment of control status, primary control mirror synchronization and arbitration decision-making, and enhancing the timeliness and data integrity of the system.

[0121] In this embodiment, step S5 specifically includes:

[0122] S51. Based on the running status and synchronization status of multiple PLC nodes recorded in the status synchronization cache, determine whether the master PLC meets the continuous control conditions and link integrity requirements, and generate the current master control evaluation result.

[0123] S52. Based on the master control evaluation results, the preset master control scheduling strategy is invoked. The master control scheduling strategy includes: determining whether the master PLC needs to be switched based on the stability of the PLC link, the integrity of the control state synchronization and the response delay threshold; selecting a shadow PLC or a cloud PLC as a candidate takeover node according to a preset priority; completing the control transfer and state mirror consistency verification; determining whether the master-standby switchover mechanism is triggered; and selecting a candidate shadow PLC or a cloud PLC as a new master control node candidate.

[0124] S53. Start the status mirroring synchronization mechanism, copy the input and output status of the current master PLC to the candidate master control node, and verify the mirroring consistency simultaneously.

[0125] S54. After completing the image consistency verification, perform the master control transfer operation, including releasing the original master node control lock, activating the candidate node control channel, and registering the instruction receiving interface and response mechanism.

[0126] S55. Record the timestamp, participating nodes, triggering reason and switching path of this control switch event, and update the master control status mapping table;

[0127] S56. Output the updated master control status mapping table and the current master control switching determination result, which are used to drive subsequent I / O module channel selection and link reconstruction.

[0128] This step, based on state synchronization caching and link state, proposes a master control scheduling strategy and control switching mechanism. By utilizing primary PLC evaluation, candidate node screening, state image consistency verification, and switching execution logic, a dynamic master control state mapping process is constructed to achieve a highly reliable scheduling process with seamless migration of master and backup control and uninterrupted operation. This is the core link in realizing intelligent edge redundancy control.

[0129] In this embodiment, step S6 specifically includes:

[0130] S61. Based on the master control status mapping table and the device operation status data set, identify the valid communication links, activation status and binding relationship of the master control node for all I / O modules, and construct a redundant channel availability table.

[0131] S62. Evaluate the communication quality of multiple signal channels for each I / O module, collect its response time, packet loss rate, channel stability and historical fault records, and generate channel health score results.

[0132] S63. Based on the current control path priority of the master control node, the channel health score of each I / O module, and the signal real-time requirements, a redundant channel selection algorithm is executed based on multi-dimensional communication performance indicators to determine the primary signal channel and backup signal channel for each I / O module; the redundant channel selection algorithm is used to optimize and allocate alternative channels among multiple available channels, specifically including:

[0133] The channel health score is calculated by weighting four indicators: communication latency, packet loss rate, response consistency, and historical failure frequency, to obtain a score reflecting the channel's reliability. Based on the control path priority of the master node and the real-time performance level of the I / O module tasks, a weighting adjustment factor is set to dynamically adjust the influence coefficients of each evaluation dimension. Candidate channels for each I / O module are sorted according to their scores, with the channel with the highest score selected as the primary signal channel and the second-highest score channel as the backup signal channel. A switching trigger rule is set between the primary and backup channels; when the real-time score of the primary channel falls below a preset health threshold, or when link interruption or abnormal response latency is detected, the system automatically switches to the backup channel.

[0134] S64. Establish signal path arbitration relationships between selected channels, construct an arbitration control rule set, and define the competition priority, conflict resolution method, and fault switching threshold between channels.

[0135] S65. Generate an I / O module signal channel mapping table, identify the binding information of the currently active main channel and backup channel of each module, and record the corresponding control path and master control node identifier;

[0136] S66, Output signal channel mapping table and arbitration control rule set, are used to drive subsequent link reconstruction and control command distribution.

[0137] This step involves designing a redundant channel selection algorithm and a signal path arbitration mechanism. By combining communication health scores, master path priority, and real-time requirements, it intelligently selects the primary and backup channels for each I / O module and establishes competition rules and fault switching strategies. This achieves adaptive mapping of signal paths and channel redundancy fault tolerance, which is a key innovation in ensuring the continuity of I / O module operation and the system's self-healing capability.

[0138] In this embodiment, step S7 specifically includes:

[0139] S71. Based on the signal channel mapping table and arbitration control rule set, extract the target communication path and current channel binding status between each PLC and I / O module, and generate a list of links to be reconstructed.

[0140] S72. Based on the communication protocol mapping table, determine the communication protocol type, communication frame structure and corresponding port configuration requirements required for the link to be reconstructed, and establish a set of link reconstruction parameters.

[0141] S73. Invoke the link control module in the software-defined CPE component to perform a communication link switching operation. This module includes a port binding control submodule and an IP reallocation submodule, used to activate the target port, release the original port, and reconfigure the device IP address to achieve dynamic reconstruction of the communication path.

