Ethercat motor control system based on RK3568 processor

Abstract

The application discloses an EtherCAT motor control system based on an RK3568 processor, which integrates a DeepSeek AI inference engine. The system can analyze EtherCAT motor state 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, realizes more accurate and intelligent control, improves the 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 task execution occurs, 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 EtherCAT motor operation log data into CSV format, and CSV format data is easy to store, transmit and parse, improving the efficiency and accuracy of data processing, thereby improving the real-time performance and accuracy of EtherCAT motor control.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of real-time ultrasound analysis, and in particular to an EtherCAT motor control system based on an RK3568 processor. BACKGROUND

[0002] At present, in the field of industrial control, traditional motor control systems usually rely on fixed control algorithms or cloud computing. However, although the fixed control algorithm can improve the control accuracy to a certain extent, it lacks intelligent adaptive ability and is difficult to optimize and adjust according to real-time working conditions. In addition, although cloud computing can provide intelligent optimization capability, it is limited by data transmission bandwidth and network delay, resulting in that the control response is affected by network delay and cannot meet the high real-time requirement. SUMMARY

[0003] Therefore, the application provides an EtherCAT motor control system based on an RK3568 processor, which can effectively solve the defects of lacking intelligent adaptive ability and being unable to meet the high real-time requirement in the prior art.

[0004] The technical scheme of the application is as follows:

[0005] The EtherCAT motor control system based on the RK3568 processor comprises:

[0006] An integration module is configured to integrate an EtherCAT motor control algorithm and a DeepSeek AI inference engine on the RK3568 processor, the EtherCAT motor control algorithm is configured to read speed values in a file system and dynamically adjust motor speed, and the DeepSeek AI inference engine is configured to analyze EtherCAT motor state data and output control parameter adjustment suggestions.

[0007] A real-time log processing module is configured to acquire EtherCAT motor operation log data and convert the EtherCAT motor operation log data into a CSV format as input of the DeepSeek inference engine.

[0008] A real-time scheduling optimization module is configured to adjust scheduling priority of the EtherCAT motor control algorithm in an operating system according to 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 speed values in a file system and dynamically adjusts motor speed, and specifically comprises:

[0010] A speed value file is provided in the Linux file system, which stores the speed value used to control the motor speed, and the speed value file is located at the / sys / class / igh / speed path;

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

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

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

[0014] According to the read new speed value, the process data object is sent to the motor controller through the EtherCAT protocol to dynamically adjust the speed of the motor.

[0015] As a further optional solution of the EtherCAT motor control system based on RK3568 processor, the DeepSeek AI inference engine analyzes EtherCAT motor state data and outputs control parameter adjustment suggestions, specifically including:

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

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

[0018] According to the analysis and processing results, the DeepSeek AI inference engine outputs adjustment suggestions for motor control parameters, including adjustment values of PID control parameters and adjustment values of target speed;

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

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

[0021] Real-time acquisition of log file data during the running process of the EtherCAT motor, the log file data records the key parameters and state information of the motor during running;

[0022] The obtained log file data is imported 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 operating state;

[0024] The extracted key data items are formatted according to the predetermined CSV format to generate a structured motor state data file;

[0025] The generated CSV format motor state data file is output.

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

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

[0028] The received log file data is preprocessed, including removing invalid characters, formatting log entries, and unifying timestamp format;

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

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

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

[0032] According to the analysis results, a set of regular expression rules is written, each regular expression rule corresponding to a key data item related to the motor operating state.

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

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

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

[0036] Adjust the urgency or importance of the control parameter adjustment suggestion output by the DeepSeek inference engine, and dynamically adjust the scheduling priority of the EtherCAT motor control algorithm in the operating system;

[0037] Set the priority of the process or thread of the EtherCAT motor control algorithm through the command line tool of the operating system.

[0038] As a further optional solution of the RK3568 processor-based EtherCAT motor control system, the identification of the process or thread of 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 process ID, thread ID and name;

[0040] Store the obtained identification information in a preset data structure.

