Method of automatic group control system based on OPCUA information model

Abstract

The invention relates to a method of a large-scale automatic group control system based on an OPCUA information model. The method comprises the following steps: step 101, defining a controller information model containing digital models of an industrial sensor, an actuator and a unit; step 102, integrating the controller information model with an OPCUA server to realize mapping of internal attributes, variables and methods of the model and the interior of the controller; step 103, realizing data transmission and production data synchronization between the controllers through an OPCUA protocol; 104, in the OPCUA server, when the object method is called externally, an instruction string is generated; and step 105, feeding back an execution result to the OPCUA client according to an action execution condition in the called method, and completing a closed loop of a platform control process. The method has the advantages that the interoperability between different devices and systems is enhanced through the controller information model created by combining AutomationML and OPCUA standards, and the limitation of closure and specificity is broken through.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of industrial automation, and particularly to a method of large-scale automation group control system based on OPCUA information model, for realizing efficient instruction execution and data synchronization between long-distance device groups. BACKGROUND

[0002] Under the background of Industry 4.0, industrial automation systems are developing towards intelligence, networking and integration. However, the limitations and drawbacks of existing technologies gradually appear, which are specifically manifested in the following aspects: Closed and special problem: The existing industrial automation system often adopts special technical standards and communication protocols, which leads to poor interoperability between systems. This closed nature limits the interconnection and intercommunication between different devices and systems, making integration and expansion difficult.

[0003] Special problem means that the system can only be compatible with a specific brand of device or software, lacking flexibility and difficulty in adapting to changing industrial needs.

[0004] Software and hardware are deeply bound to the platform: Many industrial automation systems deeply bind software and hardware to specific platforms, which limits the user's freedom in choosing devices and software and increases the dependence on a single supplier. This binding also makes it difficult to update and upgrade technology, as replacing or upgrading the system may require large capital investment and long downtime.

[0005] Communication protocol and interface diversity: There are various communication protocols and interface standards in the field of industrial automation, such as Modbus, Profibus, EtherCAT, etc. The non-uniformity between these standards increases the complexity of system integration. Device manufacturers may support different communication protocols, making it complex to integrate devices from different manufacturers on the same production line, requiring additional gateways and converters.

[0006] Poor scene practicability: Many existing automation systems lack adaptability to specific industrial scenarios and cannot meet the needs of specific processes or production processes. The system is often too complex to be quickly deployed and adjusted to adapt to rapidly changing market demands and production environments.

[0007] Challenge of centralized control: Centralized control systems need to handle a large amount of data and instructions, which requires strong computing power and efficient data processing mechanisms. Centralized control also involves data security and reliability issues, and how to ensure data security while realizing efficient centralized control is a challenge.

[0008] In summary, these drawbacks of existing industrial automation systems limit their development potential in the context of Industry 4.0, and there is an urgent need for a new solution to overcome these challenges and improve the flexibility, scalability and economy of the system. This is what the invention aims to solve by proposing a large-scale automation group control system based on OPCUA information model to achieve more efficient, flexible and economical industrial automation control. SUMMARY

[0009] To overcome the defects of the prior art, the present application provides a method for a large-scale automation group control system based on an OPCUA information model, and the technical solution of the present application is: A method for an automation group control system based on an OPCUA information model, the method comprising the following steps: Step 101: defining a controller information model containing a digital model of industrial sensors, actuators and machine groups; Step 102: integrating the controller information model with the OPCUA server to realize the mapping of internal attributes, variables and methods of the model with the internal controller; Step 103: realizing data transmission and production data synchronization between controllers through the OPCUA protocol; Step 104: in the OPCUA server, when an object method is called externally, an instruction string is generated, and the following sub-steps of the instruction state machine are executed internally in the controller: Step 104.1: instruction checking, verifying the validity of the instruction string; Step 104.2: instruction synthesis, merging multiple instructions into an executable instruction string using a synthesis algorithm f; Step 104.3: instruction issuance, sending the synthesized instruction string to the actuator; Step 104.4: instruction execution monitoring, monitoring the feedback of the actuator; Step 104.5: instruction reset, resetting the instruction state after execution is completed; Step 104.6: method feedback, feeding back the execution result to the OPCUA client; Step 105: according to the action execution in the called method, feeding back the execution result to the OPCUA client, completing the closed loop of the platform control process.

