EtherCAT motor control system based on RK3568 processor

Abstract

The invention discloses an EtherCAT motor control system based on an RK3568 processor, through integration of a DeepSeek AI inference engine, the system can analyze state data of an EtherCAT motor in real time, such as rotating speed, current, temperature and the like, and output control parameter adjustment suggestions, an EtherCAT motor control algorithm dynamically adjusts the rotating speed of the motor according to the suggestions, more accurate and more intelligent control is realized, and the system is suitable for popularization and application. The real-time scheduling optimization module dynamically adjusts the scheduling priority of an EtherCAT motor control algorithm in an operating system according to an output result of a DeepSeek inference engine, and when a high load or a key task is executed, the scheduling priority of the control algorithm is improved, timely execution of a control instruction is ensured, and the real-time performance of the system is guaranteed. The real-time log processing module converts the EtherCAT motor operation log data into the CSV format, and the CSV format data is easy to store, transmit and analyze, so that the data processing efficiency and accuracy are improved, and the EtherCAT motor control real-time performance and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intrapartum ultrasonic analysis, and in particular to an EtherCAT motor control system based on an RK3568 processor. Background Art

[0002] Currently, in the field of industrial control, traditional motor control systems usually rely on fixed control algorithms or cloud computing. However, although relying on fixed control algorithms can improve control accuracy to a certain extent, it lacks intelligent adaptability and is difficult to optimize and adjust according to real-time operating conditions. In addition, although relying on cloud computing can provide intelligent optimization capabilities, it is limited by data transmission bandwidth and network latency, resulting in control response being affected by network latency and unable to meet high real-time requirements. Summary of the Invention

[0003] In view of this, the present invention proposes an EtherCAT motor control system based on the RK3568 processor, which can effectively solve the defects of the existing technology such as lack of intelligent adaptability and inability to meet high real-time requirements.

[0004] The technical solution of the present invention is achieved as follows:

[0005] An EtherCAT motor control system based on the RK3568 processor, including:

[0006] An integration module for integrating an EtherCAT motor control algorithm and a DeepSeek AI inference engine into the RK3568 processor. The EtherCAT motor control algorithm is used to read speed values ​​from the file system and dynamically adjust the motor speed. The DeepSeek AI inference engine is used to analyze EtherCAT motor status data and output control parameter adjustment suggestions.

[0007] A real-time log processing module is used to obtain EtherCAT motor operation log data and convert it into CSV format as input to the DeepSeek inference engine;

[0008] The real-time scheduling optimization module is used to adjust the scheduling priority of the EtherCAT motor control algorithm in the operating system based on the output results of the DeepSeek inference engine.

[0009] As a further optional solution of the EtherCAT motor control system based on the RK3568 processor, the EtherCAT motor control algorithm reads the speed value in the file system and dynamically adjusts the motor speed, specifically including:

[0010] Provide a speed value file located in the Linux file system, the file storing a speed value for controlling the motor speed, the speed value file being located in the / sys / class / igh / speed path;

[0011] The EtherCAT motor control algorithm reads the content of the speed value file;

[0012] Using the inotify mechanism of the Linux kernel to monitor changes in the speed value file;

[0013] When the content of the speed value file changes, the callback function is triggered to read the new speed value;

[0014] Based on the new speed value read, the process data object is sent to the motor controller via the EtherCAT protocol to dynamically adjust the motor speed.

[0015] As a further option for the RK3568 processor-based EtherCAT motor control system, the DeepSeek AI inference engine analyzes EtherCAT motor status data and outputs control parameter adjustment suggestions, specifically including:

[0016] Receive EtherCAT motor status data converted by the real-time log processing module;

[0017] The DeepSeek AI inference engine analyzes and processes the received EtherCAT motor status data, using a pre-trained deep learning model to evaluate and predict the EtherCAT motor status.

[0018] Based on the analysis and processing results, the DeepSeek AI inference engine outputs adjustment suggestions for the motor control parameters, including adjustment values ​​for the PID control parameters and the target speed.

[0019] The output control parameter adjustment suggestions are provided to the EtherCAT motor control program to optimize the motor control.

