Moxibustion robot adaptive control system and method based on temperature feedback

Abstract

The application provides a moxibustion robot adaptive control system and method based on temperature feedback, which comprises a base, a multi-degree-of-freedom mechanical arm, a moxibustion physiotherapy head, a temperature sensor, a distance sensor and a controller. The moxibustion physiotherapy head is arranged at the end of the multi-degree-of-freedom mechanical arm, the temperature sensor is used to collect the skin surface temperature, the distance sensor is used to collect the distance between the moxibustion physiotherapy head and the skin, and the controller is electrically connected with the multi-degree-of-freedom mechanical arm, the temperature sensor and the distance sensor. The controller obtains the skin temperature and the physiotherapy head height data in real time, calculates the temperature deviation value and the temperature change rate, takes the two as inputs, calculates the height adjustment amount through a continuous control algorithm, controls the movement of the mechanical arm to adjust the distance between the physiotherapy head and the skin. The application can realize stepless smooth height regulation, effectively reduce temperature fluctuation, improve temperature control accuracy and moxibustion stability, and guarantee the effect and comfort of moxibustion physiotherapy.

Description

Technical Field

[0001] This application relates to the field of physiotherapy equipment technology, and in particular to an adaptive control system and method for a moxibustion robot based on temperature feedback. Background Technology

[0002] Moxibustion is an important therapy in the field of Traditional Chinese Medicine (TCM) physiotherapy. It uses the warmth generated by burning moxa sticks to stimulate acupoints on the body, achieving the effects of warming the meridians, promoting blood circulation, and regulating the body. It is widely used in health preservation, physiotherapy, and rehabilitation. With the development of automation and robotics, moxibustion robots are gradually replacing manual moxibustion. Existing moxibustion robots are typically equipped with temperature and distance sensors. By detecting the skin surface temperature, they control the raising and lowering of the moxibustion head, achieving basic automated temperature-controlled moxibustion. This reduces the cost of manual operation to some extent and improves the convenience of moxibustion.

[0003] However, the temperature control systems of existing moxibustion robots generally adopt a fixed threshold on / off control logic, which triggers the adjustment of the treatment head only when the temperature exceeds the preset upper and lower limits. This can easily lead to periodic and large fluctuations in skin temperature, resulting in insufficient stability of the moxibustion heat dose and affecting the therapeutic effect. At the same time, this type of control only makes lagging adjustments based on the current temperature value and does not make forward-looking adjustments based on temperature change trends. It is prone to temperature overshoot due to system thermal inertia, posing a risk of burns. Furthermore, it is difficult to adapt to the differentiated temperature control needs of different moxibustion stages and different acupoints. The accuracy, comfort, and intelligence of temperature control all need to be improved. Summary of the Invention

[0004] In view of this, the embodiments of this application provide an adaptive control system and method for a moxibustion robot based on temperature feedback, which can achieve stepless and smooth height adjustment, effectively reduce temperature fluctuations, improve temperature control accuracy and moxibustion stability, and ensure the effect and comfort of moxibustion therapy.

[0005] The technical solution of this application embodiment is implemented as follows: In a first aspect, embodiments of this application provide an adaptive control system for a moxibustion robot based on temperature feedback, including a base, a multi-degree-of-freedom robotic arm, a moxibustion therapy head, a temperature sensor, a distance sensor, and a controller; the moxibustion therapy head is disposed at the end of the multi-degree-of-freedom robotic arm, the temperature sensor is used to collect the skin surface temperature, the distance sensor is used to collect the distance between the moxibustion therapy head and the skin, and the controller is electrically connected to the multi-degree-of-freedom robotic arm, the temperature sensor, and the distance sensor respectively; The controller is configured to: Real-time acquisition of skin temperature and treatment head height data; calculation of the deviation between the current temperature and the target temperature, as well as the rate of temperature change. The temperature deviation value and temperature change rate are taken as inputs, and the height adjustment amount is calculated and output through a continuous control algorithm. The movement of the multi-degree-of-freedom robotic arm is controlled by adjusting the height to adjust the distance between the moxibustion therapy head and the skin.

[0006] Secondly, embodiments of this application also provide an adaptive control method for a moxibustion robot based on temperature feedback, comprising the following steps: Real-time acquisition of skin temperature and treatment head height data; calculation of the deviation between the current temperature and the target temperature, as well as the rate of temperature change. The temperature deviation value and temperature change rate are taken as inputs, and the height adjustment amount is calculated and output through a continuous control algorithm. The movement of the multi-degree-of-freedom robotic arm is controlled by adjusting the height to adjust the distance between the moxibustion therapy head and the skin.

[0007] Thirdly, embodiments of this application also provide a moxibustion robot, characterized in that the moxibustion robot includes any of the temperature feedback-based moxibustion robot adaptive control systems described in the first aspect.

