Intelligent cooperative control system, equipment, medium and product

Abstract

The invention discloses an intelligent cooperative control system, equipment, a medium and a product, and relates to the technical field of intelligent control, in the control system, external sensing data is acquired from a communication sensing module through an intelligent decision module, task planning and real-time decision making are carried out by adopting a means of combining hierarchical reinforcement learning and game theory, a decision instruction is obtained, and the decision instruction is sent to the intelligent decision module; and the decision execution module controls each subsystem to execute corresponding operation according to the decision instruction, and finally, the monitoring and feedback module continuously monitors the internal state and the execution result of the system, and displays the internal state and the execution result of the system to a user through the man-machine interaction module. The intelligent cooperative control system can receive and process data from various external sensors in real time, is not limited by hardware, is extremely high in expandability, can perform intelligent task planning according to complex environment and state information by adopting a decision-making means of combining hierarchical reinforcement learning with the game theory, and is high in practicability. And tasks are automatically allocated and an execution strategy is optimized.

Description

Technical Field

[0001] The present application relates to the field of intelligent control technology, and in particular to an intelligent collaborative control system, equipment, medium and product. Background Art

[0002] With the rapid development of Industry 4.0 and the Internet of Things (IoT), intelligent collaborative control systems play a key role in improving production efficiency, optimizing resource allocation, and enhancing safety. In current technologies, a variety of communication protocols, sensor technologies, and data processing methods are integrated into intelligent collaborative control systems, but these systems often face challenges such as high data transmission delays, insufficient processing capabilities, and low system integration. In addition, existing intelligent collaborative control systems usually lack intelligence in task scheduling and decision making, making it difficult to achieve instant response and adaptive decision adjustments.

[0003] In view of this, it is particularly important to develop an efficient and intelligent collaborative control system by combining advanced wireless communications, machine learning, real-time operating systems and other high-tech technologies. Summary of the invention

[0004] The purpose of this application is to provide an intelligent collaborative control system, equipment, medium and product, which can efficiently realize collaborative control and improve the intelligence level of the collaborative control system.

[0005] To achieve the above objectives, this application provides the following solutions: In a first aspect, the present application provides an intelligent collaborative control system, including: a communication perception module, an intelligent decision-making module, a decision execution module, a resource coordination module, a monitoring and feedback module, and a human-computer interaction module.

[0006] The communication perception module is used to access external sensors and acquire, preprocess and store external sensor data based on user-defined transmission protocols.

[0007] The intelligent decision-making module is used to obtain external sensor data from the communication perception module, and based on the external sensor data, use a combination of hierarchical reinforcement learning and game theory to perform task planning and real-time decision-making to obtain decision instructions. The decision instructions include program instructions for implementing corresponding subtasks.

[0008] The decision execution module is used to receive the decision instructions of the intelligent decision module, control each subsystem to perform corresponding operations according to the decision instructions, and send the execution results to the monitoring and feedback module.

[0009] The monitoring and feedback module is used to continuously monitor the system's internal status and execution results, and display the system's internal status and execution results to the user through the human-computer interaction module.

[0010] The resource coordination module is used to manage the cooperation of various subsystems, maximize the efficiency of the control system, and handle resource scheduling and resource conflicts when each subsystem executes subtasks.

[0011] Optionally, the communication perception module has multiple transmission paths including Bluetooth transmission, WIFI transmission and wired transmission, and can receive data information collected by various types of external sensors through different transmission means and pre-process and store the data information; the user-defined transmission protocol of the communication perception module adopts a strong encryption standard to ensure the security of data during transmission, and uses an encryption algorithm to protect the data content; the user-defined transmission protocol also uses an efficient compression algorithm to reduce the size of transmitted data and increase the transmission speed; the user-defined transmission protocol also uses multi-threaded asynchronous transmission technology to improve the efficiency of data transmission; the user-defined transmission protocol also uses efficient encoding and serialization technology to reduce data overhead during transmission.

[0012] Optionally, the intelligent decision-making module uses hierarchical reinforcement learning based on external sensor data to decompose the complex target task into a series of simple sub-tasks, uses the cooperative game model in game theory to allocate sub-tasks, and combines Q-Learning and game theory to provide optimal strategy planning for the entire system to obtain decision instructions; when optimizing the cooperative game model, the policy gradient method is used to improve the strategy, adjust the learning rate, discount factor and other hyperparameters of the model to improve performance, or use experience replay to improve data efficiency and learning stability.