[0010] The controller information model defined in step 101 is created by combining AutomationML and OPCUA standards.

[0011] The integrated OPCUA server in step 102 supports several industrial communication protocols and can perform protocol conversion using a protocol conversion algorithm p: p(P1)=P2, where P1 is the source protocol data and P2 is the target protocol data.

[0012] The data transmission in step 103 includes synchronization of real-time data and historical data, and uses a data synchronization algorithm s: s(D1,D2)=D', where D1 and D2 are data sources and D' is the synchronized data.

[0013] Step 104.1 instruction checking includes the following sub-steps: Verify the syntax correctness of the instruction string; Verify the logical consistency of the instruction string; Verify the permission control of the instruction string, using a permission verification algorithm v: v(U,P)=A, where U is the user, P is the permission setting, and A is the access result.

[0014] The instruction synthesis algorithm f in step 104.2 is defined as: f(I1,I2,...,In)=I', where I1,I2,...,In are the instructions to be synthesized, and I' is the synthesized instruction string.

[0015] The instruction issuing in step 104.3 includes the following sub-steps: Instruction encapsulation, encapsulating the synthesized instruction string into a network transmission format; Instruction transmission, sending the encapsulated instruction string to the target executor through the OPCUA protocol; Instruction confirmation, confirming that the executor has received the instruction string, using a confirmation algorithm c: c(T,R)=C, where T is the transmission result, R is the reception result, and C is the confirmation status.

[0016] The instruction execution monitoring in step 104.4 includes the following sub-steps: execution state tracking, tracking the state of the executor in real time; feedback signal analysis, analyzing the feedback signal returned by the executor; exception handling, handling abnormal situations during execution, using an exception handling algorithm g: g(E)=R, where E is the exception event and R is the response measure; The instruction reset in step 104.5 includes the following sub-steps: State clearing, clearing the state information of the current execution; resource release, releasing the resources occupied during execution; state updating, updating the state of the controller to prepare for the next execution.

[0017] The method feedback in step 104.6 includes the following sub-steps: Result verification, verifying the correctness of the execution result; Result encoding, encoding the execution result into a format understandable by the client; Result transmission, transmitting the encoded result to the OPCUA client.

[0018] The closed loop of the platform control flow completed in step 105 includes the following sub-steps: Result analysis, analyzing the impact of the execution result on the entire system, using the result analysis algorithm h: h(R)=S, where R is the execution result and S is the system state adjustment suggestion; System adjustment, adjusting system parameters according to the result analysis; Feedback record, record feedback results for optimization.

[0019] The advantages of the present application are: Interoperability improvement: The controller information model created by combining AutomationML and OPCUA standards enhances the interoperability between different devices and systems, breaking the limitations of closedness and specialization.

[0020] Increased integration flexibility: OPCUA server supports multiple industrial communication protocols and can perform protocol conversion, making system integration more flexible and able to adapt to the integration needs of different manufacturers and devices.

[0021] Data synchronization efficiency: The real-time data and historical data synchronization mechanism improves the efficiency of data processing, ensuring the consistency and accuracy of data, which is crucial for production monitoring and historical data analysis.

[0022] Security and permission management: Through the permission verification algorithm, only authorized users can execute specific instructions, enhancing the security of the system.

[0023] Improved instruction processing capability: The instruction synthesis algorithm can combine multiple instructions into an executable instruction string, improving the efficiency and accuracy of instruction processing.

[0024] Execution monitoring and exception handling: The execution state tracking and exception handling mechanism can monitor the state of the executor in real time and respond quickly when an exception occurs, improving the stability and reliability of the system.

[0025] Feedback and closed loop control: The method feedback and closed loop control mechanism ensures that the execution result can be fed back to the OPCUA client in a timely manner, and adjusts the system parameters according to the result, achieving more accurate control.