[0008] The embodiments of this application have the following beneficial effects: By collecting real-time data on skin temperature and the height of the treatment head using temperature and distance sensors, and using the calculated temperature deviation and temperature change rate as dual inputs, a continuous control algorithm outputs a stepless and continuous height adjustment, driving a multi-degree-of-freedom robotic arm to dynamically adjust the distance between the moxibustion treatment head and the skin, forming a complete closed-loop temperature control circuit. This solution abandons the threshold-switching adjustment mode commonly used in traditional moxibustion devices. It can quickly correct the deviation between the current temperature and the target value based on the temperature deviation, and can also predict the temperature trend and adjust the control amount in advance based on the temperature change rate. This effectively avoids the sudden rise and fall and large fluctuations in temperature caused by level adjustment, significantly improving the control accuracy and stability of the moxibustion temperature, ensuring the stable and uniform heat dosage during the moxibustion process, and realizing fully automatic closed-loop operation of the temperature control process. It eliminates the need for frequent manual adjustment of the treatment head height, effectively improving the convenience of moxibustion operation and the comfort of the treatment process. Attached Figure Description

[0009] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 This is an overall structural diagram of the moxibustion robot system provided in the embodiments of this application; Figure 2 This is the overall control logic flowchart provided in the embodiments of this application; Figure 3 This is a flowchart illustrating the operation of the dynamic continuous temperature control module provided in this application embodiment; Figure 4 This is a flowchart illustrating the operation of the temperature-time coupling control module provided in an embodiment of this application. Figure 5 This is a flowchart illustrating the operation of the acupoint coupling temperature control module provided in the embodiments of this application; Figure 6 This is a flowchart illustrating the operation of the predictive adjustment module provided in the embodiments of this application; Figure 7 This is a flowchart illustrating the operation of the three-layer collaborative security protection system provided in this application embodiment. Detailed Implementation

[0011] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0012] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0013] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0014] In the following description, the terms "first, second, third" are used merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0015] It should be noted that the term "comprising" will be used in the embodiments of this application to indicate the presence of the features declared thereafter, but does not exclude the addition of other features.

[0016] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application and is not intended to limit this application.

[0017] This application provides an adaptive control system for a moxibustion robot based on temperature feedback, including a base, a multi-degree-of-freedom robotic arm, a moxibustion therapy head, a temperature sensor, a distance sensor, and a controller; the moxibustion therapy head is disposed at the end of the multi-degree-of-freedom robotic arm, the temperature sensor is used to collect the skin surface temperature, the distance sensor is used to collect the distance between the moxibustion therapy head and the skin, and the controller is electrically connected to the multi-degree-of-freedom robotic arm, the temperature sensor, and the distance sensor respectively. The controller is configured to: Real-time acquisition of skin temperature and treatment head height data; calculation of the deviation between the current temperature and the target temperature, as well as the rate of temperature change. The temperature deviation value and temperature change rate are taken as inputs, and the height adjustment amount is calculated and output through a continuous control algorithm. The movement of the multi-degree-of-freedom robotic arm is controlled by adjusting the height to adjust the distance between the moxibustion therapy head and the skin.

[0018] The system's hardware consists of a base, a multi-degree-of-freedom robotic arm, a moxibustion therapy head, temperature sensors, distance sensors, and a controller. The base provides support and a foundation for the entire system. The multi-degree-of-freedom robotic arm has multi-dimensional spatial motion capabilities, and its end effector is equipped with a moxibustion therapy head, which can drive the therapy head to perform lifting, translating, and other movements. The temperature sensor and distance sensor are integrated into the moxibustion therapy head, respectively used to collect the skin surface temperature of the moxibustion site and the distance between the moxibustion therapy head and the skin. The controller, as the core of the system's computation and control, is connected to the multi-degree-of-freedom robotic arm and the two types of sensors through electrical circuits, receiving signals collected by the sensors and issuing motion commands to the robotic arm.

[0019] During operation, the controller continuously reads data from the temperature and distance sensors at a fixed sampling period to obtain the skin surface temperature T(t) and the height H(t) of the moxibustion therapy head at the current time t. The controller then performs preprocessing such as filtering and noise reduction on the raw data to eliminate abnormal values ​​caused by environmental interference, ensuring the accuracy of the input data. Based on the collected temperature data, the controller calculates two core state variables: one is the instantaneous temperature deviation e(t), calculated using the formula e(t) = Tset(t). T(t), where Tset(t) is the target temperature at time t, which reflects the degree and direction of temperature deviation from the target; the second is the rate of temperature change dT / dt, which is the rate at which skin temperature changes over time. In engineering, it is usually calculated by dividing the temperature difference between two adjacent sampling periods by the sampling time interval. It is used to characterize the speed and trend of temperature change and to provide a state basis for subsequent control calculations.

[0020] The controller uses the temperature deviation e(t) and the rate of temperature change dT / dt as inputs, and performs calculations through a continuous control algorithm to output a continuously changing baseline height adjustment ΔHbase(t) at time t. Unlike gear-type or on / off type adjustments, the ΔHbase(t) output by the continuous control algorithm is a stepless continuous value, which can correspond to any size of lifting and lowering displacement of the therapy head, achieving precise and smooth height adjustment. After calculating the baseline height adjustment, the controller converts it into motion control commands for a multi-degree-of-freedom robotic arm, driving the arm to raise and lower the moxibustion therapy head by the corresponding distance, updating the therapy head height H(t), and completing one control cycle of adjustment. After adjustment, the system returns to the data acquisition step to enter the next control cycle, repeating this cycle to form a continuous closed-loop temperature control, ensuring that the skin temperature T(t) stably matches the target temperature Tset(t). In some embodiments, the controller is further configured to perform predictive regulation, specifically including: A preset trend threshold for the rate of temperature change is used to determine in real time whether the absolute value of the rate of temperature change exceeds the trend threshold. If the value exceeds the limit, the corresponding predicted compensation amount is calculated and added to the height adjustment amount to suppress temperature overshoot by adjusting in advance.

