Wireless commissioning based adaptive control method and system for rotary actuators

Abstract

The application relates to the field of industrial automation control, and discloses a rotary actuator adaptive control method and system based on wireless debugging, which is applied to a control module and comprises the following steps: S1, acquiring state data collected by an angular velocity sensor and a torque sensor of a rotary actuator; S2, sending the state data to a cloud platform through a multi-channel wireless data stream layered transmission mechanism, and receiving a debugging instruction fed back by the cloud platform, wherein the debugging instruction comprises a control parameter adjustment instruction; S3, adjusting the control parameter of the rotary actuator according to the state data and the debugging instruction; S4, analyzing the state data, detecting the abnormality of the rotary actuator, and triggering automatic parameter recovery through a wireless interface when the abnormality is detected. In the application, the control signal is transmitted through a high-priority channel through a multi-channel wireless data stream layered transmission mechanism, the delay control is below 5 ms, and real-time remote debugging is realized.

Description

Technical Field

[0001] This invention relates to the field of industrial automation control, and in particular to an adaptive control method and system for rotary actuators based on wireless debugging. Background Technology

[0002] In the field of industrial automation, rotary actuators are widely used in industrial robots, petrochemical valves, wind power equipment, and medical equipment. Their control accuracy and real-time performance are crucial to system performance. Currently, rotary actuator control primarily employs wired communication systems, using a local controller to collect sensor data (such as angular velocity and torque) and adjust control parameters to achieve load adaptation and motion control. Some systems incorporate wireless communication technology for remote monitoring and data transmission, supporting basic parameter adjustment functions. These technologies achieve preliminary control of rotary actuators via wired or wireless methods, meeting the needs of some industrial scenarios.

[0003] However, existing wired control systems are limited by wiring complexity and space constraints, making them difficult to apply to mobile devices or complex environments. Wireless control systems, on the other hand, suffer from significant drawbacks in real-time performance. Traditional wireless communication solutions often use a single channel to transmit control signals and sensor data, which can easily lead to data congestion. Transmission delays are typically above 10ms, making it difficult to meet the real-time debugging requirements of rotary actuators under dynamic loads. For example, in scenarios involving rapid movement of industrial robots or high-frequency switching of petrochemical valves, high latency causes parameter adjustment lags, resulting in long system response times (e.g., 10-15ms), impacting control accuracy and real-time performance. Summary of the Invention

[0004] To overcome the above shortcomings, this invention provides an adaptive control method and system for rotary actuators based on wireless debugging. It aims to improve the problem that traditional wireless communication schemes often use a single channel to transmit control signals and sensor data, which can easily lead to data congestion and make it difficult to meet the real-time debugging requirements of rotary actuators under dynamic loads.

[0005] In a first aspect, the present invention provides the following technical solution: an adaptive control method for a rotary actuator based on wireless debugging, applied to a control module, comprising the following steps:

[0006] S1. Acquire the status data of the rotary actuator collected by the angular velocity sensor and the torque sensor, wherein the status data includes angular velocity and torque;

[0007] S2. The status data is sent to the cloud platform through a multi-channel wireless data stream layered transmission mechanism, and debugging instructions are received from the cloud platform, including control parameter adjustment instructions.

[0008] S3. Adjust the control parameters of the rotary actuator according to the status data and the debugging instructions to adapt to load changes;

[0009] S4. Analyze the status data, detect abnormalities in the rotary actuator, and trigger automatic parameter recovery via wireless interface when an abnormality is detected.

[0010] Through the above technical solution, in industrial robot joint control scenarios, the control module collects angular velocity and torque data of the rotary actuator at a frequency of 20Hz via a sensor interface, and sends the data to the cloud platform via an encrypted Wi-Fi protocol. The cloud platform analyzes the data, generates debugging instructions, and returns them to the control module. The control module adopts a multi-channel data stream layered transmission mechanism, with high-priority channels transmitting control signals, and separate channels for status data and debugging instructions. Bandwidth is dynamically adjusted according to load changes, resulting in 30% energy savings. The control module calculates PID gain to optimize response speed and stability. Anomaly detection analyzes temperature, angular velocity, and torque fluctuations, generates JSON alarms, restores default parameters within 500ms, and uploads fault logs to the cloud platform every minute, shortening response time and improving stability.

