Micro servo motor control method and system

Abstract

The invention discloses a micro servo motor control method and system, and the method specifically comprises the steps: estimating the load torque of a micro servo motor in real time through an extended Kalman filtering model, inputting the load torque into a feedforward controller to generate a compensation voltage, superposing the compensation voltage with a voltage control parameter outputted by a PID controller, and dynamically adjusting the PWM duty ratio; inputting the PWM duty ratio and the armature current of the micro servo motor into a sliding mode observer to generate a rotating speed observation value of the micro servo motor, and determining whether a brake signal is generated or not according to the deviation between the rotating speed observation value and a preset target rotating speed; and when it is determined that the brake signal is generated, the feedback current and the PWM duty ratio of the micro servo motor are adjusted in real time through the rotating speed observation value. The problems of low braking efficiency, poor dynamic response, weak anti-interference capability, insufficient power consumption control and the like in a micro servo motor control method are effectively solved, and a more efficient, reliable and accurate control scheme is provided for application of the micro servo motor.

Description

Technical Field

[0001] This invention relates to the field of micro servo motor technology, and in particular to a micro servo motor control method and system. Background Technology

[0002] Miniature servo motors, due to their small size, high precision, and fast response, have been widely used in precision machinery, automation equipment, robotics, and other fields. However, existing miniature servo motor control methods still face many challenges and struggle to meet the application requirements of high precision, high efficiency, and high reliability.

[0003] Firstly, regarding braking efficiency, traditional control methods typically employ direct power disconnection during rapid shutdown. This can lead to the ineffective release of residual electrical energy in the motor, resulting in damage to circuit components and a shortened motor lifespan. Simultaneously, the lack of an effective energy feedback mechanism results in low energy utilization during braking.

[0004] Secondly, regarding dynamic response, the sudden acceleration of a micro servo motor during startup can easily cause mechanical vibration, affecting the system's stability and accuracy. Traditional trapezoidal acceleration curves cannot dynamically adjust to load changes, leading to accumulated positioning errors and shortened motor lifespan. Furthermore, dynamic load disturbances are also a significant factor affecting speed tracking accuracy. Traditional PID controllers have long response times and are prone to triggering overcurrent protection during sudden load changes, impacting normal system operation.

[0005] Furthermore, in terms of anti-interference capability, external disturbances (such as vibration) can easily cause braking position drift, and the drift amount of traditional methods is difficult to meet the requirements of high-precision positioning. At the same time, low energy feedback efficiency is also a significant drawback of traditional control methods.

[0006] Finally, in terms of power consumption control and fault protection, traditional single-parameter protection methods are prone to false triggering, and response delays may increase the risk of component damage. The lack of a comprehensive fault determination mechanism that considers multiple dimensions means that the accuracy and reliability of fault protection need to be improved. Summary of the Invention

[0007] The purpose of this invention is to provide a micro servo motor control method and system, which effectively solves the problems of low braking efficiency, poor dynamic response, weak anti-interference ability and insufficient power consumption control in micro servo motor control methods, and provides a more efficient, reliable and accurate control scheme for the application of micro servo motors, thereby solving at least one of the above-mentioned problems in the prior art.

[0008] In a first aspect, the present invention provides a method for controlling a micro servo motor, the method specifically comprising:

[0009] A continuous acceleration curve is generated based on the moment of inertia and maximum allowable acceleration of the micro servo motor. The inflection point time is dynamically adjusted by real-time detection of the load current and position deviation of the micro motor, providing an initial stable state for the extended Kalman filter model.

[0010] The load torque of the micro servo motor is estimated in real time by using an extended Kalman filter model. The estimated load torque is then input into the feedforward controller to generate a compensation voltage, which is then superimposed on the voltage control parameters output by the PID controller to dynamically adjust the PWM duty cycle.

[0011] The PWM duty cycle and the armature current of the micro servo motor are input into the sliding mode observer to generate the speed observation value of the micro servo motor. The deviation between the speed observation value and the preset target speed determines whether to generate a braking signal.

[0012] When a braking signal is detected, the feedback current and PWM duty cycle of the micro servo motor are adjusted in real time based on the observed speed value.

[0013] A three-dimensional fault determination space including temperature, current and voltage is set up. The micro servo motor is fault detected based on the three-dimensional fault determination space. If a fault is determined, the miniaturization protection mechanism is triggered, and the protection parameter thresholds of the micro servo motor are readjusted by the moment of inertia and the maximum allowable acceleration.

[0014] Secondly, the present invention provides a micro servo motor control system, the system specifically comprising:

[0015] The first control module is used to generate a continuous acceleration curve based on the rotational inertia and maximum allowable acceleration of the micro servo motor, and dynamically adjust the inflection point time by real-time detection of the load current and position deviation of the micro motor, so as to provide an initial stable state for the extended Kalman filter model.

[0016] The second control module is used to estimate the load torque of the micro servo motor in real time through the extended Kalman filter model, input the estimated load torque into the feedforward controller to generate a compensation voltage, and superimpose it with the voltage control parameters output by the PID controller to dynamically adjust the PWM duty cycle.

[0017] The third control module is used to input the PWM duty cycle and the armature current of the micro servo motor into the sliding mode observer to generate the speed observation value of the micro servo motor, and determine whether to generate a braking signal based on the deviation between the speed observation value and the preset target speed.

[0018] The fourth control module is used to adjust the feedback current and PWM duty cycle of the micro servo motor in real time based on the observed speed value when a braking signal is determined to be generated.

[0019] The fifth control module is used to set up a three-dimensional fault judgment space including temperature, current and voltage. Based on the three-dimensional fault judgment space, the micro servo motor is fault detected. If a fault is determined, the miniaturization protection mechanism is triggered, and the protection parameter thresholds of the micro servo motor are readjusted by the moment of inertia and the maximum allowable acceleration.

[0020] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, and a computer program stored in the memory, wherein when the computer program is executed on the processor, it implements the micro servo motor control method as described in any of the above methods.

[0021] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the micro servo motor control method as described in any of the above methods.