[0026] Reducing costs and improving efficiency: By reducing the need for protocol conversion and hardware and software modification, the complexity and cost of the system are reduced, while the deployment and upgrade efficiency of the system is improved. DETAILED DESCRIPTION

[0027] The present application will be further described below in connection with specific embodiments, and the advantages and features of the present application will become more apparent from the description. However, these embodiments are only exemplary and do not constitute any limitation on the scope of the present application. Those skilled in the art should understand that modifications or substitutions can be made to the details and forms of the technical solutions of the present application without departing from the spirit and scope of the present application, and such modifications and substitutions fall within the protection scope of the present application.

[0028] The present application relates to a method for an OPCUA information model-based automation group control system, which comprises the following steps: Step 101: defining a controller information model containing a digital model of industrial sensors, actuators and units; Step 102: integrating the controller information model with an OPCUA server to realize the mapping between the internal attributes, variables and methods of the model and the internal controller; Step 103: realizing the data transmission between controllers and the synchronization of production data through the OPCUA protocol; Step 104: in the OPCUA server, when an object method is called externally, generating an instruction string and executing the following sub-steps of the instruction state machine in the internal controller: Step 104.1: instruction checking, verifying the validity of the instruction string; Step 104.2: instruction synthesis, merging multiple instructions into an executable instruction string using a synthesis algorithm f; Step 104.3: instruction issuing, sending the synthesized instruction string to the actuator; Step 104.4: instruction execution monitoring, monitoring the feedback of the actuator; Step 104.5: instruction resetting, resetting the instruction state after execution is completed; Step 104.6: method feedback, feeding back the execution result to the OPCUA client; Step 105: according to the action execution in the called method, feeding back the execution result to the OPCUA client to complete the closed loop of the platform control process.

[0029] Based on the above steps, the following is achieved: Standardized and modularized design: the controller information model defined in step 101 adopts standardized OPCUA and AutomationML, making the system integration more modularized and facilitating extension and maintenance.

[0030] Improved integration efficiency: step 102 realizes the mapping between the internal model and the internal controller by integrating the OPCUA server, simplifying the system integration process and improving the integration efficiency.

[0031] Data consistency and real-time performance: Step 103 utilizes OPCUA protocol to achieve data transmission and synchronization, ensuring data consistency and real-time performance, which is crucial for quick response to production changes.

[0032] Automation and optimization of instruction processing: The instruction state machine in step 104 automatically processes external calls, reducing human intervention and improving the speed and accuracy of instruction processing.

[0033] Step 105 completes the closed-loop control process of the platform, enabling the system to self-optimize based on execution results, improving control accuracy and system stability.

[0034] The overall implementation of steps 101 to 105 is an automated group control system method based on OPCUA information model, which provides a comprehensive, efficient, and reliable industrial automation control solution through a series of carefully designed steps. The following are the key functions and advantages of these steps: Comprehensive system integration: By defining the controller information model (step 101) and integrating it with the OPCUA server (step 102), the overall digitalization and integration of industrial sensors, actuators, and units are achieved, providing a solid foundation for automation control.

[0035] Efficient data management and synchronization: Utilizing OPCUA protocol (step 103) for data transmission between controllers and production data synchronization ensures real-time and consistent data, providing accurate data support for production decisions.

[0036] Automated instruction processing and execution: The instruction state machine (step 104) automatically processes externally called instructions, including instruction checking (step 104.1), instruction synthesis (step 104.2), instruction issuance (step 104.3), instruction execution monitoring (step 104.4), instruction reset (step 104.5), and method feedback (step 104.6), improving instruction processing speed and accuracy and reducing human errors.

[0037] Enhanced security and reliability: By verifying the validity of instruction strings (step 104.1) and using permission verification algorithms (step 105.1), only authorized users can execute specific instructions, enhancing system security.

[0038] Real-time monitoring and quick response: Real-time monitoring of actuator feedback (step 104.4) and exception handling (step 104.4) enable the system to quickly respond to any exceptions during execution, improving system stability and reliability.