[0021] During moxibustion, the controller calculates the current temperature change rate dT / dt in each control cycle and compares its absolute value |dT / dt| with a preset trend threshold. When |dT / dt| does not exceed the trend threshold, it indicates that the temperature change is stable, with no obvious risk of overheating or excessively rapid cooling. The system does not activate predictive compensation, and the final height adjustment ΔH(t) equals the base height adjustment ΔHbase(t). When |dT / dt| exceeds the trend threshold, it indicates that the temperature change rate is too rapid, posing a potential risk of subsequent temperature overshoot. At this point, the system triggers predictive adjustment logic.

[0022] After triggering predictive adjustment, the controller calculates the corresponding predictive compensation amount ΔHpredict based on the current temperature change rate dT / dt and the system's thermal inertia characteristics. This compensation amount moves in the opposite direction to the temperature change trend, used to proactively offset the temperature lag effect caused by thermal inertia. After calculation, the controller adds the predictive compensation amount to the base height adjustment amount to obtain the final height adjustment amount, calculated as ΔH(t) = ΔHbase(t) + ΔHpredict. This controls the therapy head to adjust its height in advance. This feedforward-based advance adjustment effectively suppresses temperature overshoot, prevents significant temperature deviations from the target range, and improves the stability and safety of temperature control.

[0023] In some embodiments, the controller is further configured to perform temperature-time coupled control, specifically including: The moxibustion process is divided into multiple stages based on the cumulative duration of moxibustion treatment, and a corresponding target temperature is configured for each stage. During the moxibustion process, the target temperature value is dynamically updated based on the current stage.

[0024] The controller is configured with corresponding target temperature values ​​for different stages of moxibustion. The target temperatures of all stages are sequentially connected, forming a target temperature function Tset(t) that dynamically changes with the moxibustion time t. In the preheating stage, Tset(t) starts from the initial base temperature and gradually rises to the treatment temperature at a gentle rate, allowing the skin to gradually adapt to the heat stimulation and avoiding discomfort caused by a sudden temperature rise. In the constant temperature moxibustion stage, Tset(t) is maintained at a stable treatment temperature value to ensure a continuous and uniform dose of heat stimulation and achieve the therapeutic effect of moxibustion. In the cooling and finishing stage, Tset(t) gradually decreases over time, slowly reducing to a state close to room temperature, reducing the stimulation caused by a sudden temperature drop and improving the comfort throughout the moxibustion process.

[0025] During moxibustion, the controller continuously accumulates the moxibustion time t, determines the current stage of moxibustion based on the current accumulated time, and automatically updates the current target temperature Tset(t), which is used as the benchmark for calculating the temperature deviation e(t). As the moxibustion progresses, the target temperature Tset(t) will automatically rise, maintain, and fall according to a preset curve, without the need for manual adjustment, thus achieving dynamic and process-oriented control of the temperature target throughout the entire moxibustion process.

[0026] In some embodiments, the controller is further configured with corresponding control algorithm parameters for different moxibustion stages; during the moxibustion process, the running parameters of the continuous control algorithm are dynamically switched according to the current stage.

[0027] The core control objectives differ across different stages of moxibustion, resulting in varying optimal control characteristics. Therefore, the controller is pre-configured with corresponding control algorithm parameters for each stage. When the continuous control algorithm employs PID control, the parameters include proportional gain Kp, integral gain Ki, and derivative gain Kd. These parameters can be configured through prior debugging and calibration, stored in the controller's memory unit, and automatically recalled during stage switching.

[0028] For example, in the preheating stage, the core objective of control is to rapidly and steadily raise the temperature to the treatment temperature. Therefore, the corresponding control parameter will appropriately increase the proportional gain Kp to improve the system's response speed and ensure that the temperature rises at the preset rate. At the same time, the differential gain Kd will be adjusted to limit excessively rapid temperature rise. In the constant temperature moxibustion stage, the core objective of control is to maintain temperature stability and minimize temperature fluctuations. Therefore, the corresponding control parameter will appropriately increase the integral gain Ki to enhance the ability to eliminate steady-state errors. At the same time, the differential gain Kd will be optimized to suppress fluctuations and ensure that the temperature remains stable near the target value. In the cooling and finishing stage, the core objective of control is to allow the temperature to drop smoothly. Therefore, the corresponding control parameter will appropriately decrease the proportional gain Kp to reduce the adjustment sensitivity, avoid excessively frequent adjustments, and ensure a smooth temperature decrease.