[0020] As a further optional solution for the EtherCAT motor control system based on the RK3568 processor, the real-time log processing module obtains the EtherCAT motor operation log data and converts it into CSV format, specifically including:

[0021] Real-time acquisition of log file data during the operation of the EtherCAT motor, which records key parameters and status information of the motor during operation;

[0022] Import the acquired log file data into the real-time log processing module;

[0023] The real-time log processing module parses the log file data and extracts key data items related to the motor's operating status;

[0024] Format the extracted key data items according to the predetermined CSV format to generate a structured motor status data file;

[0025] Output the generated motor status data file in CSV format.

[0026] As a further optional solution for the EtherCAT motor control system based on the RK3568 processor, the real-time log processing module parses the log file data and extracts key data items related to the motor operating status, including:

[0027] The real-time log processing module receives EtherCAT motor operation log file data, wherein the log file data contains original record information during the motor operation process;

[0028] Preprocessing the received log file data includes removing invalid characters, formatting log entries, and unifying timestamp formats;

[0029] Using predefined regular expressions, the preprocessed log file data is parsed line by line to identify and extract key data items related to the motor operating status, including motor speed, current value, temperature value, position information and operating status flag.

[0030] As a further optional solution of the EtherCAT motor control system based on the RK3568 processor, the specific steps of generating the predefined regular expression include:

[0031] Analyze sample data from EtherCAT motor log files to determine the location, format, and change patterns of key data items in the log entries;

[0032] A set of regular expression rules is written according to the analysis results, and each regular expression rule corresponds to a key data item related to the motor operating status.

[0033] As a further optional solution for the EtherCAT motor control system based on the RK3568 processor, the real-time scheduling optimization module adjusts the scheduling priority of the EtherCAT motor control algorithm in the operating system based on the output results of the DeepSeek inference engine, specifically including:

[0034] Receive motor control parameter adjustment suggestions output by the DeepSeek inference engine;

[0035] Identify the process or thread of the EtherCAT motor control algorithm in the operating system;

[0036] Dynamically adjust the scheduling priority of the EtherCAT motor control algorithm in the operating system based on the urgency or importance of the control parameter adjustment suggestions output by the DeepSeek inference engine;

[0037] Use the operating system's command line tools to set the priority of the EtherCAT motor control algorithm process or thread.

[0038] As a further optional solution of the EtherCAT motor control system based on the RK3568 processor, the process or thread of identifying the EtherCAT motor control algorithm in the operating system specifically includes:

[0039] Use the process management or thread management tools provided by the operating system to obtain the identification information of the EtherCAT motor control algorithm process or thread, including the process ID, thread ID, and name;

[0040] The obtained identification information is stored in a preset data structure.

[0041] An EtherCAT motor control method based on the RK3568 processor specifically includes:

[0042] Integrating an EtherCAT motor control algorithm and a DeepSeek AI inference engine into the RK3568 processor. The EtherCAT motor control algorithm is used to read speed values ​​from the file system and dynamically adjust the motor speed. The DeepSeek AI inference engine is used to analyze EtherCAT motor status data and output control parameter adjustment suggestions.

[0043] Acquire EtherCAT motor operation log data in real time and convert it into CSV format as input for the DeepSeek inference engine;

[0044] The DeepSeek inference engine outputs control parameter adjustment suggestions;

[0045] According to the control parameter adjustment suggestion, the scheduling priority of the EtherCAT motor control algorithm in the operating system is dynamically adjusted.

[0046] The beneficial effects of the present invention are as follows: by integrating the DeepSeek AI reasoning engine, the system can analyze EtherCAT motor status data, such as speed, current, temperature, etc., in real time, and output control parameter adjustment suggestions. The EtherCAT motor control algorithm dynamically adjusts the motor speed according to these suggestions, achieving more precise and intelligent control, and improving the system response speed and stability. The real-time scheduling optimization module dynamically adjusts the scheduling priority of the EtherCAT motor control algorithm in the operating system according to the output results of the DeepSeek reasoning engine. When high load or critical tasks are executed, the scheduling priority of the control algorithm is improved to ensure the timely execution of control instructions and guarantee the real-time performance of the system. The real-time log processing module converts the EtherCAT motor operation log data into CSV format. CSV format data is easy to store, transmit and parse, which improves the efficiency and accuracy of data processing, thereby improving the real-time performance and accuracy of EtherCAT motor control. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0048] Figure 1 This is a schematic diagram of the composition of an EtherCAT motor control system based on the RK3568 processor of the present invention;