[0039] Closed-loop control and self-optimization: The execution results are fed back to the OPCUA client according to the action execution in the called method (step 105), completing the closed loop of the platform control process, so that the system can be self-optimized according to the execution results, improving the accuracy of control and the stability of the system.

[0040] The controller information model defined in step 101 is created by combining AutomationML and OPCUA standards. The controller information model defined in step 101 is created by combining AutomationML and OPCUA standards, which has the following advantages: Standardization and compatibility: Using OPCUA and AutomationML, two internationally recognized standards, ensures the wide compatibility and interoperability of the controller information model, facilitating integration between different manufacturers and technologies.

[0041] Modular design: The information model created by combining the two standards supports modular design, allowing system components to be easily combined and reused like building blocks, improving system flexibility and maintainability.

[0042] The integrated OPCUA server in step 102 supports several industrial communication protocols and can perform protocol conversion using the protocol conversion algorithm p: p(P1)=P2, where P1 is the source protocol data and P2 is the target protocol data. This step achieves: Protocol flexibility: Supporting multiple industrial communication protocols enables the system to be compatible with devices and systems from different manufacturers, improving system flexibility and applicability.

[0043] Enhanced interoperability: Protocol conversion capabilities ensure seamless communication between different protocols, enhancing interoperability between system components and allowing more extensive devices and systems to work together.

[0044] Data transmission in step 103 includes real-time data and historical data synchronization, using the data synchronization algorithm s: s(D1,D2)=D′, where D1 and D2 are data sources and D′ is the synchronized data.

[0045] Step 104.1 instruction checking includes the following sub-steps: Verify the syntax correctness of the instruction string; Verify the logical consistency of the instruction string; Verify the permission control of the instruction string, using the permission verification algorithm v: v(U,P)=A, where U is the user, P is the permission setting, and A is the access result.

[0046] The instruction synthesis algorithm f in step 104.2 is defined as: f(I1, I2,..., In) = I', where I1, I2,..., In are the instructions to be synthesized, and I' is the synthesized instruction string.

[0047] The instruction issuing in step 104.3 includes the following sub-steps: Instruction packaging, packaging the synthesized instruction string into a network transmission format; Instruction transmission, sending the packaged instruction string to the target executor through the OPCUA protocol; Instruction confirmation, confirming that the executor has received the instruction string, using the confirmation algorithm c: c(T, R) = C, where T is the transmission result, R is the reception result, and C is the confirmation state.The instruction execution monitoring in step 104.4 includes the following sub-steps: State clearing, clearing the state information of the current execution; resource release, releasing the resources occupied during the execution; state updating, updating the state of the controller to prepare for the next execution.

[0048] The method feedback in step 104.6 includes the following sub-steps: Result verification, verifying the correctness of the execution result; result encoding, encoding the execution result into a format understandable by the client; result transmission, transmitting the encoded result to the OPCUA client.

[0049] The above steps (steps 104.1 to 104.6) constitute the core process of instruction processing in the automatic group control system, each step has obvious advantages, the following is the comprehensive advantages of these steps: Enhanced security and permission management: through the permission verification algorithm v(U, P) = Av(U, P) = A, it is ensured that only authorized users can execute specific instructions, enhancing the security and permission management of the system.

[0050] Improve the accuracy and reliability of instructions: the instruction checking step ensures the grammatical correctness and logical consistency of the instruction string, reducing execution errors and potential system risks.

[0051] Optimized instruction processing efficiency: the instruction synthesis algorithm f(I1, I2,..., In) = I' allows multiple instructions to be combined into an instruction string, improving the efficiency and execution speed of instruction processing.

[0052] Enhanced instruction issuance and confirmation mechanism: The instruction issuance step includes encapsulation, transmission, and confirmation, ensuring accurate communication and execution of instructions. The use of confirmation algorithm c(T,R)=C enhances the reliability of execution.

[0053] Real-time monitoring and feedback: The instruction execution monitoring step provides real-time tracking of execution status and feedback signal analysis, enabling the system to respond promptly to changes and abnormalities during execution.

[0054] Exception management and rapid response: The exception handling algorithm g(E)=R enables the system to quickly identify and respond to abnormal events, reducing potential downtime and losses.