[0022] Compared with the prior art, the present invention has at least one of the following technical effects:

[0023] 1. This invention effectively solves the problems of low braking efficiency, poor dynamic response, weak anti-interference ability and insufficient power consumption control in the control method of micro servo motor, and provides a more efficient, reliable and precise control scheme for the application of micro servo motor.

[0024] 2. This invention generates a continuous acceleration curve and dynamically adjusts the inflection point time to provide an initial stable state for the extended Kalman filter model, thereby improving the system's dynamic response speed and anti-interference capability.

[0025] 3. This invention achieves dynamic adjustment of the PWM duty cycle by combining a feedforward controller and a PID controller, thereby optimizing the braking strategy and improving energy feedback efficiency.

[0026] 4. This invention introduces a sliding mode observer to generate rotational speed observation values, and determines whether to generate a braking signal based on the deviation between the rotational speed observation values ​​and the preset target rotational speed, thereby further improving braking accuracy and efficiency.

[0027] 5. This invention sets up a three-dimensional fault judgment space including temperature, current and voltage, realizing comprehensive fault detection and protection of micro servo motors, reducing the false trigger rate and the risk of component damage.

[0028] 6. This invention improves the control accuracy and response speed of micro servo motors by dynamically adjusting the inflection point time of the acceleration curve and estimating the load torque in real time, thereby optimizing the PWM duty cycle. At the same time, it sets up a fault judgment space to enhance system reliability.

[0029] 7. This invention dynamically adjusts the inflection point of the third-order S-curve acceleration curve based on load current and position deviation, making the motor movement smoother and reducing mechanical shock.

[0030] 8. This invention estimates the load torque in real time using an extended Kalman filter model, and combines feedforward and PID control to dynamically adjust the PWM duty cycle, thereby improving the stability and accuracy of motor speed control.

[0031] 9. This invention constructs the dynamic equation of the sliding mode observer, generates speed observation values ​​in real time, and determines the braking signal based on the deviation and rate of change, thereby improving the accuracy and timeliness of braking control.

[0032] 10. This invention optimizes the braking process and improves energy utilization efficiency by adjusting the feedback current and PWM duty cycle in real time through energy feedback formula and PWM chopper braking formula.

[0033] 11. This invention sets up a three-dimensional fault judgment space, calculates the fault detection value through weighted Euclidean distance, and triggers the protection mechanism in a timely manner, thereby enhancing the system's fault detection and protection capabilities.

[0034] 12. This invention updates the protection parameter thresholds in real time based on the moment of inertia and the maximum permissible acceleration, making the protection mechanism more adaptable to the working state of the motor, improving the accuracy and adaptability of fault protection, as well as the reliability and safety of the system. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a flowchart illustrating a micro servo motor control method according to an embodiment of the present invention;

[0037] Figure 2 This is a schematic diagram of a micro servo motor control system provided in an embodiment of the present invention;

[0038] Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0039] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0040] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0041] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0042] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0043] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0044] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0045] In this application embodiment, the entity executing the process includes a terminal device. This terminal device includes, but is not limited to, devices capable of executing the methods disclosed in this application, such as servers, computers, smartphones, and tablets. Figure 1 A flowchart illustrating a micro servo motor control method according to an embodiment of the present invention is shown below, detailed in the following description:

[0046] S101 generates a continuous acceleration curve based on the moment of inertia and maximum allowable acceleration of the micro servo motor, and dynamically adjusts the inflection point time by real-time detection of the load current and position deviation of the micro motor, providing an initial stable state for the extended Kalman filter model.

[0047] In this embodiment, the moment of inertia of the micro servo motor is first measured (e.g., through experimental methods or by referring to data provided by the motor manufacturer) to determine the maximum allowable acceleration of the motor (which is typically determined by the motor's design specifications and operating conditions). Then, based on the moment of inertia and maximum allowable acceleration of the micro servo motor, a third-order S-curve acceleration curve is constructed. This curve includes an acceleration rise phase, a constant speed phase, and an acceleration fall phase, ensuring smooth acceleration changes during motor start-up and shutdown, reducing mechanical shock. The initial times for the acceleration rise phase, the constant speed phase, and the acceleration fall phase are set; these time parameters can be adjusted according to the specific performance of the motor and application requirements. During motor operation, the load current of the micro motor is monitored in real time using a current sensor. Changes in the load current reflect changes in external resistance and load on the motor. Simultaneously, the angular difference between the actual position and the target position of the micro servo motor, i.e., the position deviation, is monitored in real time using a position sensor (such as an encoder). Based on the dynamic changes in load current and position deviation, the inflection point time of the third-order S-curve acceleration curve is adjusted in real time. For example, when the load current increases or the position deviation is large, the time of the acceleration rise phase is appropriately extended to ensure smooth motor acceleration; when the load current decreases or the position deviation is small, the time of the acceleration fall phase is shortened to improve the positioning speed. Before motor startup, initial state parameters are set for the extended Kalman filter model based on the adjusted acceleration curve and the motor's initial state (e.g., stationary state). The extended Kalman filter model is then used to estimate the motor speed and load torque in real time, providing accurate feedback information for subsequent control strategies.

[0048] In this embodiment, by constructing a third-order S-shaped acceleration curve, smooth acceleration changes during motor start-up and shutdown are achieved, reducing mechanical shock and vibration, and improving the motor's positioning accuracy and stability. Real-time detection of load current and position deviation, along with dynamic adjustment of the inflection point time of the acceleration curve, enables the motor to adapt to different load conditions and external disturbances, maintaining smooth motion. Providing an accurate initial steady state for the extended Kalman filter model improves the estimation accuracy of speed and load torque, offering better input conditions for subsequent control strategies (such as feedforward control and PID control), thereby optimizing the motor's control performance.

[0049] S102 estimates the load torque of the micro servo motor in real time through an extended Kalman filter model. The estimated load torque is input to the feedforward controller to generate a compensation voltage, which is then superimposed with the voltage control parameters output by the PID controller to dynamically adjust the PWM duty cycle.

[0050] In this embodiment, the armature current, speed, and load torque of the micro servo motor are selected as the state variables of the extended Kalman filter model, as these variables can comprehensively reflect the motor's operating state. Based on the motor's physical characteristics and electrical equations, state equations and observation equations are constructed. The state equations describe the relationship between the motor's state variables and time, while the observation equations establish the relationship between the state variables and measurable quantities (such as armature current and voltage). The initial conditions of the extended Kalman filter model are set according to the motor's initial state (such as stationary or low-speed operation) and known parameters (such as moment of inertia and armature resistance).