[0049] Figure 2 The figure is a flow chart of an EtherCAT motor control method based on the RK3568 processor of the present invention. DETAILED DESCRIPTION

[0050] The following is a clear and complete description of the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0051] refer to Figures 1 to 2 , an EtherCAT motor control system based on the RK3568 processor, including:

[0052] An integration module for integrating an EtherCAT motor control algorithm and a DeepSeek AI inference engine into the RK3568 processor. The EtherCAT motor control algorithm is used to read speed values ​​from the file system and dynamically adjust the motor speed. The DeepSeek AI inference engine is used to analyze EtherCAT motor status data and output control parameter adjustment suggestions.

[0053] A real-time log processing module is used to obtain EtherCAT motor operation log data and convert it into CSV format as input to the DeepSeek inference engine;

[0054] The real-time scheduling optimization module is used to adjust the scheduling priority of the EtherCAT motor control algorithm in the operating system based on the output results of the DeepSeek inference engine.

[0055] In this embodiment, by integrating the DeepSeek AI inference engine, the system can analyze EtherCAT motor status data, such as speed, current, temperature, etc., in real time, and output control parameter adjustment suggestions. The EtherCAT motor control algorithm dynamically adjusts the motor speed according to these suggestions to achieve more precise and intelligent control, improve system response speed and stability, and the real-time scheduling optimization module dynamically adjusts the scheduling priority of the EtherCAT motor control algorithm in the operating system according to the output results of the DeepSeek inference engine. When high load or critical tasks are executed, the scheduling priority of the control algorithm is increased to ensure the timely execution of control instructions and guarantee the real-time performance of the system. The real-time log processing module converts the EtherCAT motor operation log data into CSV format. CSV format data is easy to store, transmit and parse, which improves the efficiency and accuracy of data processing, thereby improving the real-time and accuracy of EtherCAT motor control.

[0056] It should be noted that the EtherCAT motor control algorithm and DeepSeek AI inference engine are integrated into the RK3568 processor. The specific steps include:

[0057] Build an operating system and development environment suitable for running the EtherCAT motor control algorithm and DeepSeek AI inference engine on the RK3568 processor to ensure that the processor has the necessary computing power and interface resources;

[0058] Deploy the executable file of the EtherCAT motor control algorithm to the RK3568 processor and configure the algorithm to read the speed value from the file system as the reference input for motor speed adjustment;

[0059] Deploy the DeepSeek AI inference engine model file to the RK3568 processor and configure the inference engine to receive EtherCAT motor status data, including but not limited to key parameters such as motor speed, current, and temperature. Implement the inference engine's analysis logic, enabling it to process the received motor status data and output control parameter adjustment suggestions to optimize the performance of the motor control algorithm. The DeepSeek AI inference engine's analysis logic is based on a deep learning model trained with a large amount of historical motor status data. This model can accurately identify the motor's operating status and output effective control parameter adjustment suggestions.

[0060] Establish a data interaction interface between the EtherCAT motor control algorithm and the DeepSeek AI inference engine to ensure that they can share data in real time. Configure the data interaction interface so that the EtherCAT motor control algorithm can send motor status data to the DeepSeek AI inference engine and receive control parameter adjustment suggestions output by the inference engine.

[0061] Preferably, the EtherCAT motor control algorithm reads the speed value in the file system and dynamically adjusts the motor speed, specifically including:

[0062] Provide a speed value file located in the Linux file system, the file storing a speed value for controlling the motor speed, the speed value file being located in the / sys / class / igh / speed path;

[0063] The EtherCAT motor control algorithm reads the content of the speed value file;

[0064] Using the inotify mechanism of the Linux kernel to monitor changes in the speed value file;

[0065] When the content of the speed value file changes, the callback function is triggered to read the new speed value;

[0066] Based on the new speed value read, the process data object is sent to the motor controller via the EtherCAT protocol to dynamically adjust the motor speed.