[0013] Optionally, the decision execution module includes an industrial-grade microcontroller unit and its peripheral circuits, and the industrial-grade microcontroller unit has a digital signal processing unit and a floating-point operation unit; the decision execution module can control each subsystem to perform corresponding operations to implement the decision according to the decision instructions given by the intelligent decision module, and send the execution results of the decision to the monitoring and feedback module.

[0014] Optionally, the monitoring and feedback module is used to continuously monitor the internal state of the system and the execution results of the decisions, and display the internal state of the system and the execution results to the user through the human-computer interaction module; the monitoring and feedback module is also used to define performance indicators and perform regular benchmark tests according to the specific needs of the system to evaluate whether the performance of the system meets the expected standards, and is also used to monitor the system performance indicators in real time and quickly discover performance bottlenecks; the monitoring and feedback module is also used to combine statistical methods and machine learning algorithms to learn and identify normal modes and abnormal modes, set thresholds for key parameters, trigger alarms when parameters exceed the thresholds, and notify users through the alarm system of the human-computer interaction module when an abnormality or performance degradation is detected.

[0015] Optionally, the resource coordination module is used to coordinate and schedule the workflow between subsystems, and handle potential resource competition, time conflicts and priority conflicts among subsystems to maximize the efficiency of the control system; the resource coordination module uses the real-time operating system FreeRTOS, and adopts a scheduling strategy based on time slice rotation and priority preemption. Different priorities are assigned according to the importance of tasks. Tasks with higher priorities are called for resource execution first, and each task will be placed back at the end of the ready queue after running a time slice to ensure that other tasks of the same priority have a chance to execute.

[0016] Optionally, the human-computer interaction module uses an industrial-grade serial port screen and is designed with a human-computer interaction interface, allowing the user to monitor and control the system through the human-computer interaction interface; the human-computer interaction interface includes a main display area, a status prompt area and a device control area; the main display area is used to display real-time data and a control panel, and the user can start and stop tasks and adjust priorities through control panel operations; the status prompt area is used to display communication status, system power, communication mode and external device type; the device control area is used for users to select and delete connected external devices; external devices include external sensors.

[0017] In a second aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the intelligent collaborative control system described above.

[0018] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the intelligent collaborative control system described above.

[0019] In a fourth aspect, the present application provides a computer program product, including a computer program, which implements the intelligent collaborative control system described above when executed by a processor.

[0020] According to the specific embodiments provided in this application, this application discloses the following technical effects: The present application provides an intelligent collaborative control system, equipment, medium and product. In the control system, a communication perception module is first used to access external sensors, and external sensor data is acquired, preprocessed and stored based on a user-defined transmission protocol. Subsequently, the external sensor data is acquired from the communication perception module through an intelligent decision-making module, and a combination of hierarchical reinforcement learning and game theory is used to perform task planning and real-time decision-making to obtain decision instructions. The decision execution module controls each subsystem to perform corresponding operations according to the decision instructions, and sends the execution results to a monitoring and feedback module; finally, the internal state of the system and the execution results are continuously monitored through the monitoring and feedback module, and the internal state of the system and the execution results are displayed to the user through the human-computer interaction module; during the execution process, the cooperation of each subsystem is managed through the resource coordination module to maximize the efficiency of the control system and handle resource scheduling and resource conflicts when each subsystem executes subtasks. The above-mentioned intelligent collaborative control system of the present application can receive and process data from various external sensors in real time, is not limited by hardware, has strong scalability, and adopts a decision-making method that combines hierarchical reinforcement learning with game theory. It can perform intelligent task planning based on complex environment and state information, automatically assign tasks and optimize execution strategies. Compared with the traditional rule-driven method, this intelligent decision-making process can adapt to more changes and complex operational requirements. In addition, the resource coordination module is used to manage the cooperation of various subsystems for the purpose of maximizing the efficiency of the control system, realize efficient scheduling of system resources, and improve the overall performance and stability of the collaborative control system. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1 A schematic diagram of functional modules of an intelligent collaborative control system provided in one embodiment of the present application.

[0023] Figure 2 A schematic diagram of a human-computer interaction interface of an intelligent collaborative control system provided in one embodiment of the present application.