[0051] The motor's armature current and voltage signals are acquired in real time using sensors. The acquired data is input into an extended Kalman filter model for state prediction and observation updates. Through iterative calculations, real-time estimates of the motor speed and load torque are obtained. Based on the motor's control requirements and dynamic characteristics, a compensation formula for the feedforward controller is designed. This formula converts the estimated load torque into a compensation voltage to offset the impact of load changes on the motor speed. The estimated load torque is input into the feedforward controller, and the compensation voltage is calculated according to the compensation formula.

[0052] In a PID controller, the PID control quantity (including proportional, integral, and derivative parts) is calculated based on the deviation between the setpoint and the estimated speed. The compensation voltage output from the feedforward controller is then superimposed with the voltage control parameters output from the PID controller to obtain the final total voltage control quantity. Based on this total voltage control quantity, a corresponding PWM signal is generated. The duty cycle of the PWM signal determines the average voltage of the motor, thus affecting the motor's speed and torque. During motor operation, the duty cycle of the PWM signal is dynamically adjusted based on changes in load torque and speed feedback to achieve precise control of the motor speed.

[0053] In this embodiment, the load torque is estimated in real time using an extended Kalman filter model, and combined with feedforward control, the impact of load changes on motor speed can be predicted and compensated more accurately, thereby improving control precision. The combination of feedforward control and PID control enables the system to better cope with external disturbances and load changes, enhancing its robustness and stability. Dynamically adjusting the PWM duty cycle allows the motor to respond quickly to changes in speed commands while maintaining smooth operation, optimizing the system's dynamic performance. Compared to traditional control methods, this approach simplifies the design and implementation of the control strategy and reduces the complexity of the control system by introducing an extended Kalman filter model and feedforward control.

[0054] S103 inputs the PWM duty cycle and the armature current of the micro servo motor to the sliding mode observer to generate the speed observation value of the micro servo motor, and determines whether to generate a braking signal based on the deviation between the speed observation value and the preset target speed.

[0055] In this embodiment, a PWM controller generates a PWM signal to control the micro servo motor, and the duty cycle of the PWM signal is acquired in real time. The duty cycle determines the average value of the motor's input voltage, thus affecting the motor's speed. Simultaneously, a current sensor is used to acquire the armature current of the micro servo motor in real time. The armature current is closely related to the motor's load and speed, and is an important indicator of the motor's operating status. Based on the electrical and mechanical characteristics of the micro servo motor, a state-space model of the motor is established. The model should include state variables such as the motor's armature current and speed, as well as external factors such as input voltage (related to the PWM duty cycle) and load torque. Based on the motor's state-space model, a sliding mode observer's sliding surface is designed. The sliding surface should reflect the error between the motor speed and the observed value, so as to generate a control effect when the observation error is large. The algorithm of the sliding mode observer is implemented, taking the PWM duty cycle and armature current as inputs, and obtaining the observed motor speed value through iterative calculation. The algorithm should include a sliding mode control law to ensure that the observation error approaches zero. The observed speed value output by the sliding mode observer is compared with a preset target speed, and the speed deviation is calculated. The speed deviation reflects the difference between the current motor speed and the target speed. Based on the magnitude and sign of the speed deviation, it is determined whether a braking signal should be generated. For example, when the speed deviation exceeds a certain threshold and is negative (i.e., the motor speed is lower than the target speed), it is considered that the motor needs to decelerate and stop, and a braking signal is generated at this time. The braking signal can be a digital signal used to trigger the braking circuit or change the duty cycle of the PWM signal to achieve motor deceleration and stopping.

[0056] In this embodiment, the motor speed is estimated in real time using a sliding mode observer, and feedback control is performed by combining the PWM duty cycle and armature current. This enables more accurate tracking of the target speed and improves speed control precision. The sliding mode observer is highly robust to changes in motor parameters and external disturbances, and can operate stably under different operating conditions, ensuring the reliability and stability of the system. Based on the deviation between the observed speed and the target speed, a braking signal is generated in a timely manner to achieve rapid braking of the motor.

[0057] S104, when a braking signal is determined to be generated, adjusts the feedback current and PWM duty cycle of the micro servo motor in real time based on the observed speed value.

[0058] In this embodiment, based on the deviation between the previously output speed observation value from the sliding mode observer and the preset target speed, a braking signal is generated when the deviation exceeds a set threshold and is negative. This means that the motor's current speed is lower than the target speed, requiring deceleration and a stop. When the braking signal is triggered, the feedback current adjustment mechanism is immediately activated. Feedback current refers to the current that the motor feeds back to the power supply when converting mechanical energy into electrical energy during braking. By monitoring the motor's armature voltage and speed observation value, an algorithm is used to calculate the optimal feedback current value in real time. This algorithm can consider parameters such as the motor's resistance and inductance, as well as the current load and braking requirements. The motor's drive circuit is adjusted to make the motor work in a generating state. The calculated feedback current value is used as the target value, and the current is controlled in a closed loop through the control circuit to ensure the stability and accuracy of the feedback current. While adjusting the feedback current, the duty cycle of the PWM signal is adjusted in real time according to the speed observation value and the preset braking curve (or braking strategy). The adjustment of the duty cycle aims to control the motor's input voltage, thereby controlling the motor's braking torque and deceleration. By gradually reducing the duty cycle, the motor can be smoothly decelerated and stopped. The duty cycle adjustment should be coordinated with the feedback current adjustment to ensure that the energy conversion efficiency of the motor is maximized during braking, while avoiding overheating or damage to the motor.

[0059] In this embodiment, by monitoring the observed rotational speed in real time and adjusting the feedback current and PWM duty cycle, the braking process of the motor can be precisely controlled, ensuring that the motor stops accurately at the designated position, thus improving machining accuracy and stability. During braking, by controlling the feedback current, a portion of the motor's mechanical energy can be converted into electrical energy and fed back to the power supply, achieving energy recovery and utilization, and improving the system's energy efficiency. Reasonable control of the feedback current and PWM duty cycle can reduce motor losses and heat generation during braking, extending the motor's lifespan and reducing maintenance costs. Real-time adjustment of the feedback current and PWM duty cycle allows the motor to respond quickly to braking commands when needed, improving the system's response speed and flexibility.