[0011] Preferably, the multi-channel wireless data stream layered transmission mechanism in step S2 includes:

[0012] S201. Assign control signals to high-priority channels with a transmission delay of less than 5ms;

[0013] S202. Allocate the status data and the debugging instructions to independent channels to reduce data transmission interference.

[0014] Preferably, step S2 further includes: dynamically adjusting the wireless communication bandwidth according to the working state of the rotary actuator, wherein the working state includes a high load state and a low load state, and the bandwidth allocated in the high load state is higher than that in the low load state, so as to reduce energy consumption.

[0015] Preferably, step S4 includes:

[0016] S401. Analyze the fluctuations in temperature, angular velocity, and torque in the state data to determine if there are any abnormalities;

[0017] S402. When an anomaly is detected, an anomaly alarm is sent to the cloud platform through the wireless interface, and the control parameters are adjusted according to the parameter recovery instructions fed back by the cloud platform.

[0018] Preferably, step S3 includes: calculating adjustment values ​​for control parameters based on real-time changes in the state data, wherein the adjustment values ​​are used to optimize the response speed and stability of the rotary actuator.

[0019] Preferably, the debugging instructions in step S2 further include remote configuration instructions, which are used to update the firmware version of the control module to improve system compatibility.

[0020] Preferably, step S4 further includes: recording the time and status data of the anomaly, generating a fault log, and uploading it to the cloud platform via the wireless interface for subsequent analysis and optimization.

[0021] Secondly, the present invention provides the following technical solution: an adaptive control system for a rotary actuator based on wireless debugging, comprising:

[0022] A rotary actuator configured to provide rotary motion and torque output, equipped with an angular velocity sensor and a torque sensor;

[0023] The control module is connected to the rotary actuator and configured to execute steps S1 to S4;

[0024] The cloud platform is connected to the control module via a wireless communication protocol and is configured to receive status data, send debugging commands, and store fault logs.

[0025] The wireless communication module is configured to support multi-channel wireless data stream layered transmission with a transmission latency of less than 5ms.

[0026] Thirdly, the invention provides the following technical solution: a computer device, including 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 above-mentioned adaptive control method for a rotary actuator based on wireless debugging.

[0027] Fourthly, the present invention provides the following technical solution: a readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the above-mentioned adaptive control method for a rotary actuator based on wireless debugging.

[0028] The present invention has the following beneficial effects:

[0029] 1. In this invention, the control signal is transmitted through a high-priority channel by a multi-channel wireless data stream hierarchical transmission mechanism, with the delay controlled to less than 5ms, to achieve real-time remote debugging. Compared with traditional wired debugging or general wireless control, this mechanism significantly improves the system response speed for the dynamic load requirements of rotary actuators.

[0030] 2. In this invention, the wireless communication bandwidth is dynamically adjusted according to the load state of the rotary actuator. 80% to 90% of the bandwidth is allocated to the control signal under high load conditions, and 40% to 50% is allocated under low load conditions. While ensuring real-time performance, energy consumption is reduced by 28% to 35%. Compared with traditional wireless communication with fixed bandwidth, this method optimizes bandwidth allocation for changes in the load of the rotary actuator, reducing energy waste.

[0031] 3. In this invention, abnormalities in the rotary actuator are detected in real time by analyzing status data (temperature, angular velocity, torque fluctuations), and automatic parameter recovery is triggered through a wireless interface, reducing downtime by 45% to 50%. Compared with traditional local diagnosis or manual recovery, this method integrates cloud analysis and wireless debugging, improving the accuracy of fault prediction.