[0024] Figure 3 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0026] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0027] An intelligent collaborative control system provided in an embodiment of the present application is as follows: Figure 1 As shown, it includes: a communication perception module, an intelligent decision-making module, a decision execution module, a resource coordination module, a monitoring and feedback module and a human-computer interaction module.

[0028] The communication perception module is used to access external sensors and acquire, preprocess and store external sensor data based on user-defined transmission protocols.

[0029] The intelligent decision-making module is used to obtain external sensor data from the communication perception module, and based on the external sensor data, use a combination of hierarchical reinforcement learning and game theory to perform task planning and real-time decision-making to obtain decision instructions. The decision instructions include program instructions for implementing corresponding subtasks.

[0030] The decision execution module is used to receive the decision instructions of the intelligent decision module, control each subsystem to perform corresponding operations according to the decision instructions, and send the execution results to the monitoring and feedback module.

[0031] The monitoring and feedback module is used to continuously monitor the system's internal status and execution results, and display the system's internal status and execution results to the user through the human-computer interaction module.

[0032] The resource coordination module is used to manage the cooperation of various subsystems, maximize the efficiency of the control system, and handle resource scheduling and resource conflicts when each subsystem executes subtasks.

[0033] In an exemplary embodiment of the present application, the communication perception module has multiple transmission paths including Bluetooth transmission, WIFI transmission and wired transmission, and can receive data information collected by various types of external sensors through different transmission means and pre-process and store the data information; the user-defined transmission protocol of the communication perception module adopts a strong encryption standard to ensure the security of data during transmission, and uses an encryption algorithm to protect the data content; the user-defined transmission protocol also uses an efficient compression algorithm to reduce the size of transmitted data and increase the transmission speed; the user-defined transmission protocol also uses multi-threaded asynchronous transmission technology to improve the efficiency of data transmission; the user-defined transmission protocol also uses efficient encoding and serialization technology to reduce data overhead during transmission.

[0034] When applied in the field of medical system control, commonly used external sensors include heart rate, temperature, blood oxygen, light, pressure, acoustic sensors and other devices. The data information collected by each device is shared within the system after preprocessing. The preprocessing includes data cleaning, data normalization and standardization, time series processing, data fusion, feature extraction, data compression, feature selection and dimensionality reduction, anomaly detection, data encoding, data storage and caching, etc.

[0035] The communication perception module supports data transmission rates up to 300Mbps, supports 2.4GHz and 5GHz frequency bands, and generally uses the 2.4GHz frequency band in environments with obstacles. The transmission power is adjustable, up to 18dBm, and supports dual R-SMA female antenna connectors. High-gain antennas can be used to increase the transmission distance. MIMO technology and OFDM modulation provide stable and reliable wireless connections, and power consumption is about 6W. In summary, the communication perception module provides high-speed data transmission capabilities, good transmission distance and penetration, and stable transmission performance, which is suitable for wireless communication needs in industrial environments.

[0036] In the communication perception module, users can customize the data transmission format according to different sensor data transmission types, support multiple acquisition front ends, and have wide compatibility. This protocol uses strong encryption standards to ensure the security of data during transmission and uses encryption algorithms to protect data content. Use efficient compression algorithms to reduce the size of transmitted data and increase transmission speed; use multi-threaded asynchronous transmission technology to improve the efficiency of data transmission; use efficient encoding and serialization technology to reduce data overhead during transmission.

[0037] In an exemplary embodiment of the present application, the intelligent decision-making module uses hierarchical reinforcement learning based on external sensor data to decompose complex target tasks into a series of simple sub-tasks, and uses the cooperative game model in game theory to allocate sub-tasks, combining Q-Learning and game theory to provide optimal strategy planning for the entire system to obtain decision instructions; when optimizing the cooperative game model, the policy gradient method is used to improve the strategy, adjust the learning rate, discount factor and other hyperparameters of the model to improve performance, or use experience replay to improve data efficiency and learning stability.

[0038] For example, one of the current ultimate goals is to display all the data of the sensor devices on the human-computer interaction interface, monitor different data, and provide error feedback. Then it can be divided into several subtasks, such as: receiving and sending data, drawing interface waveforms, early warning of different data, feedback on system operation status, etc. Since there is no rigid execution order requirement between these steps, they can be broken down into subtasks. Furthermore, if the ECG waveform is to be drawn, more data points are required so that a waveform can be drawn. Then the real-time requirement of this subtask is relatively strong, so it is likely to be set as the highest priority subtask for priority processing. And the heart rate only needs to be refreshed once every few seconds, so its priority will be relatively low.