[0055] Resource management and optimization: The instruction reset step includes state clearing, resource release, and state updating, optimizing the use of system resources and preparing for the next execution.

[0056] Improving system transparency and user trust: The method feedback step ensures verification, encoding, and transmission of execution results, improving system transparency and enhancing user trust in the system.

[0057] Improving the overall performance of the system: These steps work together to improve the overall performance of the system, including response speed, accuracy, and stability.

[0058] Reducing maintenance costs and complexity: Through automated and optimized instruction processing procedures, the system's maintenance costs and complexity are reduced.

[0059] Improving the adaptability and flexibility of the system: The system can adapt to different execution environments and requirements, providing higher flexibility and adaptability.

[0060] The closed-loop platform control process in step 105 includes the following sub-steps: Result analysis, analyzing the impact of execution results on the entire system using result analysis algorithm h: h(R)=S, where R is the execution result and S is the system state adjustment suggestion; System adjustment, adjusting system parameters based on result analysis; Feedback record, record feedback results for optimization use.

[0061] This application describes a method of an OPCUA information model-based automatic group control system, which works on a series of carefully designed steps to achieve efficient, reliable and intelligent control in industrial automation. The following is the overall description of the working principle of the system: System Modeling and Standardization (Step 101): The system first defines a digital model that includes key components such as industrial sensors, actuators, and machine groups. This model adheres to AutomationML and OPCUA standards, ensuring standardization and modularity, facilitating integration of different devices and systems.

[0062] Integration and Mapping (Step 102): The controller information model is integrated with the OPCUA server, enabling the mapping of internal attributes, variables, and methods to the controller. This step ensures a close connection between the model and the actual controller, providing a foundation for data exchange and instruction execution.

[0063] Data Transmission and Synchronization (Step 103): Using OPCUA protocols, the system enables data transmission between controllers and synchronization of production data, including real-time and historical data. Data synchronization algorithms ensure data consistency and real-time performance, which are crucial for production monitoring and decision-making.

[0064] Instruction Processing and Execution (Step 104): When external objects invoke methods, the system generates instruction strings and executes instruction state machines within the controller. This includes instruction checking (Step 104.1), instruction synthesis (Step 104.2), instruction issuance (Step 104.3), instruction execution monitoring (Step 104.4), instruction reset (Step 104.5), and method feedback (Step 104.6).

[0065] Instruction Checking: Verifies the grammatical correctness, logical consistency, and permission control of instruction strings, ensuring the safety and effectiveness of instructions.

[0066] Instruction Synthesis: Combines multiple instructions into an executable instruction string, improving instruction processing efficiency.

[0067] Instruction Issuance: Encapsulates and transmits the synthesized instruction string to the actuator and confirms that the actuator has received the instruction string.

[0068] Instruction Execution Monitoring: Tracks the status of the actuator in real-time, analyzes feedback signals, and handles abnormal situations.

[0069] Instruction Reset: Resets the instruction state after execution is complete, preparing for the next execution.

[0070] Method Feedback: Feedbacks the execution results to the OPCUA client, ensuring transparency and controllability.

[0071] Closed-Loop Control and Optimization (Step 105): The system completes the closed-loop control process of the platform based on the execution results, including result analysis, system adjustment, and feedback recording. This step enables the system to optimize itself based on execution results, improving control accuracy and system stability.

[0072] Through these steps, the automatic group control system of the present application realizes the whole process automation control from data synchronization, instruction processing to execution monitoring. The design of the system focuses on interoperability, flexibility, security and efficiency, making it a comprehensive, efficient and reliable industrial automation control solution. In addition, the closed-loop control mechanism of the system enables it to continuously optimize itself, adapt to changing production needs, and improve production efficiency and quality.

[0073] The above is only the preferred specific implementation of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art within the technical range disclosed by the present application, according to the technical scheme and the inventive concept of the present application, makes equivalent replacement or change, which should be covered in the protection scope of the present application.