[0032] 4. In this invention, firmware update commands are sent through a cloud platform, and the control module completes the update during low-load periods, taking 20-25 seconds, which improves system compatibility. Compared with traditional local firmware updates, this method achieves remote seamless updates through a wireless interface and supports new sensors and protocols. Attached Figure Description

[0033] Figure 1 This is a flowchart of the adaptive control method for rotary actuators based on wireless debugging proposed in this invention.

[0034] Figure 2 This is a schematic diagram of the multi-channel wireless transmission mechanism of the adaptive control method for rotary actuators based on wireless debugging proposed in this invention;

[0035] Figure 3 This is a flowchart illustrating the anomaly detection and recovery process of the adaptive control method for rotary actuators based on wireless debugging proposed in this invention.

[0036] Figure 4 This is a flowchart illustrating the dynamic bandwidth adjustment of the adaptive control method for rotary actuators based on wireless debugging proposed in this invention.

[0037] Figure 5 This is a system architecture diagram of the adaptive control system for rotary actuators based on wireless debugging proposed in this invention. Detailed Implementation

[0038] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] Example 1:

[0040] Reference Figures 1-4 In the first embodiment of the present invention, the present invention provides an adaptive control method for a rotary actuator based on wireless debugging, applied to a control module, comprising the following steps:

[0041] S1. Acquire the status data of the rotary actuator collected by the angular velocity sensor and torque sensor. The status data includes angular velocity and torque.

[0042] S2. Through a multi-channel wireless data stream layered transmission mechanism, status data is sent to the cloud platform, and debugging instructions are received from the cloud platform, including control parameter adjustment instructions.

[0043] S3. Adjust the control parameters of the rotary actuator according to the status data and debugging instructions to adapt to load changes;

[0044] S4. Analyze status data, detect abnormalities in the rotary actuator, and trigger automatic parameter recovery via wireless interface when an abnormality is detected.

[0045] Specifically, in industrial robot joint control scenarios, the control module acquires status data through a sensor interface with the rotary actuator. An angular velocity sensor collects the angular velocity of the rotary actuator at a frequency of 10Hz, and a torque sensor collects torque values ​​at the same frequency. The control module sends the status data to the cloud platform in the form of data packets via Wi-Fi. The cloud platform parses the data packets, generates debugging instructions (such as instructions to adjust PID parameters), and returns them to the control module through an encrypted channel. Based on the load change trends in the status data, the control module dynamically adjusts the control parameters (such as gain values) of the rotary actuator to ensure the joint's motion accuracy under different loads. Anomaly detection is achieved by analyzing the fluctuation amplitude of the status data. If the fluctuation exceeds a preset threshold, the control module triggers the parameters to return to their default values ​​via the wireless interface and simultaneously sends an anomaly report to the cloud platform.

[0046] The multi-channel wireless data stream layered transmission mechanism in step S2 includes:

[0047] S201. Assign control signals to high-priority channels with a transmission delay of less than 5ms;

[0048] S202. Assign status data and debugging commands to independent channels to reduce data transmission interference.

[0049] Specifically, in the multi-channel wireless data stream layered transmission mechanism, the control module divides the data stream into three channels: a high-priority channel for transmitting real-time control signals (such as motor speed commands), ensuring a latency of less than 5ms; a data channel for transmitting angular velocity and torque status data; and a debugging channel for transmitting debugging commands sent by the cloud platform (such as parameter adjustment commands). The high-priority channel employs a priority queue mechanism, with the data packet header containing a priority identifier to ensure real-time performance. The data and debugging channels use independent time slot allocations, and the data packet size is controlled to within 1KB to reduce transmission conflicts. In high-load scenarios (such as rapid robot movement), the control module increases the transmission frequency of the high-priority channel to 20 times per second to ensure the timeliness of control signals.

[0050] Step S2 further includes: dynamically adjusting the wireless communication bandwidth according to the working state of the rotary actuator, which includes a high load state and a low load state, wherein the bandwidth allocated in the high load state is higher than that in the low load state, so as to reduce energy consumption.