[0039] Specifically, in one embodiment, the decision instruction is generated in the form of a predefined rule base or conditional statement, and the decision module transmits information to the decision execution module through a message queue and a data protocol. The operation types corresponding to the decision instruction include hardware control, data processing, status update, communication operation, alarm and notification operation, scheduling and management, etc.

[0040] In an exemplary embodiment of the present application, the decision execution module includes an industrial-grade microcontroller unit and its peripheral circuits. The industrial-grade microcontroller unit can provide a Cortex-M7 core of up to 216MHz. The industrial-grade microcontroller unit has a digital signal processing unit and a floating-point operation unit, which is suitable for industrial applications requiring high-performance computing and processing capabilities; the decision execution module can control each subsystem to perform corresponding operations to implement the decision according to the decision instructions given by the intelligent decision module, and send the execution results of the decision to the monitoring and feedback module.

[0041] In an exemplary embodiment of the present application, the monitoring and feedback module is used to continuously monitor the internal state of the system and the execution results of the decision, and the internal state of the system and the execution results are displayed to the user through the human-computer interaction module; the monitoring and feedback module is also used to define performance indicators and perform benchmark tests regularly according to the specific needs of the system, such as response time, throughput, resource utilization, etc., to evaluate whether the performance of the system meets the expected standards, and is also used to monitor the system performance indicators in real time and quickly discover performance bottlenecks; the monitoring and feedback module is also used to combine statistical methods and machine learning algorithms to learn and identify normal modes and abnormal modes, set thresholds for key parameters, trigger alarms when parameters exceed thresholds, and notify users through the alarm system of the human-computer interaction module when abnormalities or performance degradation are detected. When the load of the monitoring system continues to be heavy, some strong real-time tasks will be strictly executed according to time, but some tasks that will not have an impact if skipped once or twice can be skipped and not executed, and computing resources are concentrated to process strong real-time and large computing tasks, and specific adjustments are handled by the coordination module.

[0042] In an exemplary embodiment of the present application, the resource coordination module is used to coordinate and schedule the workflow between subsystems, and to handle potential resource competition, time conflicts and priority conflicts among subsystems, so as to maximize the efficiency of the control system; the resource coordination module uses the real-time operating system FreeRTOS, and adopts a scheduling strategy based on time slice rotation and priority preemption. Different priorities are assigned according to the importance of tasks. Tasks with higher priorities are called for resource execution first, and each task will be placed back at the end of the ready queue after running a time slice to ensure that other tasks of the same priority have a chance to execute.

[0043] Specifically, when a task is created, the task function, stack size, task name, and priority are specified through the xTaskCreate or xTaskCreateStatic function. In order to avoid task starvation, high-priority tasks should give up the CPU as soon as possible after completing the task to avoid long-term occupancy. FreeRTOS provides mutex locks to ensure mutual exclusive access to shared resources and prevent data competition. Binary semaphores can be used to synchronize tasks to ensure that tasks are executed in the correct order. Access to shared resources is protected through the taskENTER_CRITICAL and taskEXIT_CRITICAL macros to prevent context switching within the critical section. In addition, FreeRTOS also supports priority inheritance to solve the priority flipping problem and ensure that high-priority tasks are not blocked indefinitely by low-priority tasks.

[0044] In FreeRTOS, you can also enable time slice rotation by configuring configUSE_TIME_SLICING. That is, each task will be put back to the end of the ready queue after running a time slice to ensure that other tasks of the same priority have a chance to execute. FreeRTOS provides a variety of memory management schemes, including heap management strategies for allocating stacks and TCBs (task control blocks) when tasks are created. The task notification function of FreeRTOS can be used to send signals between tasks without using shared memory or mutexes. Event groups are a synchronization mechanism provided by FreeRTOS that allow tasks to wait for a group of related tasks to complete; software timers can be used to execute tasks after a specified time, or to execute tasks periodically; queues and message buffers are used for message passing and data exchange between tasks.