[0142] S74. Perform protocol consistency verification on the switched communication path to ensure that the protocol template type, parameter mapping method and parsing priority used by both communicating parties are consistent.

[0143] S75. After a successful link switchover, record the timestamp of the link reconfiguration event, port information before and after the switchover, and configuration changes, and update the current communication topology diagram and protocol mapping table.

[0144] S76 outputs the link reconfiguration results and updated communication control parameters, which are used to drive subsequent master control scheduling refresh, I / O channel mapping adjustment and remote control strategy synchronization.

[0145] This step aims at link reconstruction. It calls the link control module in the software-defined CPE to perform communication port switching and IP rebinding operations based on protocol consistency verification. This forms a linkage mechanism between protocol mapping table updates and communication topology adjustments, enabling lossless switching of cross-protocol links and adaptive edge communication, significantly improving the system's link recovery capability and communication resilience in dynamic scenarios.

[0146] Example 1:

[0147] To verify the feasibility of this invention in practice, it was applied to the intelligent manufacturing system upgrade project of a hot rolling mill workshop under a steel group. The aim was to solve problems in the workshop's original automated control system, such as incompatible protocols between heterogeneous equipment, high risk of single-point failure of the main control PLC, and inflexible communication link switching. This hot rolling production line control system includes 10 physical PLC devices, over 150 I / O modules, and various sensor devices. The equipment manufacturers include multiple brands such as Siemens, Schneider Electric, and Omron, and the control protocols include various industrial communication standards such as Modbus TCP, Profinet, and EtherCAT, exhibiting significant protocol heterogeneity and non-standard equipment characteristics.

[0148] In this project, the edge computing units proposed in this invention were deployed to systematically reconstruct all control nodes and equipment in the hot rolling workshop. For multi-brand PLC equipment, a unified multi-level redundant control architecture was constructed, designating the primary physical PLC, shadow PLC, and cloud-based virtual PLC as control scheduling objects. Each PLC was configured with a unique control identifier, network interface, and corresponding I / O module list. By loading the multi-protocol communication template library pre-defined in this invention into the software-defined CPE components deployed at the edge nodes, automatic identification and adaptation of three mainstream protocols—Modbus TCP, Profinet, and EtherCAT—was achieved, enabling heterogeneous protocol PLCs and I / O modules to be uniformly registered in the system control topology.

[0149] During actual operation, edge nodes collect status data from all devices and build a real-time status synchronization cache. The primary PLC mirrors and synchronizes the control status to the shadow and cloud PLC nodes, forming a multi-level redundant control mapping table. During a production line switchover, the primary PLC lost response due to a sudden failure. The edge nodes completed the master control switchover operation within 8ms through the status mirroring mechanism, automatically transferring control to the shadow PLC and continuing to stably output control commands based on the current status cache, without causing any I / O channel interruptions or device alarms. Measurements showed that from the primary PLC failure to the system's stable switchover and control recovery, only 11ms elapsed, far lower than the 30ms to 100ms switchover time of the traditional cold standby redundancy mode.

[0150] To address the issue of frequent fluctuations in link communication, this system introduces the redundant link health scoring mechanism and signal channel arbitration strategy of this invention. Edge nodes evaluate link quality every 500ms, including metrics such as packet loss rate, latency, stability, and bandwidth. Combined with control path priority and I / O real-time requirements, the system dynamically decides which primary / backup signal channel to use. In a link instability test caused by electromagnetic interference, the system automatically identified a packet retransmission rate exceeding 70% on the current Modbus link and automatically switched to the backup Profinet link within the next control cycle (approximately 20ms). This achieved seamless link reconfiguration and maintained stable signal output, avoiding device control jumps caused by link interruptions.

[0151] During the project deployment, the intelligent scheduling system ran for a total of 21 days, handling 14 master control switching events, 23 link reconstruction operations, and 18 communication protocol adaptive conversions. The overall system control stability improved by approximately 42%, and the average fault response time decreased by 65%. In scheduling multiple cross-production lines, no control loss occurred during the link reconstruction process, and the equipment switching process was completed silently. Workshop operators reported that they could hardly feel the switching process, greatly enhancing the transparency and resilience of the control system.

[0152] By applying the method of this invention to a multi-PLC heterogeneous system in a complex industrial environment, not only are the goals of standardized protocol management, redundant control scheduling, and intelligent link switching achieved, but the stable operation capability and automatic self-healing level of the system in the industrial environment are also significantly improved, verifying the practicality and advancement of the method of this invention in a real industrial environment.