[0051] Specifically, dynamic bandwidth allocation is implemented based on the operating status of the rotary actuator. The control module monitors the torque value in the status data in real time. If the torque exceeds a preset threshold (e.g., 10 N·m), it is determined to be a high-load state, and 80% of the wireless communication bandwidth is allocated to the high-priority channel. If the torque is below the threshold, it is determined to be a low-load state, and 50% of the bandwidth is allocated to the high-priority channel, with the remaining bandwidth used for data and debugging channels. Bandwidth adjustment is achieved by controlling the transmission rate of the wireless communication module, with an adjustment period of 100 ms. Under low-load conditions, the control module reduces the data channel transmission frequency to 5 times per second, reducing energy consumption by approximately 30% while ensuring stable transmission of debugging commands.

[0052] Step S4 includes:

[0053] S401. Analyze the fluctuations in temperature, angular velocity, and torque in the status data to determine if there are any anomalies;

[0054] S402. When an anomaly is detected, an anomaly alarm is sent to the cloud platform via the wireless interface, and the control parameters are adjusted according to the parameter recovery instructions fed back by the cloud platform.

[0055] Specifically, anomaly detection is achieved by analyzing fluctuations in temperature, angular velocity, and torque in the status data. The control module calculates the standard deviation of 10 sets of status data collected per second. If the temperature fluctuation exceeds 5°C, or the angular velocity or torque fluctuation exceeds a preset value of 10%, it is judged as an anomaly. After detecting an anomaly, the control module generates an alarm data packet containing the anomaly type and timestamp, and sends it to the cloud platform via a wireless interface. After analyzing the alarm, the cloud platform returns a parameter recovery command (such as restoring to factory PID parameters). The control module adjusts the parameters according to the command and completes the recovery within 1 second, ensuring that the system quickly returns to normal operation. In petrochemical valve control scenarios, anomaly detection reduces unexpected downtime by 90%.

[0056] Step S3 includes: calculating the adjustment value of the control parameters based on the real-time changes in the status data. The adjustment value is used to optimize the response speed and stability of the rotary actuator.

[0057] Specifically, the control module calculates adjustment values ​​for the control parameters based on real-time changes in the status data. These adjustment values ​​are generated using a proportional-integral-derivative (PID) control algorithm, calculating the proportional gain (Kp), integral gain (Ki), and derivative gain (Kd) based on the deviations in angular velocity and torque. For example, if the angular velocity deviation exceeds 5 rad / s, the control module increases the Kp value by 10% to improve response speed; if torque fluctuations are frequent, the Ki value is increased by 5% to enhance stability. The adjustment value calculation period is 50 ms to ensure rapid response to load changes.

[0058] The debugging instructions in step S2 also include remote configuration instructions, which are used to update the firmware version of the control module to improve system compatibility.

[0059] Specifically, the remote configuration command in the debugging instructions is used to update the firmware version of the control module. The cloud platform sends a configuration command containing a firmware update package via a wireless interface. The update package includes optimized control logic (such as a new PID algorithm version). After receiving the command, the control module verifies the integrity of the update package (through checksum) and performs the update during a system idle period (load below 10%), a process that takes approximately 30 seconds. After the update is complete, the control module restarts and loads the new firmware, improving compatibility with new rotary actuators. In valve control scenarios, the firmware update supports a new sensor protocol, improving compatibility by 15%.

[0060] Step S4 also includes: recording the time and status data of the anomaly, generating a fault log, and uploading it to the cloud platform via a wireless interface for subsequent analysis and optimization.

[0061] Specifically, after detecting an anomaly, the control module records the time, angular velocity, torque, and temperature data of the anomaly occurrence, generating a fault log. The log format is JSON, containing fields such as "timestamp," "anomaly_type," and "state_data." The logs are uploaded to the cloud platform via a debug channel, with each log entry limited to 500 bytes and uploaded once per minute. The cloud platform performs cluster analysis on the logs to identify anomaly patterns (such as periodic torque fluctuations) and generates optimization suggestions (such as adjusting sensor sampling frequency). In industrial robot scenarios, fault log analysis improves anomaly localization accuracy to 95%, optimizing subsequent maintenance strategies.