Claims

1. A method of an OPC UA information model-based automation colony control system, characterized by, The method comprises the following steps: Step 101: defining a controller information model containing a digital model of industrial sensors, actuators, and machine groups; Step 102: integrating the controller information model with an OPCUA server to realize the mapping of internal attributes, variables, and methods of the model to the internal controller; Step 103: realizing data transmission and production data synchronization between controllers through the OPCUA protocol; Step 104: in the OPCUA server, when an external object method is called, generating an instruction string and executing the following sub-steps of the instruction state machine inside the controller: Step 104.1: instruction checking, verifying the validity of the instruction string; Step 104.2: instruction synthesis, merging multiple instructions into an executable instruction string using a synthesis algorithm f; Step 104.3: instruction issuance, sending the synthesized instruction string to the actuator; Step 104.4: instruction execution monitoring, monitoring the feedback of the actuator; Step 104.5: instruction reset, resetting the instruction state after execution is completed; Step 104.6: method feedback, feeding back the execution result to the OPCUA client; Step 105: according to the action execution in the called method, feeding back the execution result to the OPCUA client to complete the closed loop of the platform control process.

2. The method of the OPC UA information model based automation group control system according to claim 1, characterized in that, The controller information model defined in step 101 is created by combining AutomationML and OPCUA standards. 3.The method of the OPC UA information model based automation group control system according to claim 1, wherein, The integrated OPCUA server in step 102 supports several industrial communication protocols and can perform protocol conversion using a protocol conversion algorithm p: p(P1)=P2, where P1 is the source protocol data and P2 is the target protocol data.

4. The method of the OPC UA information model based automation group control system according to claim 1, characterized in that, The data transmission in step 103 includes real-time data and historical data synchronization, and uses a data synchronization algorithm s: s(D1,D2)=D', where D1 and D2 are data sources and D' is the synchronized data.

5. The method of OPC UA information model based automation group control system according to claim 1, wherein, The instruction checking in step 104.1 includes the following sub-steps: Verifying the grammatical correctness of the instruction string; Verifying the logical consistency of the instruction string; Verifying the permission control of the instruction string using a permission verification algorithm v: v(U,P)=A, where U is the user, P is the permission setting, and A is the access result.

6. The method of OPC UA information model based automation group control system according to claim 1, wherein, The instruction synthesis algorithm f in step 104.2 is defined as: f(I1,I2,...,In)=I', where I1,I2,...,In are the instructions to be synthesized, and I' is the synthesized instruction string.

7. The method of OPC UA information model based automation group control system according to claim 1, wherein, The instruction issuance in step 104.3 includes the following sub-steps: Instruction encapsulation, encapsulating the synthesized instruction string into a network transmission format; Instruction transmission, sending the encapsulated instruction string to the target actuator through the OPCUA protocol; Instruction confirmation, confirming that the actuator has received the instruction string using a confirmation algorithm c: c(T,R)=C, where T is the transmission result, R is the reception result, and C is the confirmation status.

8. The method of the OPC UA information model based automation group control system according to claim 1, characterized in that, The instruction execution monitoring in step 104.4 includes the following sub-steps: execution state tracking, tracking the state of the executor in real time; feedback signal analysis, analyzing the feedback signal returned by the executor; exception handling, handling abnormal situations in the execution process, using exception handling algorithm g: g(E)=R, where E is the exception event and R is the response measure; The instruction reset in step 104.5 includes the following sub-steps: State clearing, clearing the state information of the current execution; resource releasing, releasing the resources occupied in the execution process; state updating, updating the state of the controller to prepare for the next execution; The method feedback in step 104.6 includes the following sub-steps: Result verification, verifying the correctness of the execution result; result encoding, encoding the execution result into a format understandable by the client; result transmission, transmitting the encoded result to the OPCUA client.

9. The method of the OPC UA information model based automation group control system according to claim 8, characterized in that, The closed loop of the platform control process in step 105 includes the following sub-steps: Result analysis, analyzing the impact of the execution result on the entire system, using result analysis algorithm h: h(R)=S, where R is the execution result and S is the system state adjustment suggestion; System adjustment, adjusting system parameters according to the result analysis; Feedback recording, recording the feedback result for optimization use.