[0029] During moxibustion, when the controller determines a switch in the moxibustion stage based on the treatment duration t, it automatically retrieves the control algorithm parameters corresponding to the next stage from the storage unit and replaces the Kp, Ki, and Kd values ​​used in the current control calculation, thus completing the dynamic switching of control characteristics. Through this staged parameter adaptation method, the system can maintain optimal control performance at different stages of moxibustion, taking into account the response speed, stability, and comfort requirements of different stages.

[0030] In some embodiments, the storage unit of the controller has a built-in acupoint temperature control strategy database, which stores temperature control parameter groups corresponding to various acupoint types. After the controller obtains the selected acupoint type, it retrieves the temperature control parameter set of the corresponding acupoint from the database and performs temperature control based on the parameter set.

[0031] The controller's storage unit contains a database of acupoint temperature control strategies, which pre-stores temperature control parameter sets corresponding to various common acupoints for moxibustion. Different acupoints have varying skin thickness, subcutaneous tissue distribution, nerve sensitivity, and heat conduction characteristics, resulting in different suitable moxibustion temperatures and control characteristics. Therefore, the parameter sets in the database are calibrated based on the physiological characteristics of each acupoint and clinical moxibustion experience.

[0032] Before moxibustion, the user can select the acupoint type to be treated through the system's interactive interface. After receiving the acupoint selection command, the controller retrieves the temperature control parameter set matching the acupoint type from the acupoint temperature control strategy database and loads this parameter set into the current control calculation program as the calculation basis for the temperature control of this moxibustion treatment. This includes the corresponding target temperature range, control algorithm parameters, and heating rate limits. The parameter retrieval and loading process is completed automatically, eliminating the need for manual parameter setting and improving operational convenience.

[0033] Through an acupoint temperature control strategy database and an automatic parameter recall mechanism, the system can automatically match a unique temperature control strategy for different acupoints, achieving precise control with a "one acupoint, one strategy" approach. This differentiated control method allows the temperature control logic to better adapt to the physiological characteristics of acupoints, ensuring both the therapeutic effect of moxibustion and improving comfort during moxibustion at different acupoints, thus avoiding the inadequacy of adaptability issues caused by general control strategies.

[0034] In some embodiments, each set of temperature control parameters in the acupoint temperature control strategy database includes a target temperature range, control algorithm parameters, and a heating rate limit.

[0035] The first type of parameter in the acupoint temperature control parameter set is the target temperature range. The target temperature range is the appropriate range of moxibustion temperature for the corresponding acupoint, including both the upper and lower temperature limits, and serves as the benchmark for setting the target temperature Tset(t). Different acupoints have different target temperature ranges: for acupoints requiring stronger heat stimulation, the target temperature range value is relatively higher; for acupoints with thinner skin and higher sensitivity, the target temperature range value is relatively lower, thus adapting to the different stimulation intensity requirements of each acupoint.

[0036] The second type of parameter is the control algorithm parameter, which is a continuous control algorithm parameter adapted to the thermal response characteristics of the corresponding acupoint. When using a PID control algorithm, this includes dedicated proportional gain Kp, integral gain Ki, and derivative gain Kd. Different acupoints have different skin heat conduction speeds and thermal inertia, resulting in different optimal control parameters. Configuring dedicated control algorithm parameters for each acupoint ensures that the system's response speed and stability are optimal when applying moxibustion to the corresponding acupoint, avoiding a decrease in control effectiveness due to differences in acupoint thermal characteristics and improving the accuracy of temperature control.

[0037] The third type of parameter is the heating rate limit, which is the maximum allowable temperature rise rate for the corresponding acupoint. It is the upper limit constraint value of the temperature change rate dT / dt. This parameter is used to limit the rate of temperature rise in the initial stage of moxibustion to avoid strong stimulation to the skin caused by a sudden temperature increase. For acupoints with higher sensitivity, a lower heating rate limit is set to ensure a gradual temperature rise; for acupoints with higher tolerance, a relatively higher heating rate limit can be set. This parameter further improves the differentiated control of acupoints, enhancing the comfort and safety of moxibustion.

[0038] In some embodiments, the continuous control algorithm is a PID control algorithm or a fuzzy control algorithm; When a PID control algorithm is used, the control algorithm parameters include proportional gain, integral gain, and derivative gain.

[0039] This embodiment can employ either a PID control algorithm or a fuzzy control algorithm. Both algorithms fall under the category of continuous control algorithms and can output a continuous, stepless height adjustment ΔH(t), adapting to the temperature control requirements of moxibustion scenarios. In practical applications, the appropriate algorithm can be selected based on the product's positioning, cost, and control precision requirements. Alternatively, both algorithms can be built into the system simultaneously, switching between them according to the scenario.

[0040] When using a PID control algorithm, the core control parameters include the proportional gain Kp, integral gain Ki, and derivative gain Kd. The proportional gain Kp determines the amplitude of the control response; the larger the temperature deviation e(t), the stronger the output regulation, used to quickly correct the temperature deviation. The integral gain Ki is used to accumulate historical temperature deviations e(t), gradually eliminating the system's steady-state error and ensuring that the temperature eventually stably matches the target value Tset(t). The derivative gain Kd outputs a reverse regulation based on the temperature change rate dT / dt, suppressing excessively rapid temperature changes, reducing temperature overshoot, and improving system stability. These three parameters work together to determine the dynamic and steady-state performance of the PID control.