[0067] In this embodiment, by directly reading the speed value file in the Linux file system, the EtherCAT motor control algorithm can obtain the set value of the motor speed in real time. This method avoids complex network communication or data parsing processes and improves the real-time performance of speed value acquisition. When the content of the speed value file changes, the inotify mechanism of the Linux kernel can immediately trigger the callback function to read the new speed value. According to the new speed value, the algorithm quickly sends the process data object to the motor controller through the EtherCAT protocol to achieve dynamic adjustment of the motor speed. This dynamic adjustment capability enables the motor to quickly respond to changes in external conditions or control requirements, thereby improving the flexibility and response speed of the system. The inotify mechanism is a Efficient file monitoring can detect changes in file content in real time, ensuring that speed value updates are captured promptly. Compared to inefficient methods such as polling, the inotify mechanism reduces unnecessary resource consumption and improves system stability. The speed value file is located in the standard path of the Linux file system ( / sys / class / igh / speed), facilitating integration with other systems or tools. This standardized interface reduces the complexity of system integration and improves development efficiency. The EtherCAT motor control algorithm is separated from the speed value file reading and monitoring mechanism, achieving a modular design. This design makes the system easy to maintain and expand. When the algorithm needs to be modified or upgraded, it will not affect the speed value reading and monitoring mechanism.

[0068] Preferably, the DeepSeek AI inference engine analyzes EtherCAT motor status data and outputs control parameter adjustment suggestions, specifically including:

[0069] Receive EtherCAT motor status data converted by the real-time log processing module;

[0070] The DeepSeek AI inference engine analyzes and processes the received EtherCAT motor status data, using a pre-trained deep learning model to evaluate and predict the EtherCAT motor status.

[0071] Based on the analysis and processing results, the DeepSeek AI inference engine outputs adjustment suggestions for the motor control parameters, including adjustment values ​​for the PID control parameters and the target speed.

[0072] The output control parameter adjustment suggestions are provided to the EtherCAT motor control program to optimize the motor control.

[0073] In this embodiment, the DeepSeek AI inference engine uses a pre-trained deep learning model to analyze and process EtherCAT motor status data, capturing the complex patterns and underlying laws in motor operation. The deep learning model has powerful feature extraction and classification capabilities, accurately assessing the motor's current state and predicting its possible future operating state. The inference engine receives EtherCAT motor status data converted by the real-time log processing module in real time, ensuring the timeliness and accuracy of analysis and processing. Real-time data analysis enables the system to quickly respond to changes in motor status and adjust control parameters in a timely manner to keep the motor operating in optimal conditions. Based on the analysis and processing results, the DeepSeek AI inference engine outputs adjustment suggestions for the PID control parameters to help optimize the motor's dynamic response and stability. Intelligent adjustment of the PID control parameters can reduce overshoot, oscillation, and other phenomena during motor operation, improving control accuracy and efficiency. The inference engine also outputs adjustment suggestions for the target speed. Based on the motor's current state and prediction results, the motor speed is dynamically adjusted to adapt to different operating conditions. Intelligent adjustment of the target speed can optimize motor energy consumption, improve production efficiency, and extend the motor's service life.

[0074] Preferably, the real-time log processing module obtains the EtherCAT motor operation log data and converts it into CSV format, specifically including:

[0075] Real-time acquisition of log file data during the operation of the EtherCAT motor, which records key parameters and status information of the motor during operation;

[0076] Import the acquired log file data into the real-time log processing module;

[0077] The real-time log processing module parses the log file data and extracts key data items related to the motor's operating status;

[0078] Format the extracted key data items according to the predetermined CSV format to generate a structured motor status data file;

[0079] Output the generated motor status data file in CSV format.

[0080] In this embodiment, the real-time log processing module parses the log file data and extracts key data items related to the motor operating status, such as speed, current, temperature, etc. The extraction of key data items makes the data more focused, reduces redundant information, and improves the efficiency of data processing; the real-time log processing module can obtain the log file data during the operation of the EtherCAT motor in real time and process it immediately. Real-time processing ensures the timeliness and accuracy of the data, allowing the system to quickly respond to changes in the motor status.