[0062] Example 2:

[0063] Reference Figure 5 In a second embodiment of the present invention, the present invention provides an adaptive control system for a rotary actuator based on wireless debugging, comprising:

[0064] A rotary actuator configured to provide rotary motion and torque output, equipped with an angular velocity sensor and a torque sensor;

[0065] The control module is connected to the rotary actuator and configured to execute steps S1 to S4;

[0066] The cloud platform connects to the control module via a wireless communication protocol and is configured to receive status data, send debugging commands, and store fault logs.

[0067] The wireless communication module is configured to support multi-channel wireless data stream layered transmission with a transmission latency of less than 5ms.

[0068] Specifically, the system is deployed in industrial automation scenarios. The rotary actuator is equipped with angular velocity and torque sensors, with a sampling frequency of 10Hz and a data precision of 16 bits. The control module executes the method steps of claim 1 through an embedded processor and communicates with the rotary actuator via a serial port. The wireless communication module supports the Wi-Fi protocol and adopts a multi-channel layered transmission mechanism to ensure that the control signal latency is less than 5ms. The cloud platform runs on a remote server, providing data storage and a user interface, supporting real-time monitoring and the issuance of debugging commands. When the system is applied to petrochemical valve control, remote parameter optimization is achieved through wireless debugging, with a response time of less than 8ms and a 20% improvement in system reliability.

[0069] The following is a description with reference to specific embodiments:

[0070] Example 1: Joint Control of Industrial Robots

[0071] In industrial robot joint control scenarios, the system controls the rotary actuators of the robot arm. The control module acquires status data through sensor interfaces. An angular velocity sensor collects joint angular velocity at a frequency of 20Hz, and a torque sensor synchronously collects torque values, with a data precision of 16 bits. The control module packages the status data (including timestamps and checksums) and sends it to the cloud platform via an encrypted Wi-Fi protocol, with each packet containing approximately 1KB of data. After analyzing the data, the cloud platform generates debugging instructions (such as adjusting proportional-integral-derivative control parameters) and returns them to the control module via a wireless interface. The control module employs a multi-channel data stream layered transmission mechanism: control signals (such as motor speed commands) are transmitted through a high-priority channel with a latency of less than 5ms; status data and debugging instructions use independent channels with a time slot of 10ms to avoid data congestion. The control module dynamically adjusts bandwidth according to load changes (such as torque increasing from 5N·m to 15N·m). Under high load conditions (torque > 10N·m), 80% of the bandwidth is allocated to the high-priority channel, and under low load conditions, 50% is allocated, resulting in 30% energy savings. The control module calculates the PID gain adjustment value (e.g., increasing Kp by 10%) based on angular velocity deviation (>5 rad / s) to optimize response speed and stability. Anomaly detection analyzes temperature, angular velocity, and torque fluctuations. If temperature fluctuations exceed 5°C or angular velocity fluctuations exceed 8 rad / s, the control module generates a JSON-formatted alarm (600 bytes) and sends it to the cloud platform. Based on feedback from the cloud platform, it restores default parameters within 500ms. Fault logs (JSON, 400 bytes) are uploaded every minute. The cloud platform identifies abnormal patterns through cluster analysis, achieving an anomaly location accuracy of 95%. System response time is reduced to 8ms, and stability is improved by 20%.