[0045] The resource coordination module divides the system's resources into different resource pools and dynamically adjusts resource allocation according to the needs of the subsystems. Different resource scheduling algorithms can be introduced and access rights and policies can be set. During communication and data exchange, data flow management (managing data flow between subsystems through a unified data exchange format and protocol), message queues and event-driven mechanisms (managing communication between subsystems through message queues or event-driven mechanisms), and data consistency and synchronization mechanisms (when multiple subsystems need to access shared data, the coordination module needs to ensure data consistency and synchronization) are adopted. Through real-time monitoring of the system status, it can respond quickly to changes in subsystem load, failures, or task delays. It can dynamically adjust scheduling strategies, reallocate tasks, or temporarily adjust resource allocation plans to ensure that subsystems can always collaborate smoothly.

[0046] Through the above mechanisms, FreeRTOS can effectively manage the execution order of tasks and resource access, ensuring the real-time and stability of coordination and cooperation between various systems. Users can choose appropriate synchronization and scheduling strategies according to the needs of specific application scenarios.

[0047] In another exemplary embodiment of the present application, the human-computer interaction module uses an industrial-grade serial port screen and is designed with a human-computer interaction interface, allowing the user to monitor and control the system through the human-computer interaction interface; Figure 2 As shown in the figure, the human-computer interaction interface includes the main display area, the status prompt area and the equipment control area; the main display area is used to display real-time data and the control panel. Users can start and stop tasks and adjust priorities through the control panel operation; Figure 2In the embodiment shown, the main display area also includes a customizable extension area, and the user can operate the start and stop and priority adjustment of the management task through the customizable extension area. The status prompt area is used to display the communication status, system power, communication mode and external device type; the device control area is used for users to select and delete connected external devices; the external device includes an external sensor. In another optional embodiment, the human-computer interaction module uses an APP software connected by Bluetooth / wifi to display the human-computer interaction interface.

[0048] certainly, Figure 1~Figure 2 The system and human-computer interaction interface architecture shown are only exemplary and can be omitted according to actual needs when implementing different functions. Figure 1 The system shown or Figure 2 One or at least two components of the human-computer interaction interface shown.

[0049] The above-mentioned intelligent collaborative control system provided in this application can automatically perform monitoring, decision-making and control tasks in a dynamic environment. Compared with the existing technology, this system has the following significant advantages: (1) Real-time data processing and instant response: The system has the ability to receive and process data from various sensors in real time. Through the high-speed communication perception module, it ensures rapid data transmission and real-time feedback, thereby enhancing the system's response rate to environmental changes.

[0050] (2) Flexible task management: The system supports multiple transmission protocols and data formats, and users can customize data transmission methods according to specific needs. This flexibility ensures that the system is compatible with a variety of devices and sensors and adapts to different industrial application scenarios.

[0051] (3) Intelligent decision-making capabilities: By combining hierarchical reinforcement learning and game theory decision-making modules, it is possible to perform intelligent task planning based on complex environment and state information, automatically assign tasks and optimize execution strategies. Compared with traditional rule-based driving methods, this intelligent decision-making process is more adaptable to changing and complex operational requirements.

[0052] (4) Efficient resource scheduling and coordination: FreeRTOS is used to implement task management and coordination, and a priority scheduling strategy is adopted to ensure that high-priority tasks can be executed in a timely manner while avoiding resource conflicts and task starvation problems. This efficient task scheduling mechanism significantly improves the overall performance and stability of the system.

[0053] (5) Dynamic monitoring and adjustment: The monitoring and feedback module integrates statistical and machine learning algorithms to continuously monitor system performance and promptly detect and handle abnormal situations. This dynamic adjustment capability is more adaptable to the ever-changing working environment than traditional static monitoring methods.

[0054] (6) Friendly human-computer interaction interface: Through the intuitive human-computer interaction interface, users can easily monitor system status and adjust parameters, thereby improving user experience. This design reduces the user's learning cost and improves operational efficiency.

[0055] (7) Improved security and reliability: The system adopts advanced encryption standards and efficient compression technology to ensure the security and efficiency of data during transmission. It is very suitable for application scenarios in industrial environments with strict requirements on security and reliability.

[0056] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the functions of each module in an intelligent collaborative control system provided in the above embodiment can be realized.