[0081] Preferably, the real-time log processing module parses the log file data and extracts key data items related to the motor operating status, specifically including:

[0082] The real-time log processing module receives EtherCAT motor operation log file data, wherein the log file data contains original record information during the motor operation process;

[0083] Preprocessing the received log file data includes removing invalid characters, formatting log entries, and unifying timestamp formats;

[0084] Using predefined regular expressions, the preprocessed log file data is parsed line by line to identify and extract key data items related to the motor operating status, including motor speed, current value, temperature value, position information and operating status flag.

[0085] In this embodiment, the real-time log processing module pre-processes the received log file data, first removing invalid characters such as garbled characters and special symbols to ensure the purity and accuracy of the data. The removal of invalid characters avoids errors and interference in the subsequent parsing process and improves the reliability of data processing. The module formats the log entries so that each log record has a unified format and structure. The formatted log entries facilitate subsequent parsing and extraction of key data items, thereby improving the efficiency of data processing. The module unifies the timestamp format in the log files to ensure the accuracy and comparability of time information. The unified timestamp format facilitates subsequent data analysis and trend prediction, providing strong support for the monitoring and evaluation of the motor operating status. The pre-processed log file data is parsed line by line using a predefined regular expression to identify and extract key data items related to the motor operating status. This can accurately identify key information in the log and improve the accuracy and efficiency of data extraction. The real-time log processing module greatly reduces the workload and time cost of manual processing by automatically parsing and extracting key data items. Automated processing improves the efficiency of data processing while reducing the possibility of human errors and omissions.

[0086] Preferably, the specific steps of generating the predefined regular expression include:

[0087] Analyze sample data from EtherCAT motor log files to determine the location, format, and change patterns of key data items in the log entries;

[0088] A set of regular expression rules is written according to the analysis results, and each regular expression rule corresponds to a key data item related to the motor operating status.

[0089] In this embodiment, by analyzing the sample data of the EtherCAT motor log file, the position, format and change pattern of the key data items in the log entries are determined, and customized regular expression rules are written. These regular expression rules can accurately match the key data items in the log entries, ensuring the accuracy and efficiency of data extraction; each regular expression rule corresponds to a key data item related to the motor operating status, making the data parsing process more efficient. Compared with traditional string processing methods, regular expressions can locate and extract the required data items more quickly, thereby improving the efficiency of data processing; since regular expressions are written based on the analysis results of the log sample data, they can flexibly adapt to log files of different formats and structures. When the log format changes, only the regular expression rules need to be adjusted accordingly to continue to achieve accurate extraction of key data items; in the process of extracting key data items, regular expressions can also be used for data cleaning and verification. By matching specific formats and patterns, invalid or erroneous data items can be filtered out to ensure the quality of the extracted data is reliable; the automated regular expression matching process reduces the workload and time cost of manual processing, while reducing the possibility of human error.

[0090] Preferably, the real-time scheduling optimization module adjusts the scheduling priority of the EtherCAT motor control algorithm in the operating system according to the output result of the DeepSeek inference engine, specifically including:

[0091] Receive motor control parameter adjustment suggestions output by the DeepSeek inference engine;

[0092] Identify the process or thread of the EtherCAT motor control algorithm in the operating system;

[0093] Dynamically adjust the scheduling priority of the EtherCAT motor control algorithm in the operating system based on the urgency or importance of the control parameter adjustment suggestions output by the DeepSeek inference engine;

[0094] Use the operating system's command line tools to set the priority of the EtherCAT motor control algorithm process or thread.

[0095] In this embodiment, the real-time scheduling optimization module can receive the motor control parameter adjustment suggestions output by the DeepSeek inference engine, and dynamically adjust the scheduling priority of the EtherCAT motor control algorithm in the operating system according to the urgency or importance of these suggestions. This dynamic adjustment mechanism enables the system to respond to changes in control requirements in real time, ensuring that key control tasks can be executed in a timely manner, thereby improving the overall response speed of the system; by adjusting the scheduling priority, the system can more reasonably allocate CPU resources, ensuring that the EtherCAT motor control algorithm can obtain sufficient computing resources when needed, avoiding performance degradation due to resource competition, and dynamically adjusting the scheduling priority can reduce the execution delay and jitter of the EtherCAT motor control algorithm, ensuring the timeliness and accuracy of the motor control instructions, which helps to maintain the stability of the motor operation and reduce motor performance fluctuations or failures caused by control delays; when the system load is heavy or a fault occurs, the real-time scheduling optimization module can automatically increase the priority of key control tasks to ensure that these tasks can be executed first.