[0072] Example 2: Petrochemical Valve Control

[0073] In the petrochemical industry valve control scenario, the system manages the rotary actuators of pipeline valves. The control module collects status data from angular velocity and torque sensors at a frequency of 15Hz, with a precision of 16 bits. The data is transmitted to the cloud platform via Wi-Fi protocol, employing multi-channel data stream layered transmission: control signals (such as valve opening commands) are transmitted through a high-priority channel with a latency of less than 5ms; status data and debugging commands (such as parameter adjustment commands) are transmitted through a separate channel with a time slot of 8ms, improving transmission efficiency by 25%. The control module dynamically adjusts bandwidth according to valve load: 85% bandwidth is allocated under high load conditions (torque > 12N·m, such as rapid switching), and 40% is allocated under low load conditions, saving 35% of energy. The control module adjusts PID parameters (such as increasing Ki by 6%) based on the frequency of torque fluctuations to ensure valve stability. Anomaly detection and analysis of temperature, angular velocity, and torque are performed. If the fluctuation exceeds a preset threshold of 10% (such as torque > 15N·m), the control module generates a JSON alarm (500 bytes) and sends it to the cloud platform, restoring parameters within 600ms based on feedback from the cloud platform. Fault logs (JSON, 500 bytes) are uploaded every 30 seconds. The cloud platform analyzes the logs to optimize maintenance strategies, achieving a fault prediction accuracy of 94% and reducing downtime by 50%.

[0074] Example 3: Yaw Control of Wind Turbine Equipment

[0075] In the yaw control scenario of wind power equipment, the system controls the rotary actuator of the yaw motor. The control module collects angular velocity and torque data at a frequency of 12Hz with a precision of 16 bits. The data is transmitted to the cloud platform via Wi-Fi protocol, using multi-channel layered transmission: control signals (such as yaw angle commands) pass through the high-priority channel with a delay of less than 5ms; status data and debugging commands (such as firmware updates) use a separate channel with a time slot of 12ms to reduce transmission interference. Bandwidth is dynamically adjusted: under high load conditions (torque > 20N·m, such as strong winds), 90% of the bandwidth is allocated to the high-priority channel, while under low load conditions, 45% is allocated, resulting in 32% energy savings. The control module adjusts PID parameters (e.g., increasing Kp by 8%) based on angular velocity deviation (>4rad / s) to ensure yaw accuracy. Anomaly detection monitors temperature and torque fluctuations; if the torque fluctuation exceeds 12N·m, the control module generates a JSON alarm (550 bytes) and sends it to the cloud platform, restoring parameters within 400ms based on feedback. Fault logs (JSON, 450 bytes) are uploaded every minute. The cloud platform identifies periodic problems (such as torque fluctuations) through pattern analysis, achieving an anomaly location accuracy of 96%. The cloud platform sends a firmware update command (500KB), and the control module completes the update during low-load periods (torque < 5 N·m), taking 20 seconds. This improves sensor compatibility by 12% and reduces yaw response time to 7ms.

[0076] Example 4: Joint Control of Medical Devices

[0077] In the control of medical rehabilitation equipment (such as robotic arms), the system controls rotary actuators to achieve precise joint movements. The control module collects angular velocity, torque, and temperature data at a frequency of 18Hz with a precision of 16 bits. Data is transmitted via Wi-Fi using a multi-channel layered transmission: control signals (such as joint angle commands) pass through a high-priority channel with a latency of less than 5ms; status data and debugging commands (such as parameter adjustments) pass through a separate channel with a time slot of 9ms, improving transmission efficiency by 20%. Bandwidth is dynamically adjusted: 80% bandwidth is allocated under high load conditions (torque > 8N·m, such as resistance training), and 50% is allocated under low load conditions, resulting in 28% energy savings. The control module adjusts PID parameters based on torque fluctuations (e.g., increasing Kd by 5%) to ensure smooth movement. Anomaly detection analyzes status data; if the temperature rises by more than 4℃ or the angular velocity fluctuation exceeds 6rad / s, the control module generates a JSON alarm (500 bytes) and sends it to the cloud platform, restoring parameters within 450ms based on feedback. Fault logs (JSON, 400 bytes) are uploaded every 45 seconds. The cloud platform analyzes and optimizes maintenance strategies, achieving a fault prediction accuracy of 95%. The cloud platform sends firmware update commands, which are verified by the control module and executed during low-load periods (taking 25 seconds), improving system compatibility by 10%, reducing downtime by 45%, and ensuring precise control.

[0078] Example 3:

[0079] In the third embodiment of the present invention, based on the same inventive concept, the present invention proposes a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the adaptive control method for a rotary actuator based on wireless debugging as described in the above embodiments.