[0060] S105 sets a three-dimensional fault judgment space including temperature, current and voltage. The micro servo motor is fault detected according to the three-dimensional fault judgment space. If a fault is determined, the miniaturization protection mechanism is triggered, and the protection parameter threshold of the micro servo motor is readjusted by the moment of inertia and the maximum allowable acceleration.

[0061] In this embodiment, temperature, current, and voltage are selected as monitoring parameters, as these three parameters can comprehensively reflect the operating status of the micro servo motor. Temperature reflects the motor's thermal load, current reflects the motor's load size and efficiency, and voltage is related to the motor's input power and stability. Based on a large amount of experimental data and historical operating records, a three-dimensional fault determination space including temperature, current, and voltage is established. This space is a three-dimensional coordinate system, where temperature, current, and voltage correspond to the three coordinate axes, respectively. Different fault type determination thresholds are set in the three-dimensional fault determination space. These thresholds are determined based on the motor's design parameters, operating characteristics, and safety requirements. When the motor's temperature, current, and voltage values ​​simultaneously exceed a certain threshold, a fault is determined.

[0062] Sensors are used to monitor the temperature, current, and voltage values ​​of a miniature servo motor in real time. The sensors should possess high accuracy and reliability to ensure the accuracy of the collected data. The collected temperature, current, and voltage values ​​are mapped onto a three-dimensional fault detection space to determine their location. The location of the mapped value in the three-dimensional fault detection space is compared with a set threshold. If the location exceeds the threshold range, a fault is identified. Once a fault is identified, a miniaturized protection mechanism is immediately triggered. This mechanism includes cutting off the motor's power supply and stopping its operation to prevent further escalation of the fault and protect the motor and related equipment. Simultaneously, an alarm device is triggered to send a fault alarm signal to the operator and record fault information for subsequent analysis.

[0063] Based on parameters such as the moment of inertia and maximum permissible acceleration of the micro servo motor, the protection parameter thresholds for the micro servo motor are recalculated and adjusted. The new thresholds should better reflect the actual operating conditions and safety requirements of the motor. The adjusted protection parameter thresholds are then updated in the three-dimensional fault determination space and protection mechanism for use in subsequent fault detection.

[0064] In this embodiment, by establishing a three-dimensional fault judgment space and comprehensively considering multiple parameters such as temperature, current, and voltage, the accuracy and timeliness of fault detection are improved. This allows for timely detection and handling of faults in their early stages, preventing further escalation. Triggering the miniaturized protection mechanism quickly cuts off the power supply and stops the motor when a fault occurs, effectively protecting the motor and related equipment from damage. Simultaneously, recording fault information provides a basis for subsequent fault analysis and processing. The protection parameter thresholds are readjusted based on parameters such as the moment of inertia and maximum permissible acceleration of the miniature servo motor, making the protection mechanism more consistent with the actual operating conditions and safety requirements of the motor. This helps improve the targeting and effectiveness of the protection mechanism, reducing false alarms and missed alarms. Timely fault detection and handling prevent motor damage due to prolonged overload or overheating. Furthermore, optimizing the protection parameter settings helps improve motor operating efficiency and reduce energy consumption and maintenance costs.

[0065] In some embodiments, step S101 above, which involves generating a continuous acceleration curve based on the moment of inertia and maximum allowable acceleration of the micro servo motor, and dynamically adjusting the inflection point time by real-time detection of the load current of the micro motor, specifically includes:

[0066] A third-order S-shaped acceleration curve is constructed based on the moment of inertia and maximum allowable acceleration of the micro servo motor. The third-order S-shaped acceleration curve includes an acceleration rising phase, a constant velocity phase, and an acceleration falling phase.

[0067] The load current of the micro motor and the angle difference between the actual position and the target position of the micro servo motor are detected in real time. The inflection point between each stage of the third-order S-curve acceleration curve is dynamically adjusted according to the load current and the angle difference.

[0068] In this embodiment, the third-order S-shaped acceleration curve achieves smooth acceleration changes, effectively avoiding mechanical shocks and vibrations caused by sudden acceleration changes, and extending the service life of the micro servo motor. By monitoring the load current and position error in real time and dynamically adjusting the inflection point of the acceleration curve, the motor can flexibly adjust its motion state according to load changes and target position requirements under different operating conditions, improving the accuracy and stability of control.

[0069] Furthermore, the third-order S-curve acceleration curve satisfies

[0070]

[0071] in, This represents a third-order S-shaped acceleration curve, where t represents time. Indicates the maximum permissible acceleration. Indicates the time of the acceleration rise phase. This represents the time of the uniform velocity phase. Indicates the phase of acceleration decrease;

[0072]

[0073] in, Represents the moment of inertia. This indicates the rated torque of the micro servo motor. This represents the angular difference between the actual position and the target position of the micro servo motor. This indicates the maximum speed of the micro servo motor. and This represents the shape factor.

[0074] In this embodiment, the formula for dynamically adjusting the inflection points between each stage of the third-order S-curve acceleration curve based on the load current and angle difference is as follows:

[0075]

[0076] Indicates the load current. Indicates the rated current. and This represents the current feedback adjustment coefficient.

[0077] The third-order S-curve acceleration curve is a mathematical function that describes the change of acceleration of a micro servo motor over time. It ensures a smooth transition of acceleration and reduces mechanical shock and vibration.

[0078] The maximum permissible acceleration is the maximum acceleration value that a micro servo motor is allowed to achieve in its design. It limits the motor's acceleration capability to prevent overload and damage.

[0079] The duration of the acceleration rise phase, the duration of the constant velocity phase, and the duration of the acceleration fall phase define the three stages of the acceleration curve: rise, constant velocity, and fall. These stages determine the rate of acceleration and deceleration of the motor, as well as the duration of constant velocity motion, thus affecting the smoothness and efficiency of the motor's motion.