[0096] Preferably, the identifying process or thread of the EtherCAT motor control algorithm in the operating system specifically includes:

[0097] Use the process management or thread management tools provided by the operating system to obtain the identification information of the EtherCAT motor control algorithm process or thread, including the process ID, thread ID, and name;

[0098] The obtained identification information is stored in a preset data structure.

[0099] In this embodiment, through the process management or thread management tool provided by the operating system, the identification information of the EtherCAT motor control algorithm process or thread, including the process ID, thread ID and name, can be accurately obtained. These identification information are the basis for subsequent scheduling priority adjustment, ensuring the accuracy and pertinence of the adjustment operation. At the same time, it also avoids resource conflicts between different processes or threads and improves the utilization efficiency of system resources; the obtained identification information is stored in a preset data structure, such as a hash table, dictionary or database, etc., to facilitate subsequent rapid query and use. This storage method improves the efficiency of data access and reduces system overhead. The preset data structure makes the management of identification information more efficient. It is orderly and efficient, facilitating operations such as adding, deleting, modifying, and checking. At the same time, it also facilitates system maintenance and upgrades, improving the system's maintainability and scalability. Through the stored identification information, the system can obtain the status of the EtherCAT motor control algorithm process or thread in real time, such as operating status, resource occupancy, etc., which provides real-time data support for dynamic scheduling and priority adjustment, ensuring the timeliness and effectiveness of the adjustment operation. Based on the obtained identification information and process or thread status, the system can flexibly adjust the scheduling strategy, such as increasing or decreasing the scheduling priority, adjusting the time slice size, etc. This flexibility enables the system to adapt to the performance requirements of different application scenarios, improving the system's adaptability and response speed.

[0100] An EtherCAT motor control method based on the RK3568 processor specifically includes:

[0101] Integrating an EtherCAT motor control algorithm and a DeepSeek AI inference engine into the RK3568 processor. The EtherCAT motor control algorithm is used to read speed values ​​from the file system and dynamically adjust the motor speed. The DeepSeek AI inference engine is used to analyze EtherCAT motor status data and output control parameter adjustment suggestions.

[0102] Acquire EtherCAT motor operation log data in real time and convert it into CSV format as input for the DeepSeek inference engine;

[0103] The DeepSeek inference engine outputs control parameter adjustment suggestions;

[0104] According to the control parameter adjustment suggestion, the scheduling priority of the EtherCAT motor control algorithm in the operating system is dynamically adjusted.

[0105] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An EtherCAT motor control system based on RK3568 processor, characterized in that: include: An integration module for integrating an EtherCAT motor control algorithm and a DeepSeek AI inference engine into the RK3568 processor. The EtherCAT motor control algorithm is used to read speed values ​​from the file system and dynamically adjust the motor speed. The DeepSeek AI inference engine is used to analyze EtherCAT motor status data and output control parameter adjustment suggestions. A real-time log processing module is used to obtain EtherCAT motor operation log data and convert it into CSV format as input to the DeepSeek inference engine; The real-time scheduling optimization module is used to adjust the scheduling priority of the EtherCAT motor control algorithm in the operating system based on the output results of the DeepSeek inference engine.

2. The EtherCAT motor control system based on the RK3568 processor according to claim 1, characterized in that: The EtherCAT motor control algorithm reads the speed value in the file system and dynamically adjusts the motor speed. Specifically, it includes: Provide a speed value file located in the Linux file system, the file storing a speed value for controlling the motor speed, the speed value file being located in the / sys / class / igh / speed path; The EtherCAT motor control algorithm reads the content of the speed value file; Using the inotify mechanism of the Linux kernel to monitor changes in the speed value file; When the content of the speed value file changes, the callback function is triggered to read the new speed value; Based on the new speed value read, the process data object is sent to the motor controller via the EtherCAT protocol to dynamically adjust the motor speed.