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

[0042] Integrate the EtherCAT motor control algorithm and the DeepSeek AI inference engine on the RK3568 processor, the EtherCAT motor control algorithm is used to read the speed value in the file system and dynamically adjust the motor speed, and the DeepSeek AI inference engine is used to analyze the EtherCAT motor state data and output control parameter adjustment suggestions;

[0043] Real-time acquisition of EtherCAT motor running log data and conversion to CSV format as input of the DeepSeek inference engine;

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

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

[0046] The beneficial effects of the present application are: by integrating the DeepSeek AI inference engine, the system can analyze EtherCAT motor state data such as speed, current, temperature, etc. in real time, and output control parameter adjustment suggestions, and the EtherCAT motor control algorithm dynamically adjusts the motor speed according to these suggestions to realize more accurate 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, improves the scheduling priority of the control algorithm during high load or critical task execution, ensures the timely execution of control instructions, and guarantees the real-time performance of the system, and the real-time log processing module converts EtherCAT motor operation log data into CSV format, CSV format data is easy to store, transmit and parse, improves the efficiency and accuracy of data processing, thereby improving the real-time performance and accuracy of EtherCAT motor control. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0048] Fig. 1 The composition schematic diagram of an EtherCAT motor control system based on an RK3568 processor according to the present application is shown in the figure.

[0049] Fig. 2 The flowchart of an EtherCAT motor control method based on an RK3568 processor according to the present application is shown in the figure. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present application will be described in detail below. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0051] REFERENCE Figs. 1-2 An EtherCAT motor control system based on an RK3568 processor, comprising:

[0052] An integrated module for integrating an EtherCAT motor control algorithm and a DeepSeek AI inference engine on the RK3568 processor, the EtherCAT motor control algorithm for reading speed values in a file system and dynamically adjusting motor speed, and the DeepSeek AI inference engine for analyzing EtherCAT motor state data and outputting control parameter adjustment suggestions;

[0053] A real-time log processing module for obtaining EtherCAT motor operation log data and converting it into CSV format as input for the DeepSeek inference engine;

[0054] A real-time scheduling optimization module for adjusting the scheduling priority of the EtherCAT motor control algorithm in the operating system according to the output of the DeepSeek inference engine.

[0055] In this embodiment, by integrating the DeepSeek AI inference engine, the system can analyze EtherCAT motor state data such as speed, current, temperature, etc. in real time and output control parameter adjustment suggestions, and the EtherCAT motor control algorithm dynamically adjusts the motor speed according to these suggestions to achieve more accurate 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 of the DeepSeek inference engine, improves the scheduling priority of the control algorithm during high load or critical task execution, ensures timely execution of control instructions, and guarantees system real-time performance. The real-time log processing module converts EtherCAT motor operation log data into CSV format, and CSV format data is easy to store, transmit and parse, improving data processing efficiency and accuracy, thereby improving EtherCAT motor control real-time performance and accuracy.

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

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

[0058] Deploying the executable file of the EtherCAT motor control algorithm on the RK3568 processor, configuring the algorithm to read speed values in the file system, which are used as reference input for motor speed adjustment;

[0059] Deploy the model file of the DeepSeek AI inference engine on the RK3568 processor, configure the inference engine to receive EtherCAT motor status data, including but not limited to motor speed, current, temperature, and other key parameters, implement the analysis logic of the inference engine, so that it can process the received motor status data and output control parameter adjustment suggestions for optimizing the performance of the motor control algorithm, the analysis logic of the DeepSeek AI inference engine is based on a deep learning model trained by a large amount of historical motor status data, which can accurately identify the motor operating state 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 in the Linux file system, which stores the speed value used to control the motor speed, the speed value file is located in the / sys / class / igh / speed path;

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

[0064] Use 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, trigger the callback function to read the new speed value;

[0066] According to the read new speed value, send the process data object to the motor controller through the EtherCAT protocol to dynamically adjust the speed of the motor.