[0080] Moment of inertia is a physical quantity that describes the magnitude of an object's inertia during rotational motion. In motor control, moment of inertia affects the motor's acceleration and deceleration performance; a larger moment of inertia requires a longer acceleration and deceleration time.

[0081] Rated torque is the maximum torque that a motor can continuously output under rated conditions. It limits the motor's load capacity and affects the setting of the acceleration curve.

[0082] The angular difference between the actual position and the target position of the micro servo motor is an error that the control system needs to eliminate. It affects the adjustment of the acceleration curve to reach the target position faster or slower.

[0083] Maximum speed is the highest speed that can be achieved in the design of a motor. It limits the speed range of the motor and affects the constant speed phase of the acceleration curve.

[0084] Shape coefficients are used to adjust the shape of the acceleration curve, such as the rate of acceleration rise and fall, and the symmetry of the curve. They provide flexibility to adapt to different motion requirements.

[0085] Load current is the current that a motor experiences during actual operation, reflecting the motor's load condition. A larger load current may indicate that the motor is under a large load or is in an overload state.

[0086] Rated current is the maximum current that a motor is allowed to continuously carry under rated conditions. It is an important parameter to consider when designing a motor to ensure its safe operation.

[0087] The current feedback adjustment coefficient is used to adjust the inflection point of the acceleration curve according to changes in load current. When the load current increases, adjusting these coefficients can reduce the rate of acceleration rise and fall, thereby reducing the load on the motor and preventing overload.

[0088] In some embodiments, step S102 above, which involves estimating the load torque of the micro servo motor in real time using an extended Kalman filter model, inputting the estimated load torque into a feedforward controller to generate a compensation voltage, and superimposing it with the voltage control parameters output by the PID controller to dynamically adjust the PWM duty cycle, specifically includes:

[0089] Set the state variables of the extended Kalman filter model, which include the armature current, speed and load torque of the micro servo motor;

[0090] Set up state equations and observation equations, substitute the state variables into the state equations and observation equations for recursive updates, and output the estimated speed and estimated load torque.

[0091] The estimated load torque is input to the feedforward controller, and a compensation voltage is generated by the preset compensation formula in the feedforward controller.

[0092] A PID control quantity is generated based on the deviation between the speed setpoint in the PID controller and the speed estimate. The PID control quantity and the compensation voltage are superimposed to generate a total voltage control quantity. The PWM duty cycle is dynamically adjusted through the total voltage control quantity.

[0093] In this embodiment, the extended Kalman filter algorithm enables real-time and accurate estimation of the speed and load torque of the micro servo motor, improving the precision and stability of speed control. The feedforward controller generates a compensation voltage based on the estimated load torque, effectively compensating for the impact of load disturbances on motor speed and enhancing the system's resistance to load disturbances. The combination of the PID controller and the feedforward controller allows the system to respond quickly to changes in the speed setpoint while maintaining good steady-state performance, optimizing dynamic response performance. By adjusting the PWM duty cycle in real time, the input voltage of the motor is precisely controlled, improving energy utilization efficiency and reducing energy waste. The entire control system considers factors such as the motor's dynamic characteristics and load disturbances. The combination of the extended Kalman filter algorithm, feedforward control algorithm, and PID control algorithm enhances the system's robustness, enabling stable operation under different working conditions.

[0094] Furthermore, the state equation satisfies

[0095]

[0096] in, Indicates armature current, Indicates rotational speed. Indicates the load torque. Indicates the input voltage. Indicates armature inductance. Indicates armature resistance. Represents the back electromotive force coefficient. Represents the moment of inertia. Indicates the torque coefficient. Indicates the damping coefficient;

[0097] The observation equation satisfies ,in, Represents the observation vector. Indicates the clicked location;

[0098] The compensation formula satisfies ,in, Indicates the compensation voltage. This represents the estimated load torque value;

[0099] The PID control quantity is: , This represents the PID proportional coefficient. Represents the integral coefficient of the PID controller. Represents the PID differential coefficients. The deviation between the speed setpoint and the estimated speed in the PID controller is represented by t, where t represents time.

[0100] In this embodiment, the state equation describes the dynamic behavior of the micro servo motor system. Here, armature current is the current flowing through the motor armature and is a key variable controlling the motor's torque and speed; speed is the motor's rotational speed and is one of the control targets; load torque is the external torque applied to the motor shaft, affecting the motor's speed and current; input voltage is the voltage applied to the motor armature and is the control input; armature inductance is the inductance of the motor armature windings, affecting the rate of change of current; armature resistance is the resistance of the motor armature windings, affecting the magnitude of current and losses; back electromotive force coefficient is the proportionality coefficient between the motor speed and the back electromotive force, reflecting the motor's electromagnetic characteristics; moment of inertia is the inertia of the motor rotor and its load, affecting the rate of change of speed; torque coefficient is the proportionality coefficient between the motor armature current and the generated torque, reflecting the motor's torque output capability; and damping coefficient is the mechanical damping of the motor system, including friction and wind resistance, affecting the change of speed.

[0101] The observation equations describe the relationship between state variables and measurable quantities. The observation vector contains the measurable state variables; the motor position is the angular position of the motor rotor. Using the observation equations, state variables that cannot be directly measured, such as load torque, can be estimated using the measurable quantities.

[0102] The compensation formula describes how the feedforward controller generates a compensation voltage based on the estimated load torque. This compensation voltage can compensate for changes in load torque in real time, reducing the impact of load disturbances on motor speed. By rapidly compensating for changes in load torque, the system's dynamic response speed and stability are improved.

[0103] The PID control input describes how a PID controller generates a control voltage based on the speed deviation. The PID proportional coefficient adjusts the proportional relationship between the control voltage and the speed deviation, affecting the system's response speed and overshoot. The PID integral coefficient integrates the speed deviation, eliminating static errors and improving the system's steady-state accuracy. The PID derivative coefficient differentiates the rate of change of the speed deviation, predicting the system's future behavior and improving its dynamic performance. By adjusting the parameters of the PID controller, the motor speed can be precisely controlled to achieve the set control objective.