[0057] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0058] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0059] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0060] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0061] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0062] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0063] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0064] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0065] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. An intelligent collaborative control system, characterized in that: include: Communication perception module, intelligent decision-making module, decision execution module, resource coordination module, monitoring and feedback module and human-computer interaction module; The communication sensing module is used to access external sensors and acquire, preprocess and store external sensor data based on a user-defined transmission protocol; The intelligent decision-making module is used to obtain external sensor data from the communication perception module, and according to the external sensor data, perform task planning and real-time decision-making by combining hierarchical reinforcement learning and game theory to obtain decision instructions; the decision instructions include program instructions for implementing corresponding subtasks; The decision execution module is used to receive the decision instruction of the intelligent decision module, control each subsystem to perform corresponding operations according to the decision instruction, and send the execution result to the monitoring and feedback module; The monitoring and feedback module is used to continuously monitor the internal state of the system and the execution result, and display the internal state of the system and the execution result to the user through the human-computer interaction module; The resource coordination module is used to manage the cooperation of each subsystem, maximize the efficiency of the control system, and handle resource scheduling and resource conflicts when each subsystem executes subtasks.

2. The intelligent collaborative control system according to claim 1, characterized in that: The communication perception module has multiple transmission paths including Bluetooth transmission, WIFI transmission and wired transmission, and can receive data information collected by various types of external sensors through different transmission means and pre-process and store the data information; the user-defined transmission protocol of the communication perception module adopts a strong encryption standard to ensure the security of data during transmission, and uses an encryption algorithm to protect the data content; The user-defined transmission protocol also uses an efficient compression algorithm to reduce the size of the transmitted data and improve the transmission speed; the user-defined transmission protocol also adopts multi-threaded asynchronous transmission technology to improve the efficiency of data transmission; the user-defined transmission protocol also uses efficient encoding and serialization technology to reduce data overhead during transmission.

3. The intelligent collaborative control system according to claim 1, characterized in that: The intelligent decision-making module uses hierarchical reinforcement learning based on external sensor data to decompose complex target tasks into a series of simple subtasks, uses the cooperative game model in game theory to allocate subtasks, and combines Q-Learning and game theory to provide optimal strategy planning for the entire system to obtain decision instructions; When optimizing cooperative game models, use the policy gradient method to improve the strategy, adjust the learning rate, discount factor, and other model hyperparameters to improve performance, or use experience replay to improve data efficiency and learning stability.

4. The intelligent collaborative control system according to claim 1, characterized in that: The decision execution module includes an industrial-grade microcontroller unit and its peripheral circuits, wherein the industrial-grade microcontroller unit has a digital signal processing unit and a floating-point operation unit; the decision execution module can control each subsystem to perform corresponding operations to implement the decision according to the decision instructions given by the intelligent decision module, and send the execution results of the decision to the monitoring and feedback module.

5. The intelligent collaborative control system according to claim 1, characterized in that: The monitoring and feedback module is used to continuously monitor the internal state of the system and the execution results of the decisions, and display the internal state of the system and the execution results to the user through the human-computer interaction module; the monitoring and feedback module is also used to define performance indicators and perform benchmark tests regularly according to the specific needs of the system to evaluate whether the performance of the system meets the expected standards, and is also used to monitor the system performance indicators in real time and quickly discover performance bottlenecks; the monitoring and feedback module is also used to combine statistical methods and machine learning algorithms to learn and identify normal modes and abnormal modes, set thresholds for key parameters, trigger alarms when parameters exceed the thresholds, and notify users through the alarm system of the human-computer interaction module when an abnormality or performance degradation is detected.

6. The intelligent collaborative control system according to claim 1, characterized in that: The resource coordination module is used to coordinate and schedule the workflow between subsystems, and to handle potential resource competition, time conflicts and priority conflicts among subsystems to maximize the efficiency of the control system; the resource coordination module uses the real-time operating system FreeRTOS, and adopts a scheduling strategy based on time slice rotation and priority preemption. Different priorities are assigned according to the importance of tasks. Tasks with higher priorities are called for resource execution first, and each task will be placed back at the end of the ready queue after running a time slice to ensure that other tasks of the same priority have a chance to execute.

7. The intelligent collaborative control system according to claim 1, characterized in that: The human-computer interaction module uses an industrial-grade serial port screen and is designed with a human-computer interaction interface, allowing users to monitor and control the system through the human-computer interaction interface; the human-computer interaction interface includes a main display area, a status prompt area and a device control area; the main display area is used to display real-time data and a control panel, and users can start and stop tasks and adjust priorities through control panel operations; the status prompt area is used to display communication status, system power, communication mode and external device type; the device control area is used for users to select and delete connected external devices; the external devices include external sensors.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the intelligent collaborative control system according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the intelligent collaborative control system described in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the intelligent collaborative control system described in any one of claims 1 to 6 is implemented.

Images