[0153] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for intelligent scheduling and control of heterogeneous devices based on cloud-edge collaboration, characterized in that, Comprise the following steps: S1, construct a multi-level redundant control architecture composed of multiple physical PLCs, shadow PLCs and cloud virtual PLCs, configure the unique identification, control object, communication interface and associated I / O module information of each PLC, and generate a multi-PLC system edge control topology structure description; S2, based on the edge control topology structure description, deploy the software defined CPE component, initialize the dynamic protocol stack management module, load the communication protocol template, and generate the protocol template library; S3, based on the PLC and I / O module mapping information and the protocol template library, construct a communication protocol mapping relationship table and an initial communication topology structure diagram; S4, based on the communication topology structure diagram, collect the input and output state, link connection state and communication quality index of each PLC and I / O module, generate a multi-device running state data set and establish a state synchronization cache; S5, based on the state synchronization cache, execute the PLC master-slave control scheduling strategy, and use the state mirroring mechanism to generate the master state mapping table and the current master switching judgment result; S6, based on the master switching judgment result and the device running state data set, execute the I / O module redundant channel selection and signal path arbitration mechanism, generate the I / O module signal channel mapping table and the arbitration control strategy; S7, based on the signal channel mapping table and the arbitration control strategy, combined with the communication protocol mapping relationship table, call the software defined CPE component, dynamically adjust the communication link port and IP binding relationship, realize the lossless switching of the communication link, and output the link reconstruction configuration result. 2.The cloud-edge collaboration based heterogeneous device intelligent scheduling and control method of claim 1, wherein, The step S1 specifically comprises: S11, obtain the hardware configuration list of the multiple physical PLC devices, shadow PLC devices and cloud virtual PLCs involved in the heterogeneous control system; S12, one-to-one mapping configuration is performed on the physical PLC and the I / O module controlled thereby, and a logical association table of the PLC and the I / O module is established; S13, a unique edge node address, system control identification and link priority parameter are allocated to each PLC, and its communication interface binding information is configured; S14, a control architecture description model is constructed in the edge computing unit, which is used to structurally express the master-slave relationship, redundancy level, control path priority and link dependency relationship among multiple PLCs, and the model comprises: Control node set, control relationship set, state mirroring mapping table, control path set, control domain coverage table, redundancy role switching parameter set; Finally, the control architecture description model serves as the basic data model of the edge control topology structure description, providing unified structural support for master scheduling strategy, link switching configuration and I / O redundancy arbitration; S15, mark the control priority, control range and associated I / O device list of each control path, and form a master link set by summarizing; S16, according to the priority relationship and control redundancy strategy of each control path, the physical PLC, shadow PLC and cloud PLC are divided into master, standby and emergency roles, and finally the edge control topology structure description of the multi-PLC system is output. 3.The cloud-edge collaboration based heterogeneous device intelligent scheduling and control method of claim 1, wherein, The step S2 specifically comprises: S21, based on the edge control topology description, deploying a software-defined CPE component in the edge computing node, loading core function modules for protocol identification and link control; S22, establishing a communication protocol template library; S23, performing protocol adaptability analysis on the historical communication behavior of each PLC node and I / O module, extracting feature information, and matching with the communication protocol template library; S24, configuring the protocol loading strategy of each edge device, determining the default enabled protocol type, supported protocol switching mode and link port binding method, and forming a protocol loading configuration item set; S25, based on the protocol loading configuration item set, initializing the runtime environment of the communication protocol template library, registering the parsing function entry, link monitoring interface and dynamic switching control instruction set of each protocol; S26, completing the link establishment and protocol loading initialization of the CPE component and PLC / I / O device, and outputting the protocol template library structure and CPE control interface instance set for subsequent communication identification. 4.The cloud-edge collaboration based heterogeneous device intelligent scheduling and control method of claim 1, wherein, The step S3 specifically comprises: S31, obtaining the port configuration, communication protocol identification and link binding information of each PLC node and its associated I / O module, and establishing a device connection initial relationship table based on the edge control topology description; S32, based on the protocol template library, calling the loaded communication protocol template therein, identifying the protocol type of the communication behavior between each group of devices, and determining the actual used communication protocol type; S33, collecting the current connection state, communication quality index, data packet integrity rate and link fault record of each communication link, combining the physical connection relationship between devices, and constructing a communication link state mapping set; S34, analyzing the link state mapping set and the protocol type identification result, generating a communication protocol mapping relationship table, which is used to identify the protocol adaptation mode and communication channel binding relationship between each pair of PLC and I / O module; S35, constructing a communication topology structure diagram in the edge computing unit, representing the protocol interaction path, link available state and switching feasibility between all PLCs and I / O modules, and marking the protocol type and port binding information of each link; S36, outputting the communication protocol mapping relationship table and the communication topology structure diagram.