[0104] In some embodiments, step S103 above, which involves inputting the PWM duty cycle and the armature current of the micro servo motor into a sliding mode observer to generate a speed observation value for the micro servo motor, and determining whether to generate a braking signal based on the deviation between the speed observation value and a preset target speed, specifically includes:

[0105] Construct the dynamic equations of the sliding mode observer, the dynamic equations satisfying

[0106]

[0107]

[0108] in, This represents the estimated armature current. Indicates the PWM duty cycle. Indicates bus voltage. This represents the observed rotational speed. Indicates sliding mode gain. This indicates the armature current estimation error. This represents the feedback term used to force the armature current estimation error s to approach zero;

[0109] The PWM duty cycle and the armature current of the micro servo motor are input into the dynamic equation to generate speed observations;

[0110] If the deviation between the observed speed and the preset target speed is greater than the preset speed deviation threshold, and the rate of change of the observed speed is less than the negative value of the deceleration rate threshold, then a braking signal is generated.

[0111] In this embodiment, the armature current estimate is an estimate of the actual armature current by a sliding mode observer. The observer continuously adjusts this estimate using dynamic equations to make it as close as possible to the true value.

[0112] The PWM (Pulse Width Modulation) duty cycle determines the average voltage applied to the motor armature. It is a key input for controlling motor speed and current. By adjusting the PWM duty cycle, the motor's input voltage can be precisely controlled, thereby achieving speed and current regulation.

[0113] Bus voltage is the supply voltage of a motor system, which affects the motor's current and speed. Considering bus voltage in the dynamic equations can improve the accuracy and robustness of the observer.

[0114] The observed rotational speed is an estimate of the actual rotational speed from the sliding mode observer. The observer continuously adjusts this estimate using the dynamic equations and the sliding mode control law. This provides a real-time estimate of the rotational speed, offering feedback information to the control algorithm.

[0115] The sliding mode gain determines the observer's sensitivity to estimation errors and its adjustment speed. A larger gain can speed up convergence but may cause system chattering. By appropriately selecting the sliding mode gain, a balance can be struck between convergence speed and system stability.

[0116] Armature current estimation error represents the difference between the actual armature current and the estimated value. It serves as feedback to adjust the estimated armature current to approximate the true value.

[0117] The feedback term used to force the armature current estimation error s to approach zero is part of the sliding mode control law. It is used to ensure that the estimation error s (which may be the current error or some transformation thereof) approaches zero, thereby improving the accuracy and robustness of the observer and making the system more resistant to disturbances and uncertainties.

[0118] The observed rotational speed is compared with the target rotational speed, and the deviation is calculated. This provides feedback information to the control algorithm, which adjusts the PWM duty cycle to control the motor speed.

[0119] When the deviation between the observed motor speed and the target motor speed exceeds a preset threshold, it indicates that the motor speed has not reached the desired value. The trigger control algorithm then takes corresponding measures, such as adjusting the PWM duty cycle, to reduce the deviation.

[0120] When the rate of change of the observed rotational speed is less than a certain negative value, it indicates that the motor is decelerating at an excessively rapid rate. A braking signal may be necessary to prevent the motor from stopping or reversing too quickly, thus protecting the motor and the system.

[0121] When the above conditions are met, the control algorithm generates a braking signal to control the motor's braking behavior. This ensures that the motor can safely and effectively decelerate or stop when needed, improving the system's reliability and safety.

[0122] In some embodiments, step S104 above, specifically adjusting the feedback current and PWM duty cycle of the micro servo motor in real time using observed rotational speed values, includes:

[0123] Using the observed rotational speed as input, the feedback current of the micro servo motor is adjusted in real time according to the energy feedback formula, which satisfies...

[0124]

[0125] in, Indicates feedback current. Indicates the torque coefficient. Indicates capacitor voltage. This represents the equivalent series resistance of the capacitor;

[0126] Using the observed rotational speed as input, the PWM duty cycle is adjusted in real time according to the PWM chopper braking formula, which satisfies...

[0127]

[0128] in, This indicates the adjusted PWM duty cycle. Indicates the initial duty cycle. Indicates the attenuation coefficient. t represents the target rotational speed, and t represents time.

[0129] In this embodiment, the energy feedback formula is used to adjust the feedback current of the micro servo motor in real time. The feedback current is the current that the motor feeds back into the capacitor or power source when it converts mechanical energy into electrical energy during braking or deceleration. By controlling the feedback current, energy can be effectively recovered, improving the system's energy efficiency and reducing heat generation during braking.

[0130] The torque coefficient determines the ratio between motor current and generated torque. In energy feedback processes, it affects the magnitude of the feedback current. By considering the torque coefficient, the feedback current can be calculated more accurately, ensuring the efficiency and stability of energy feedback.

[0131] The capacitor voltage is the voltage at the receiving end of the energy feedback system. It determines the storage and reuse of the fed-in energy. By monitoring and adjusting the capacitor voltage, the energy feedback process can be optimized, preventing damage to the system from excessively high or low voltage.

[0132] The equivalent series resistance (ESR) of a capacitor is the internal resistance generated during the charging and discharging process. It affects the efficiency and speed of energy feedback. Considering the ESR allows for more accurate calculation of the feedback current and losses during energy feedback, thereby optimizing the control strategy.

[0133] The PWM (Pulse Width Modulation) braking formula is used to adjust the PWM duty cycle in real time to control the motor's braking process. The adjusted PWM duty cycle determines the average voltage applied to the motor armature, thus affecting the motor's braking speed and force. By adjusting the PWM duty cycle in real time, the motor's braking process can be precisely controlled, ensuring that the motor can stop quickly and smoothly when needed.

[0134] The initial duty cycle is the PWM duty cycle at the start of the braking process. It determines the starting conditions of the braking process. By setting a reasonable initial duty cycle, the smooth progress of the braking process can be ensured, and excessive shocks or oscillations during the braking process can be avoided.

[0135] The attenuation coefficient determines the rate of change of the PWM duty cycle with respect to the deviation between the observed and target speeds. A larger attenuation coefficient results in faster braking speeds. By adjusting the attenuation coefficient, precise control of the motor's braking speed can be achieved to meet the needs of different application scenarios.

[0136] The target speed is the speed value intended for use during braking. When the motor speed reaches or approaches the target speed, the braking process should gradually decrease or stop. By setting a reasonable target speed, it can be ensured that the motor can stop accurately and stably at a specified position or speed during braking.