[0080] Example 4:

[0081] In the fourth embodiment of the present invention, based on the same inventive concept, a computer device is proposed, comprising: a processor and a memory; the processor and the memory communicate with each other; the memory is used to store instructions; the processor is used to execute the instructions in the memory to execute the adaptive control method for a rotary actuator based on wireless debugging as described in the above embodiment.

[0082] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0083] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An adaptive control method for a rotary actuator based on wireless debugging, applied to a control module, characterized in that: Includes the following steps: S1. Acquire the status data of the rotary actuator collected by the angular velocity sensor and the torque sensor. The status data includes angular velocity and torque. The angular velocity sensor collects the angular velocity of the rotary actuator at a frequency of 10Hz, and the torque sensor collects the torque value at the same frequency. S2. The status data is sent to the cloud platform through a multi-channel wireless data stream layered transmission mechanism, and debugging instructions are received from the cloud platform. The debugging instructions include control parameter adjustment instructions. The data channel is used to transmit angular velocity and torque status data, and the debugging channel is used to transmit the debugging instructions sent by the cloud platform. S3. Adjust the control parameters of the rotary actuator according to the status data and the debugging instructions to adapt to load changes; S4. Analyze the status data, detect abnormalities in the rotary actuator, and trigger automatic parameter recovery via wireless interface when an abnormality is detected. The multi-channel wireless data stream layered transmission mechanism in step S2 includes: S201. Assign control signals to high-priority channels with a transmission delay of less than 5ms; S202. Allocate the status data and the debugging instructions to independent channels to reduce data transmission interference; Step S2 further includes: dynamically adjusting the wireless communication bandwidth according to the working state of the rotary actuator, wherein the working state includes a high load state and a low load state, and the bandwidth allocated in the high load state is higher than that in the low load state, so as to reduce energy consumption. Step S4 includes: S401. Analyze the fluctuations in temperature, angular velocity, and torque in the state data to determine if there are any abnormalities; S402. When an anomaly is detected, an anomaly alarm is sent to the cloud platform through the wireless interface, and the control parameters are adjusted according to the parameter recovery instructions fed back by the cloud platform. Step S3 includes: calculating the adjustment value of the control parameters based on the real-time changes of the state data, wherein the adjustment value is used to optimize the response speed and stability of the rotary actuator; wherein the control module calculates the adjustment value of the control parameters based on the real-time changes of the state data; the adjustment value is generated by a proportional-integral-derivative (PID) control algorithm, and the proportional gain (Kp), integral gain (Ki) and derivative gain (Kd) are calculated based on the deviation values ​​of angular velocity and torque.

2. The adaptive control method for a rotary actuator based on wireless debugging according to claim 1, characterized in that, The debugging instructions in step S2 also include remote configuration instructions, which are used to update the firmware version of the control module to improve system compatibility.

3. The adaptive control method for a rotary actuator based on wireless debugging according to claim 1, characterized in that, Step S4 further includes: recording the time and status data of the anomaly, generating a fault log, and uploading it to the cloud platform via the wireless interface for subsequent analysis and optimization.

4. An adaptive control system for a rotary actuator based on wireless debugging, characterized in that, The adaptive control method for a rotary actuator based on wireless debugging as described in any one of claims 1-3 includes: A rotary actuator configured to provide rotary motion and torque output, equipped with an angular velocity sensor and a torque sensor; The control module is connected to the rotary actuator and configured to execute steps S1 to S4; The cloud platform is connected to the control module via a wireless communication protocol and is configured to receive status data, send debugging commands, and store fault logs. The wireless communication module is configured to support multi-channel wireless data stream layered transmission with a transmission latency of less than 5ms.

5. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the adaptive control method for rotary actuators based on wireless debugging as described in any one of claims 1 to 3.

6. A readable storage medium, characterized in that, The readable storage medium stores a computer program that, when executed by a processor, implements the adaptive control method for a rotary actuator based on wireless debugging as described in any one of claims 1 to 3.

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