5. The method of claim 1, wherein the cloud-edge collaboration based intelligent scheduling and control of heterogeneous devices is characterized by, The step S4 specifically comprises: S41, based on the communication topology structure diagram, activating the communication link between all PLC nodes and the I / O modules connected thereto, starting the state collection process and initializing the state record buffer; S42, collecting multi-source state data of each PLC and I / O module in real time, and adding standardized timestamp information; S43, based on the multi-source state data, performing preprocessing to generate a structured state data record set; S44, indexing and dividing the structured state data according to device identification, data type and communication direction, and constructing state cache blocks organized by device dimension; S45, establishing a synchronization mapping index for each state cache block, identifying the corresponding primary PLC, shadow PLC and cloud PLC synchronization path, and marking whether the state mirroring mechanism is enabled; S46, encapsulating the state cache blocks and synchronization mapping index set into a state synchronization cache. 6.The cloud-edge collaboration based heterogeneous device intelligent scheduling and control method of claim 1, wherein, The step S5 specifically comprises: S51, based on the running state and synchronization state of the multiple PLC nodes recorded in the state synchronization cache, judging whether the primary PLC meets the continuous control condition and link integrity requirement, and generating a current master evaluation result; S52, based on the master evaluation result, calling a preset master scheduling strategy, the master scheduling strategy comprising: judging whether the primary PLC needs to be switched according to the PLC link stability, control state synchronization integrity and response delay threshold, selecting a shadow PLC or a cloud PLC as a candidate takeover node according to a preset priority, and completing control right migration and state mirror consistency verification, determining whether to trigger the master-standby switching mechanism, and selecting the candidate shadow PLC or the cloud PLC as a new master node candidate; S53, starting a state mirror synchronization mechanism, copying the input state and output state of the current primary PLC to the candidate master node, and synchronously verifying the mirror consistency; S54, after completing the mirror consistency verification, performing a master control right migration operation; S55, recording the timestamp, participating nodes, trigger reason and switching path of the current control right switching event, and updating the master state mapping table; S56, outputting the updated master state mapping table and the current master switching judgment result, for driving subsequent I / O module channel selection and link reconstruction. 7.The cloud-edge collaboration based heterogeneous device intelligent scheduling and control method of claim 1, wherein, The step S6 specifically comprises: S61, based on the master state mapping table and the device running state data set, identifying the binding relationship between the valid communication link, active state and master node of all I / O modules, and constructing a redundant channel availability table; S62, performing communication quality evaluation on multiple signal channels of each I / O module, and generating a channel health score result; S63, based on the current control path priority of the master node, the channel health score of each I / O module and the signal real-time requirement, executing a redundant channel selection algorithm based on multiple communication performance indicators, to determine the primary signal channel and the standby signal channel of each I / O module; the redundant channel selection algorithm is used for preferred and standby channel allocation between multiple available channels, specifically comprising: calculating the channel health score, performing weighted evaluation based on four types of indicators of the communication delay, packet loss rate, response consistency and historical failure frequency of the channel, to obtain a score value reflecting the reliability of the channel; according to the control path priority where the master node is located and the real-time level of the I / O module task, a weight adjustment factor of the channel score is set to dynamically adjust the influence coefficient of each evaluation dimension; the candidate channels of each I / O module are sorted according to the score value, the channel with the highest score is selected as the primary signal channel, and the channel with the second highest score is selected as the standby signal channel; a switching trigger rule is set between the primary channel and the standby channel, when the real-time score of the primary channel is lower than a preset health threshold, or conditions such as link interruption and response delay anomaly are detected, the standby channel is automatically switched to; S64, establishing a signal path arbitration relationship between the selected channels, constructing an arbitration control rule set, and defining the competition priority order, conflict resolution method and fault switching threshold between the channels; S65, generate an I / O module signal channel mapping table, identify the current effective main channel and standby channel binding information of each module, and record the corresponding control path and master node identifier; S66, output the signal channel mapping table and the arbitration control rule set. 8.The cloud-edge collaboration based heterogeneous device intelligent scheduling and control method of claim 1, wherein, The step S7 specifically comprises: S71, based on the signal channel mapping table and the arbitration control rule set, generate a to-be-reconstructed link list; S72, based on the communication protocol mapping relationship table, determine the communication protocol type, communication frame structure and corresponding port configuration requirement required by the to-be-reconstructed link, and establish a link reconstruction parameter set; S73, call the link control module in the software-defined CPE component to perform a communication link switching operation to realize dynamic reconstruction of the communication path. S74, perform protocol consistency verification on the switched communication path to ensure that the protocol template type, parameter mapping method and parsing priority used by both parties are consistent; S75, after the link switching is successful, record the timestamp of the link reconstruction event, the port information before and after the switching and the configuration change items, update the current communication topology structure diagram and the protocol mapping table; S76, output the link reconstruction configuration result and the updated communication control parameter, which is used to drive the subsequent master scheduling refresh, I / O channel mapping adjustment and remote control strategy synchronization.

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