[0137] In some embodiments, in step S105 above, the step of performing fault detection on the micro servo motor based on the three-dimensional fault determination space, and triggering a miniaturization protection mechanism if a fault is determined, specifically includes:

[0138] The temperature, current, and voltage of the micro servo motor are acquired, and the temperature, current, and voltage are normalized.

[0139] The normalized temperature, current and voltage are input into the three-dimensional fault judgment space, and the fault detection value is obtained by weighted Euclidean distance calculation.

[0140] If the fault monitoring value is greater than or equal to the fault determination threshold, the micro servo motor is determined to be in a fault state, and the PWM duty cycle is reduced, the upper bridge MOSFET is cut off, and the power is completely cut off and the dynamic discharge circuit is started.

[0141] In this embodiment, normalization processing converts temperature, current, and voltage data to a unified range, eliminating the influence of different units on data comparison and improving the accuracy of fault detection. Weighted Euclidean distance calculation comprehensively considers changes in temperature, current, and voltage, enabling timely detection of abnormal conditions during motor operation and achieving early fault warning. Once a fault condition is determined, immediate measures such as reducing the PWM duty cycle, disconnecting the upper bridge MOSFET, and complete power-off are taken to effectively prevent further fault escalation and protect the safety of the motor and system.

[0142] In some embodiments, step S105 above, specifically the readjustment of the protection parameter thresholds of the micro servo motor by adjusting the moment of inertia and maximum permissible acceleration, includes:

[0143] The moment of inertia and maximum allowable acceleration are input into the protection parameter threshold adjustment formula to update the current protection threshold and temperature protection threshold in real time.

[0144] The protection parameter threshold adjustment formula satisfies

[0145]

[0146] in, Indicates the current protection threshold. This indicates the updated current protection threshold. Indicates the temperature protection threshold. This indicates the updated temperature protection threshold. Represents the moment of inertia. Indicates the maximum permissible acceleration. Indicates the nominal moment of inertia. Indicates the nominal maximum permissible acceleration. This represents the temperature-inertia coupling coefficient.

[0147] In this embodiment, the nominal moment of inertia and nominal maximum permissible acceleration represent the parameters of the motor under design or rated conditions. They are used as reference points to calculate the protection threshold adjustment under actual conditions. By comparing the actual values ​​with the nominal values, the formula can calculate the protection threshold adjustment caused by changes in moment of inertia and maximum permissible acceleration, thereby achieving dynamic protection.

[0148] The temperature-inertia coupling coefficient reflects the degree to which changes in rotational inertia affect temperature. A larger moment of inertia may cause the motor to generate more heat during acceleration or deceleration, thus requiring adjustment of the temperature protection threshold to compensate for this effect. By introducing the temperature-inertia coupling coefficient, the protection parameter threshold adjustment formula can more accurately reflect the impact of changes in rotational inertia on temperature, thereby improving the accuracy and reliability of temperature protection.

[0149] In this embodiment, the protection threshold is dynamically adjusted based on the actual load and acceleration performance of the motor to avoid over-protection or under-protection, enabling the motor system to adapt to different load conditions and operating environments, thus improving the system's flexibility and reliability. By accurately controlling current and temperature, the risk of motor overheating and overload is reduced, thereby extending the motor's service life and ensuring that the motor does not exceed its physical limits during acceleration and deceleration, preventing safety accidents such as mechanical damage or control instability.

[0150] Reference Figure 2 An embodiment of the present invention provides a micro servo motor control system 2, the system 2 specifically comprising:

[0151] The first control module 201 is used to generate a continuous acceleration curve based on the moment of inertia and maximum allowable acceleration of the micro servo motor, and dynamically adjust the inflection point time by real-time detection of the load current and position deviation of the micro motor, so as to provide an initial stable state for the extended Kalman filter model.

[0152] The second control module 202 is used to estimate the load torque of the micro servo motor in real time through the extended Kalman filter model, input the estimated load torque into the feedforward controller to generate a compensation voltage, and superimpose it with the voltage control parameters output by the PID controller to dynamically adjust the PWM duty cycle.

[0153] The third control module 203 is used to input the PWM duty cycle and the armature current of the micro servo motor into the sliding mode observer to generate the speed observation value of the micro servo motor, and determine whether to generate a braking signal based on the deviation between the speed observation value and the preset target speed.

[0154] The fourth control module 204 is used to adjust the feedback current and PWM duty cycle of the micro servo motor in real time based on the observed speed value when a braking signal is determined to be generated.

[0155] The fifth control module 205 is used to set a three-dimensional fault judgment space including temperature, current and voltage. Based on the three-dimensional fault judgment space, the micro servo motor is fault detected. If a fault is determined, the miniaturization protection mechanism is triggered, and the protection parameter threshold of the micro servo motor is readjusted by the moment of inertia and the maximum allowable acceleration.

[0156] It is understandable that, such as Figure 1 The content of the micro servo motor control method embodiments shown is applicable to the micro servo motor control system embodiments. The specific functions implemented by the micro servo motor control system embodiments are the same as those shown in the examples. Figure 1 The micro servo motor control method shown in the embodiment is the same, and the beneficial effects achieved are the same as those described above. Figure 1 The beneficial effects achieved by the illustrated embodiment of the micro servo motor control method are also the same.

[0157] It should be noted that the information interaction and execution process between the above systems are based on the same concept as the method embodiments of the present invention. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0158] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments 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. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0159] Reference Figure 3 The present invention also provides a computer device 3, including: a memory 302 and a processor 301, and a computer program 303 stored in the memory 302. When the computer program 303 is executed on the processor 301, it implements the micro servo motor control method as described in any of the above methods.

[0160] The computer device 3 may be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device 3 may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art will understand that... Figure 3 The computer device 3 is merely an example and does not constitute a limitation on the computer device 3. It may include more or fewer components than shown in the figure, or combine certain components, or different components, such as input / output devices, network access devices, etc.