[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 analysis process, 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 trigger the callback function immediately 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, realizing the dynamic adjustment of the motor speed. This dynamic adjustment capability enables the motor to quickly respond to changes in external conditions or control requirements, improving the flexibility and response speed of the system. The inotify mechanism is an efficient file monitoring method that can detect changes in file content in real time, ensuring that the speed value update can be captured in time. Compared with 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), which is convenient for 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 reading and monitoring mechanism of the speed value file, realizing modular design. This design makes the system easy to maintain and extend, and when the algorithm needs to be modified or upgraded, it will not affect the reading and monitoring mechanism of the speed value.

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

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

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

[0071] According to the analysis and processing results, the DeepSeek AI inference engine outputs adjustment suggestions for motor control parameters, including adjustment values of PID control parameters and adjustment values of target speed;

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

[0073] In this embodiment, the DeepSeek AI inference engine utilizes a pre-trained deep learning model to analyze and process EtherCAT motor state data, capable of capturing complex patterns and potential laws in motor operation. The deep learning model has strong feature extraction and classification capabilities, enabling accurate assessment of the current motor state and prediction of future possible operating states. The inference engine receives EtherCAT motor state 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 state, adjust control parameters in a timely manner, and maintain optimal motor operation. Based on the analysis and processing results, the DeepSeek AI inference engine outputs adjustment suggestions for PID control parameters, helping to optimize motor dynamic response and stability. Intelligent adjustment of PID control parameters can reduce overshoot, oscillation, and other phenomena during motor operation, improving control precision and efficiency. The inference engine also outputs adjustment suggestions for target speed, dynamically adjusting motor speed to adapt to different working conditions based on the current motor state and prediction results. Intelligent adjustment of target speed can optimize motor energy consumption, improve production efficiency, and extend motor service life.

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

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

[0076] Importing the obtained 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 operating state;

[0078] The extracted key data items are formatted according to the predetermined CSV format to generate structured motor state data files;

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

[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 state, such as speed, current, temperature, etc. The extraction of key data items makes the data more focused, reduces redundant information, and improves data processing efficiency. The real-time log processing module can acquire log file data during EtherCAT motor operation in real time and immediately process it. Real-time processing ensures the timeliness and accuracy of data, enabling the system to quickly respond to changes in motor state.

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

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

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

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

[0085] In this embodiment, the real-time log processing module preprocesses the received log file data, first removes invalid characters such as garbled characters, special symbols, etc., to ensure data purity and accuracy. The removal of invalid characters avoids errors and interference in the subsequent parsing process, improving the reliability of data processing. The module formats the log entries to ensure uniform format and structure for each log record. The formatted log entries facilitate subsequent parsing and extraction of key data items, improving data processing efficiency. The module unifies the timestamp format in the log file to ensure the accuracy and comparability of time information. The unified timestamp format facilitates subsequent data analysis and trend prediction, providing strong support for motor operating state monitoring and evaluation. Using a predefined regular expression, the preprocessed log file data is parsed line by line to identify and extract key data items related to the motor operating state. This can accurately identify key information in the log, improving the accuracy and efficiency of data extraction. The real-time log processing module automatically parses and extracts key data items, greatly reducing the workload and time cost of manual processing. Automation improves data processing efficiency while reducing the likelihood of human error and omissions.

[0086] Preferably, the predefined regular expression generation steps include:

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

[0088] According to the analysis results, a set of regular expression rules is written, each regular expression rule corresponding to a key data item related to the motor operating state.

[0089] In this embodiment, by analyzing the sample data of EtherCAT motor log files, the location, format and change rule of key data items in 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 running state of the motor, making the data analysis process more efficient. Compared with traditional string processing methods, regular expressions can quickly locate and extract the required data items, improving the efficiency of data processing; since regular expressions are written based on the analysis results of 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 accurately extract 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, ensuring the reliability of the extracted data quality; 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] Receiving the motor control parameter adjustment suggestion output by the DeepSeek inference engine;

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

[0093] According to the urgency or importance of the control parameter adjustment suggestion output by the DeepSeek inference engine, dynamically adjusting the scheduling priority of the EtherCAT motor control algorithm in the operating system;

[0094] Through the command line tool of the operating system, setting the priority of the process or thread of the EtherCAT motor control algorithm.