[0041] When using a fuzzy control algorithm, the system takes temperature deviation e(t) and temperature change rate dT / dt as two input quantities. First, the precise input values ​​are fuzzified according to a preset fuzzy subset, converting them into fuzzy quantities. Then, fuzzy inference is performed based on a pre-built fuzzy control rule base, which is formed from experience in moxibustion temperature control and covers adjustment strategies corresponding to various temperature states. After inference, defuzzification is performed, and the precise height adjustment amount ΔH(t) is output. Fuzzy control does not require establishing a precise system mathematical model, and for nonlinear, high-inertia, and parameter-uncertain temperature control scenarios like moxibustion, it has stronger robustness and environmental adaptability.

[0042] In some embodiments, the controller includes a three-layer collaborative security protection mechanism: The first layer is an active continuous regulation layer, which maintains the skin temperature within the target temperature range through closed-loop continuous control. The second layer is the predictive intervention layer, which predicts risks by monitoring the rate of temperature change and adjusts the height of the therapy head in advance to correct temperature trends. The third layer is an emergency hard protection layer, which has preset safe temperature thresholds and minimum height thresholds. When the detected value exceeds the corresponding threshold, the robotic arm will be immediately controlled to reset and stop.

[0043] The first layer is the active continuous adjustment layer. This layer is the fundamental safety mechanism for the system's normal operation, implemented through a core closed-loop continuous temperature control logic that runs throughout the entire moxibustion process. This layer collects temperature T(t) and height H(t) in real time, calculates the temperature deviation e(t) and the rate of temperature change dT / dt, and outputs a continuous base height adjustment amount ΔHbase(t). This closed-loop control dynamically adjusts the height of the treatment head, actively maintaining the skin temperature T(t) within the preset target temperature range. This reduces the probability of temperature deviating from the safe range from the source, making it the most basic and core active safety guarantee.

[0044] The second layer is the predictive intervention layer, a proactive safety mechanism. This layer monitors the rate of temperature change (dT / dt) in real time to predict temperature trends. When |dT / dt| exceeds the trend threshold, indicating a potential risk of overheating, it will initiate regulation in advance, even if the current skin temperature T(t) is still within the normal safe range. It calculates a predictive compensation amount ΔHpredict and adds it to the height adjustment amount to adjust the therapy head height in advance, correcting the temperature trend. This layer can eliminate potential safety risks at their inception, compensate for the lag in conventional closed-loop control, and further improve the safety and stability of temperature control.

[0045] The third layer is the emergency hard protection layer, which is the system's highest priority fallback safety mechanism. The controller is pre-set with absolute safety thresholds, including a safe temperature threshold and a minimum height threshold, corresponding to the critical temperature for skin burns and the safe distance between the treatment head and the skin, respectively. When the controller detects that the skin temperature T(t) exceeds the safe temperature threshold, or the treatment head height H(t) is below the minimum height threshold, it immediately triggers the highest priority interrupt procedure, suspending all regular control logic and directly controlling the multi-degree-of-freedom robotic arm to quickly lift and reset the moxibustion treatment head before stopping the machine. This layer is used to deal with extreme situations such as control logic anomalies and sensor failures, serving as the final safety line to ensure the absolute safety of moxibustion. These three protective mechanisms work together to form a complete safety system from proactive maintenance to early intervention and emergency fallback.

[0046] The embodiments of this application will now be described in detail with reference to practical applications.

[0047] The overall structure of the moxibustion robot system in this embodiment is as follows: Figure 1 As shown, the system includes a support base, a multi-degree-of-freedom robotic arm 1 mounted on the base, and a moxibustion therapy head fixed to the end of the robotic arm. The therapy head has a moxa stick combustion chamber 5 inside for placing and burning moxa sticks. The end face of the therapy head is integrated with a temperature sensor 2 and two sets of distance sensors 3 and 4. The temperature sensor 2 is aligned with the center of the moxibustion area to collect the skin surface temperature T(t). The two sets of distance sensors 3 and 4 are symmetrically distributed on the outer periphery of the moxa stick combustion chamber 5 to detect the vertical height H(t) between the therapy head and the skin. The system also includes a controller 6, which is electrically connected to the multi-degree-of-freedom robotic arm 1, the temperature sensor 2, and the distance sensors 3 and 4, respectively, to receive the sensor signals and output motion control commands.

[0048] The overall control logic flow of this embodiment is as follows: Figure 2 As shown, after the system starts, it first enters step S1, where the controller collects the skin surface temperature T(t) output by the temperature sensor and the height H(t) of the therapy head output by the distance sensor in real time, and records the current moxibustion duration and the selected acupoint type. Then, it enters step S2, which calls the acupoint temperature control model to obtain the corresponding target temperature range, control parameters, and heating rate limit. Next, it enters step S4 to calculate the instantaneous temperature deviation e(t) = T_set(t) - T(t) and the temperature change rate dT / dt. Then, in step S5, the basic height adjustment amount ΔH_base(t) is calculated through a continuous control algorithm. After that, in step S6, predictive adjustment judgment is performed, and the predictive compensation amount is superimposed based on whether the temperature change rate exceeds the threshold to obtain the final height adjustment amount ΔH(t). Then, step S7 is executed to control the robotic arm to adjust the height of the therapy head. Finally, after completing the three-layer safety detection in step S8, it returns to step S1 to enter the next control cycle, forming a continuous closed-loop operation.