3. The EtherCAT motor control system based on the RK3568 processor according to claim 2, characterized in that: The DeepSeek AI inference engine analyzes EtherCAT motor status data and outputs control parameter adjustment suggestions, including: Receive EtherCAT motor status data converted by the real-time log processing module; The DeepSeek AI inference engine analyzes and processes the received EtherCAT motor status data, using a pre-trained deep learning model to evaluate and predict the EtherCAT motor status. Based on the analysis and processing results, the DeepSeek AI inference engine outputs adjustment suggestions for the motor control parameters, including adjustment values ​​for the PID control parameters and the target speed. The output control parameter adjustment suggestions are provided to the EtherCAT motor control program to optimize the motor control.

4. The EtherCAT motor control system based on the RK3568 processor according to claim 3, characterized in that: The real-time log processing module obtains the EtherCAT motor operation log data and converts it into CSV format, specifically including: Real-time acquisition of log file data during the operation of the EtherCAT motor, which records key parameters and status information of the motor during operation; Import the acquired log file data into the real-time log processing module; The real-time log processing module parses the log file data and extracts key data items related to the motor's operating status; Format the extracted key data items according to the predetermined CSV format to generate a structured motor status data file; Output the generated motor status data file in CSV format.

5. The EtherCAT motor control system based on the RK3568 processor according to claim 4, characterized in that: The real-time log processing module parses the log file data and extracts key data items related to the motor operating status, including: The real-time log processing module receives EtherCAT motor operation log file data, wherein the log file data contains original record information during the motor operation process; Preprocessing the received log file data includes removing invalid characters, formatting log entries, and unifying timestamp formats; Using predefined regular expressions, the preprocessed log file data is parsed line by line to identify and extract key data items related to the motor operating status, including motor speed, current value, temperature value, position information and operating status flag.

6. The EtherCAT motor control system based on the RK3568 processor according to claim 5, characterized in that: The specific steps of generating the predefined regular expression include: Analyze sample data from EtherCAT motor log files to determine the location, format, and change patterns of key data items in the log entries; A set of regular expression rules is written according to the analysis results, and each regular expression rule corresponds to a key data item related to the motor operating status.

7. The EtherCAT motor control system based on the RK3568 processor according to claim 6, characterized in that: The real-time scheduling optimization module adjusts the scheduling priority of the EtherCAT motor control algorithm in the operating system based on the output results of the DeepSeek inference engine, specifically including: Receive motor control parameter adjustment suggestions output by the DeepSeek inference engine; Identify the process or thread of the EtherCAT motor control algorithm in the operating system; Dynamically adjust the scheduling priority of the EtherCAT motor control algorithm in the operating system based on the urgency or importance of the control parameter adjustment suggestions output by the DeepSeek inference engine; Use the operating system's command line tools to set the priority of the EtherCAT motor control algorithm process or thread.

8. The EtherCAT motor control system based on the RK3568 processor according to claim 7, characterized in that: The process or thread of identifying the EtherCAT motor control algorithm in the operating system specifically includes: Use the process management or thread management tools provided by the operating system to obtain the identification information of the EtherCAT motor control algorithm process or thread, including the process ID, thread ID, and name; The obtained identification information is stored in a preset data structure.

9. An EtherCAT motor control method based on RK3568 processor, characterized in that: Specifically include: Integrating an EtherCAT motor control algorithm and a DeepSeek AI inference engine into the RK3568 processor. The EtherCAT motor control algorithm is used to read speed values ​​from the file system and dynamically adjust the motor speed. The DeepSeek AI inference engine is used to analyze EtherCAT motor status data and output control parameter adjustment suggestions. Acquire EtherCAT motor operation log data in real time and convert it into CSV format as input for the DeepSeek inference engine; The DeepSeek inference engine outputs control parameter adjustment suggestions; According to the control parameter adjustment suggestion, the scheduling priority of the EtherCAT motor control algorithm in the operating system is dynamically adjusted.

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