[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 critical 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. Dynamic adjustment of the scheduling priority can reduce the execution delay and jitter of the EtherCAT motor control algorithm, ensuring the timeliness and accuracy of motor control instructions, which helps to maintain the stability of 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 critical control tasks to ensure that these tasks are executed first.

[0096] Preferably, the process or thread of the EtherCAT motor control algorithm in the operating system is specifically identified, including:

[0097] The process management or thread management tool provided by the operating system is used 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 predetermined data structure.

[0099] In the embodiment, the identification information of the EtherCAT motor control algorithm process or thread, including the process ID, thread ID and name, can be accurately obtained through the process management or thread management tool provided by the operating system, which is the basis for subsequent scheduling priority adjustment, ensuring the accuracy and pertinence of the adjustment operation, and avoiding resource conflicts between different processes or threads, improving the utilization efficiency of system resources; the obtained identification information is stored in a preset data structure, such as a hash table, a dictionary or a database, etc., for subsequent quick query and use, which improves the data access efficiency and reduces the system overhead, and the preset data structure makes the management of identification information more orderly and efficient, facilitating operations such as adding, deleting, modifying and querying, and also facilitating the maintenance and upgrading of the system, improving the maintainability and scalability of the system; through the stored identification information, the system can obtain the state of the EtherCAT motor control algorithm process or thread in real time, such as the running state and resource occupation, which provides real-time data support for dynamic scheduling and priority adjustment, ensuring the timeliness and effectiveness of the adjustment operation, and based on the obtained identification information and process or thread state, the system can flexibly adjust the scheduling strategy, such as increasing or decreasing the scheduling priority, adjusting the time slice size, etc., which makes the system adapt to the performance requirements in different application scenarios, improving the adaptability and response speed of the system.

[0100] An EtherCAT motor control method based on an RK3568 processor, specifically comprising:

[0101] Integrating an EtherCAT motor control algorithm and a DeepSeek AI inference engine on the RK3568 processor, the EtherCAT motor control algorithm is used to read the speed value in the file system and dynamically adjust the motor speed, and the DeepSeek AI inference engine is used to analyze EtherCAT motor state data and output control parameter adjustment suggestions;

[0102] Real-time acquisition of EtherCAT motor running log data and conversion into CSV format as input of the DeepSeek inference engine;

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

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

[0105] The above only describes the preferred embodiments of the present application and does not limit the present application, any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. An EtherCAT motor control system based on RK3568 processor, characterized in that, Comprise: An integration module for integrating an EtherCAT motor control algorithm and a DeepSeek AI inference engine on the RK3568 processor, the EtherCAT motor control algorithm for reading speed values in the file system and dynamically adjusting motor speed, and the DeepSeek AI inference engine for analyzing EtherCAT motor state data and outputting control parameter adjustment suggestions; A real-time log processing module for obtaining EtherCAT motor operation log data and converting it into CSV format as input for the DeepSeek inference engine; A real-time scheduling optimization module for adjusting the scheduling priority of the EtherCAT motor control algorithm in the operating system according to the output of the DeepSeek inference engine; Wherein the real-time log processing module obtains EtherCAT motor operation log data and converts it into CSV format, specifically comprising: Real-time acquisition of log file data during the operation of the EtherCAT motor, the log file data recording key parameters and state information during motor operation; Importing the obtained 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 operating state; The extracted key data items are formatted according to the predetermined CSV format to generate structured motor state data files; Output the generated CSV format motor state data file; The real-time log processing module parses the log file data and extracts key data items related to the motor operating state, specifically comprising: The real-time log processing module receives EtherCAT motor operation log file data, which contains original recorded information during motor operation; Pretreatment of the received log file data, including removing invalid characters, formatting log entries, and unifying timestamp format; Using a predefined regular expression, the log file data after preprocessing is parsed line by line to identify and extract key data items related to the motor operating state, including motor speed, current value, temperature value, position information, and operating state flag.