[0049] The operation flow of the dynamic continuous temperature control module in this embodiment is as follows: Figure 3 As shown, after the module starts, it first inputs the current actual skin temperature T(t) and the target temperature T_set(t); then it calculates the instantaneous temperature deviation e(t) = T(t) - T_set(t), and simultaneously calculates the rate of temperature change over time dT / dt; the temperature deviation e(t) and the rate of temperature change dT / dt are input together into the PID / fuzzy control operation unit, and through the weighted operation of proportional, integral, and derivative operations or fuzzy rule reasoning, the continuous stepless height adjustment ΔH(t) is output; this module abandons the traditional threshold switch-type adjustment, and realizes smooth fine adjustment of the height of the therapy head through continuous control algorithm, ensuring that the skin temperature is stably in line with the target value and reducing the temperature fluctuation amplitude.

[0050] The operation flow of the temperature-time coupling control module in this embodiment is as follows: Figure 4 As shown, after the module starts, it takes the current cumulative moxibustion treatment time t as input; then it enters the stage judgment step, which divides the moxibustion treatment process into three intervals according to the preset time nodes: the preheating stage from 0 to t1, the constant temperature moxibustion stage from t1 to t2, and the cooling and finishing stage from t2 to the end; the corresponding dynamic target temperature T_set(t) is generated according to the current stage, where T_set(t) rises slowly in the preheating stage, remains constant in the constant temperature stage, and slowly falls in the cooling stage; at the same time, the three parameters of the PID control algorithm, namely proportional gain Kp, integral gain Ki, and derivative gain Kd, are dynamically adjusted to match the control characteristics with the control requirements of the corresponding stage, so as to realize dynamic adaptive control of the entire moxibustion treatment cycle.

[0051] In this embodiment, the operation flow of the acupoint coupling temperature control module is as follows: Figure 5 As shown, after the module starts, the user-selected acupoint type is first input; then the controller calls the built-in acupoint temperature control strategy database to match the control parameter group corresponding to the current acupoint type; this parameter group contains three types of parameters: the first type is the target temperature range corresponding to the acupoint, used to set the baseline range of temperature control; the second type is the control algorithm parameters adapted to the thermal characteristics of the acupoint to ensure the accuracy of control; the third type is the heating rate limit corresponding to the acupoint, used to constrain the temperature rise rate in the early stage of moxibustion; after the parameter matching is completed, the complete control model parameters are output and loaded into the main control program for execution to achieve differentiated and precise moxibustion for different acupoints.

[0052] The operation flow of the predictive adjustment module in this embodiment is as follows: Figure 6As shown, the module first establishes a calculation model for the temperature change rate dT / dt based on the system's thermal characteristics. During operation, the current temperature change rate dT / dt is input in real time, and its absolute value is checked to see if it exceeds a preset trend threshold. If it does not exceed the threshold, no compensation is applied, and the module's calculation ends directly. If it exceeds the threshold, a prediction calculation is initiated, predicting the temperature change trend in the near future based on the current temperature and the temperature change rate, and calculating the corresponding prediction compensation amount ΔH_predict. Finally, the prediction compensation amount is output and superimposed on the base height adjustment amount. By adjusting in advance in a feedforward manner, the system's thermal inertia is offset, the temperature overshoot phenomenon is suppressed, and the risk is eliminated at the nascent stage.

[0053] The operation flow of the three-layer collaborative security protection system in this embodiment is as follows: Figure 7 As shown, after the system starts, it enters a real-time monitoring state. First, it runs the first-layer continuous adjustment mechanism, which maintains the temperature within the target range through closed-loop continuous control, achieving proactive basic safety protection. Then, it enters the trend judgment step, which detects in real time whether the temperature change rate exceeds the safe range. If it does, the second-layer predictive intervention mechanism is activated to adjust the height of the treatment head in advance to correct the temperature trend, achieving proactive risk prevention and control. If the trend is normal, it enters the third-layer limit judgment step, which detects whether the current skin temperature exceeds the safe temperature threshold of 60°C and whether the height of the treatment head is lower than the minimum safe height threshold. If they exceed, an emergency stop and robotic arm reset are immediately triggered as a fallback protection. If everything is normal, it returns to the control loop and continues to run. The three-layer mechanism together constructs a three-dimensional and in-depth safety protection network.

[0054] This application also provides an adaptive control method for a moxibustion robot based on temperature feedback, comprising the following steps: Real-time acquisition of skin temperature and treatment head height data; calculation of the deviation between the current temperature and the target temperature, as well as the rate of temperature change. The temperature deviation value and temperature change rate are taken as inputs, and the height adjustment amount is calculated and output through a continuous control algorithm. The movement of the multi-degree-of-freedom robotic arm is controlled by adjusting the height to adjust the distance between the moxibustion therapy head and the skin.