2. The EtherCAT motor control system based on RK3568 processor according to claim 1, wherein The EtherCAT motor control algorithm reads the speed value in the file system and dynamically adjusts the motor speed, specifically comprising: Providing a speed value file in the Linux file system, which stores the speed value used to control the motor speed, the speed value file is located in the / sys / class / igh / speed path; The EtherCAT motor control algorithm reads the contents 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, trigger the callback function to read the new speed value; According to the read new speed value, send process data object to the motor controller through EtherCAT protocol to dynamically adjust the speed of the motor.

3. The EtherCAT motor control system based on RK3568 processor according to claim 2, characterized in that, The DeepSeek AI inference engine analyzes EtherCAT motor state data and outputs control parameter adjustment suggestions, specifically including: Receiving EtherCAT motor state data converted by the real-time log processing module; The DeepSeek AI inference engine analyzes the received EtherCAT motor state data, and uses a pre-trained deep learning model to evaluate and predict the EtherCAT motor state; According to the analysis result, the DeepSeek AI inference engine outputs the adjustment suggestion of the motor control parameter, and the adjustment suggestion includes the adjustment value of the PID control parameter and the adjustment value of the target speed; The output control parameter adjustment suggestion is provided to the EtherCAT motor control program to optimize the motor control.

4. The EtherCAT motor control system based on RK3568 processor according to claim 3, characterized in that, The specific generation steps of the predefined regular expression include: Analyze sample data of EtherCAT motor log files to determine the location, format and change rule of key data items in log entries; According to the analysis result, a set of regular expression rules are written, each regular expression rule corresponds to a key data item related to the motor running state.

5. The EtherCAT motor control system based on RK3568 processor according to claim 4, characterized in that, 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: Receiving the motor control parameter adjustment suggestion output by the DeepSeek inference engine; Identify the process or thread of the EtherCAT motor control algorithm in the operating system; According to the urgency or importance of the control parameter adjustment suggestion output by the DeepSeek inference engine, dynamically adjust the scheduling priority of the EtherCAT motor control algorithm in the operating system; Through the command line tool of the operating system, set the priority of the process or thread of the EtherCAT motor control algorithm.

6. The EtherCAT motor control system based on RK3568 processor according to claim 5, characterized in that, The specific process of identifying the process or thread of the EtherCAT motor control algorithm in the operating system includes: Use the process management or thread management tool provided by the operating system to obtain the identification information of the EtherCAT motor control algorithm process or thread, including process ID, thread ID and name; Store the obtained identification information in the preset data structure.

7. An EtherCAT motor control method based on an RK3568 processor, characterized in that, Specifically including: Integrate the EtherCAT motor control algorithm and the DeepSeek AI inference engine on the RK3568 processor, the EtherCAT motor control algorithm is used to read the speed value in the file system and dynamically adjust the motor speed, and the DeepSeek AI inference engine is used to analyze EtherCAT motor state data and output control parameter adjustment suggestions; Real-time acquisition of EtherCAT motor running log data and conversion to CSV format as input of DeepSeek inference engine; The DeepSeek inference engine outputs the control parameter adjustment suggestion; According to the control parameter adjustment suggestion, dynamically adjust the scheduling priority of the EtherCAT motor control algorithm in the operating system; The real-time log processing module acquires EtherCAT motor operation log data and converts it into CSV format, specifically including: Real-time acquisition of log file data during EtherCAT motor operation, which records key parameters and state information during motor operation; Importing 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 operating state; The extracted key data items are formatted according to the predetermined CSV format to generate structured motor state data files; Output the generated CSV format motor state data file; The real-time log processing module parses the log file data and extracts key data items related to the motor operating state, specifically including: The real-time log processing module receives EtherCAT motor operation log file data, which contains original recorded information during motor operation; Pretreatment of the received log file data, including removing invalid characters, formatting log entries, and unifying timestamp format; Using a predefined regular expression, the preprocessed log file data is parsed line by line to identify and extract key data items related to the motor operating state, including motor speed, current value, temperature value, position information, and operating state flag.

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