[0055] This embodiment provides an adaptive control method for a moxibustion robot based on temperature feedback. The control system is constructed using skin temperature as the feedback quantity, and the height of the treatment head is dynamically adjusted throughout the process via continuous digital computation. During operation, the controller collects the skin surface temperature T(t) detected by the temperature sensor and the treatment head height H(t) detected by the distance sensor in real time at a fixed sampling period. The raw data is then subjected to sliding filtering to eliminate abnormal fluctuations caused by environmental airflow and sensor noise, ensuring the stability of the input data. Based on the collected temperature data, the controller calculates two core state variables: one is the instantaneous temperature deviation, calculated using the formula e(t) = Tset(t). T(t), where Tset(t) is the target temperature at the current moment, which directly reflects the degree and direction of deviation between the actual temperature and the target value; the second is the temperature change rate dT / dt, which is calculated in engineering by dividing the temperature difference between two adjacent sampling periods by the sampling time interval, and is used to characterize the speed and trend of temperature rise and fall.

[0056] After completing the state variable calculation, the method enters the continuous control algorithm operation stage. Using the temperature deviation value e(t) and the temperature change rate dT / dt as dual inputs, the method outputs the height adjustment amount ΔH(t) through a preset continuous control algorithm. This continuous control algorithm can employ PID control or fuzzy control, and the output height adjustment amount ΔH(t) is a stepless continuous value, corresponding to any size of lifting or lowering displacement of the therapy head, unlike traditional gear-type or on / off type adjustments. Taking PID control as an example, the proportional term outputs the adjustment amount proportionally to the magnitude of the temperature deviation e(t), achieving rapid response to the deviation; the integral term accumulates historical temperature deviations, gradually eliminating long-term steady-state errors to ensure that the temperature eventually stably matches the target value; the derivative term outputs a reverse adjustment amount based on the temperature change rate dT / dt, suppressing excessively rapid temperature changes and reducing overshoot; the continuous height adjustment amount ΔH(t) is obtained by weighted summation of the three parameters.

[0057] After obtaining the height adjustment amount ΔH(t), the method enters the execution phase. The controller converts the height adjustment amount into motion control commands for each joint of the multi-degree-of-freedom robotic arm. By driving the servo motors, the moxibustion therapy head at the end effector rises and falls by the corresponding distance, thus adjusting the distance between the therapy head and the skin. After a single adjustment is completed, the method returns to the data acquisition step and enters the next control cycle. In this way, the skin temperature T(t) can continuously and stably track the target temperature Tset(t), achieving a high-precision adaptive temperature control effect.

[0058] This application also provides a moxibustion robot, which includes the temperature feedback-based adaptive control system for moxibustion robots described in any of the above embodiments.

[0059] This embodiment uses the temperature feedback-based adaptive control system of the moxibustion robot from the above embodiments as the core control unit, integrating it into the hardware architecture of the robot. This enables the robot to possess intelligent moxibustion capabilities such as adaptive temperature control, differentiated acupoint regulation, and multi-level safety protection. This adaptive control system is the core computing and control center of the robot, responsible for integrating data collected from all sensors, running the entire temperature control algorithm, outputting motion and function control commands, and coordinating all moxibustion-related functions of the robot.

[0060] The moxibustion robot comprises a support base, a multi-degree-of-freedom robotic arm, a moxibustion therapy head, sensing components, a human-computer interaction unit, and a power supply unit. The multi-degree-of-freedom robotic arm, mounted on the base, possesses multi-degree-of-freedom spatial movement capabilities, enabling it to move the end-effector moxibustion therapy head to the corresponding position of any acupoint on the human body. The moxibustion therapy head contains a moxa stick combustion chamber to hold the moxa stick and provide a stable combustion space. The sensing components include temperature and distance sensors, integrated into the moxibustion end face of the therapy head, used to collect real-time data on skin temperature and head height during the moxibustion process, providing stable feedback input for the adaptive control system.

[0061] During operation, the adaptive control system receives real-time data from the sensing components and runs its built-in continuous temperature control algorithm, acupoint adaptation model, predictive adjustment logic, and three-layer safety protection mechanism. It outputs precise height adjustment commands to the multi-degree-of-freedom robotic arm and dynamically adjusts the control strategy according to the moxibustion stage and acupoint type, achieving intelligent and personalized moxibustion therapy. Equipped with this adaptive control system, the moxibustion robot can maintain a stable and suitable moxibustion temperature without frequent manual height adjustments, while also possessing multiple safety protection capabilities, significantly improving the accuracy, comfort, and safety of moxibustion.

[0062] In summary, the embodiments of this application have the following beneficial effects: By employing a continuous control algorithm to replace traditional on / off threshold regulation, the robot can output stepless and continuous height adjustment, achieving smooth fine-tuning of the treatment head height, significantly reducing skin temperature fluctuations, and greatly improving the accuracy and stability of temperature control. By introducing temperature-time coupled control logic, the target temperature and control parameters can be dynamically adjusted according to the moxibustion process, conforming to the physiological laws of human skin's thermal adaptation and simulating the phased techniques of manual moxibustion, thus improving the comfort of the treatment process. Through a built-in acupoint temperature control strategy database, differentiated temperature control parameters can be matched for different acupoints, achieving precise moxibustion with a "one acupoint, one strategy" approach, adapting to the heat conduction characteristics and stimulation intensity requirements of different acupoints, and implementing the concept of syndrome differentiation and moxibustion in traditional Chinese medicine. By adding a predictive adjustment mechanism, temperature trends can be predicted in advance based on the rate of temperature change and feedforward compensation can be applied, effectively offsetting system thermal inertia and suppressing temperature overshoot, shifting risk prevention from post-treatment remediation to pre-intervention. Combined with a three-layer collaborative safety protection system, a comprehensive and in-depth safety network is constructed, significantly reducing safety risks such as burns, and overall significantly improving the intelligence level, therapeutic effect, and safety of the moxibustion robot.

[0063] In the several embodiments provided in this application, it should be understood that the disclosed methods and electronic devices can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components may be combined, or integrated into another system, or some features may be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0064] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0065] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0066] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a platform server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0067] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An adaptive control system for a moxibustion robot based on temperature feedback, characterized in that, The device includes a base, a multi-degree-of-freedom robotic arm, a moxibustion therapy head, a temperature sensor, a distance sensor, and a controller. The moxibustion therapy head is located at the end of the multi-degree-of-freedom robotic arm. The temperature sensor is used to collect the skin surface temperature, and the distance sensor is used to collect the distance between the moxibustion therapy head and the skin. The controller is electrically connected to the multi-degree-of-freedom robotic arm, the temperature sensor, and the distance sensor. The controller is configured to: Real-time acquisition of skin temperature and treatment head height data; calculation of the deviation between the current temperature and the target temperature, as well as the rate of temperature change. The temperature deviation value and temperature change rate are taken as inputs, and the height adjustment amount is calculated and output through a continuous control algorithm. The movement of the multi-degree-of-freedom robotic arm is controlled by adjusting the height to adjust the distance between the moxibustion therapy head and the skin.

2. The adaptive control system for the moxibustion robot based on temperature feedback according to claim 1, characterized in that, The controller is also configured to perform predictive regulation, specifically including: A preset trend threshold for the rate of temperature change is used to determine in real time whether the absolute value of the rate of temperature change exceeds the trend threshold. If the value exceeds the limit, the corresponding predicted compensation amount is calculated and added to the height adjustment amount to suppress temperature overshoot by adjusting in advance.

3. The adaptive control system for the moxibustion robot based on temperature feedback according to claim 1, characterized in that, The controller is also configured to perform temperature-time coupled control, specifically including: The moxibustion process is divided into multiple stages based on the cumulative duration of moxibustion treatment, and a corresponding target temperature is configured for each stage. During the moxibustion process, the target temperature value is dynamically updated based on the current stage.

4. The adaptive control system for the moxibustion robot based on temperature feedback according to claim 3, characterized in that, The controller is also configured with corresponding control algorithm parameters for different moxibustion stages; during the moxibustion process, the running parameters of the continuous control algorithm are dynamically switched according to the current stage.

5. The adaptive control system for the moxibustion robot based on temperature feedback according to claim 1, characterized in that, The controller's storage unit has a built-in acupoint temperature control strategy database, which stores temperature control parameter groups corresponding to various acupoint types. After the controller obtains the selected acupoint type, it retrieves the temperature control parameter set of the corresponding acupoint from the database and performs temperature control based on the parameter set.

6. The adaptive control system for the moxibustion robot based on temperature feedback according to claim 5, characterized in that, In the acupoint temperature control strategy database, each set of temperature control parameters includes a target temperature range, control algorithm parameters, and a heating rate limit.

7. The temperature feedback-based adaptive control system for a moxibustion robot according to any one of claims 1-6, characterized in that, The continuous control algorithm is either a PID control algorithm or a fuzzy control algorithm; When a PID control algorithm is used, the control algorithm parameters include proportional gain, integral gain, and derivative gain.

8. The adaptive control system for the moxibustion robot based on temperature feedback according to claim 1, characterized in that, The controller includes a three-layer collaborative security protection mechanism: The first layer is an active continuous regulation layer, which maintains the skin temperature within the target temperature range through closed-loop continuous control. The second layer is the predictive intervention layer, which predicts risks by monitoring the rate of temperature change and adjusts the height of the therapy head in advance to correct temperature trends. The third layer is an emergency hard protection layer, which has preset safe temperature thresholds and minimum height thresholds. When the detected value exceeds the corresponding threshold, the robotic arm will be immediately controlled to reset and stop.

9. An adaptive control method for a moxibustion robot based on temperature feedback, characterized in that, Includes the following steps: Real-time acquisition of skin temperature and treatment head height data; calculation of the deviation between the current temperature and the target temperature, as well as the rate of temperature change. The temperature deviation value and temperature change rate are taken as inputs, and the height adjustment amount is calculated and output through a continuous control algorithm. The movement of the multi-degree-of-freedom robotic arm is controlled by adjusting the height to adjust the distance between the moxibustion therapy head and the skin.

10. A moxibustion robot, characterized in that, The moxibustion robot includes the temperature feedback-based adaptive control system for moxibustion robots as described in any one of claims 1-8.

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