[0161] The processor 301 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0162] In some embodiments, the memory 302 may be an internal storage unit of the computer device 3, such as a hard disk or memory of the computer device 3. In other embodiments, the memory 302 may be an external storage device of the computer device 3, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 3. Furthermore, the memory 302 may include both internal and external storage units of the computer device 3. The memory 302 is used to store the operating system, applications, boot loader, data, and other programs, such as the program code of the computer program. The memory 302 can also be used to temporarily store data that has been output or will be output.

[0163] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the micro servo motor control method as described in any of the above methods.

[0164] In this embodiment, if the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0165] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0166] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0167] In the embodiments disclosed in this application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling or direct coupling or communication connection may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0168] The units described as separate components may or may not be physically separate. The components shown as units 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.

Claims

1. A method of controlling a micro-servo motor, characterized by, The method specifically comprises: According to the moment of inertia and the maximum allowable acceleration of the micro servo motor, an acceleration continuous curve is generated, and the inflection point time is dynamically adjusted by real-time detection of the load current and the position deviation of the micro motor to provide an initial stable state for an extended Kalman filter model; The load torque of the micro servo motor is estimated in real time through the extended Kalman filter model, the estimated load torque is input into a feedforward controller to generate a compensation voltage, and the compensation voltage is superimposed with a voltage control parameter output by a PID controller to dynamically adjust the PWM duty cycle; The PWM duty cycle and the armature current of the micro servo motor are input into a sliding mode observer to generate a speed observation value of the micro servo motor, and whether a braking signal is generated is determined according to the deviation between the speed observation value and a preset target speed; When it is determined that the braking signal is generated, the feedback current and the PWM duty cycle of the micro servo motor are adjusted in real time through the speed observation value; A three-dimensional fault judgment space containing temperature, current and voltage is set, the micro servo motor is detected according to the three-dimensional fault judgment space, if it is judged that a fault condition exists, a miniaturized protection mechanism is triggered, and the protection parameter threshold of the micro servo motor is re-adjusted through the moment of inertia and the maximum allowable acceleration.

2. The method of claim 1, wherein, The method specifically comprises: According to the moment of inertia and the maximum allowable acceleration of the micro servo motor, an acceleration continuous curve is generated, and the inflection point time is dynamically adjusted by real-time detection of the load current and the position deviation of the micro motor to provide an initial stable state for an extended Kalman filter model; According to the moment of inertia and the maximum allowable acceleration of the micro servo motor, a three-order S-shaped acceleration curve is constructed, and the three-order S-shaped acceleration curve comprises an acceleration rising stage, a constant speed stage and an acceleration falling stage; 3. The method of claim 2, wherein, The load current of the micro motor and the angle difference between the actual position and the target position of the micro servo motor are detected in real time, and the inflection points between each stage of the three-order S-shaped acceleration curve are dynamically adjusted according to the load current and the angle difference. wherein, represents a third order S-shaped acceleration profile, t represents time, represents the maximum allowed acceleration, represents the time of the acceleration rise phase, represents the time of the constant speed phase, represents the acceleration fall phase; wherein, denotes the moment of inertia, denotes the rated torque of the micro-servo motor, denotes the angular difference between the actual position and the target position of the micro-servo motor, denotes the maximum rotational speed of the micro-servo motor, and denotes the shape factor.

4. The method of claim 1, wherein, The three-order S-shaped acceleration curve satisfies The method specifically comprises: The state variables of the extended Kalman filter model are set, and the state variables comprise the armature current, the speed and the load torque of the micro servo motor; The state equation and the observation equation are set, the state variables are substituted into the state equation and the observation equation for recursive updating, and the speed estimation value and the load torque estimation value are output; The load torque estimation value is input into the feedforward controller, and a compensation voltage is generated through a preset compensation formula in the feedforward controller; 5. The method of claim 4, wherein, According to the deviation between the speed set value in the PID controller and the speed estimation value, a PID control amount is generated, the PID control amount and the compensation voltage are superimposed to generate a total voltage control amount, and the PWM duty cycle is dynamically adjusted through the total voltage control amount. The state equation satisfies wherein, represents the armature current, represents the rotational speed, represents the load torque, represents the input voltage, represents the armature inductance, represents the armature resistance, represents the back EMF coefficient, represents the moment of inertia, represents the torque coefficient, represents the damping coefficient; The observation equation satisfies wherein, represents an observation vector, represents a click position; The compensation formula satisfies wherein, represents a compensation voltage, represents a load torque estimation value; The PID control amount is , denotes a PID proportionality coefficient, denotes a PID integral coefficient, denotes a PID differential coefficient, denotes a deviation between a rotational speed set value within a PID controller and the rotational speed estimated value, and t denotes time.

6. The method of claim 5, wherein, The PWM duty ratio and the armature current of the micro servo motor are input into the sliding mode observer to generate a speed observation value of the micro servo motor, and whether to generate a braking signal is determined according to a deviation between the speed observation value and a preset target speed, and specifically includes the following steps. A dynamic equation of the sliding mode observer is constructed, and the dynamic equation satisfies wherein represents an armature current estimation value, represents a PWM duty ratio, represents a bus voltage, represents a rotational speed observation value, represents a sliding mode gain, represents an armature current estimation error, represents a feedback term for forcing the armature current estimation error s to approach zero; The PWM duty ratio and the armature current of the micro servo motor are input into the dynamic equation to generate the speed observation value; If the deviation between the speed observation value and the preset target speed is greater than a preset speed deviation threshold value, and the change rate of the speed observation value is less than a negative value of a deceleration rate threshold value, it is determined that the braking signal is generated.

7. The method of claim 6, wherein, The feedback current of the micro servo motor and the PWM duty ratio are adjusted in real time according to the speed observation value, and specifically includes the following steps. The speed observation value is taken as an input, and the feedback current of the micro servo motor is adjusted in real time according to an energy feedback formula, and the energy feedback formula satisfies wherein, represents the feedback current, represents the torque coefficient, represents the capacitor voltage, represents the capacitor equivalent series resistance; The speed observation value is taken as an input, and the PWM duty ratio is adjusted in real time according to a PWM chopping brake formula, and the PWM chopping brake formula satisfies wherein, denotes the adjusted PWM duty cycle, denotes the initial duty cycle, denotes the decay coefficient, denotes the target rotational speed, t denotes time.

8. The method of claim 1, wherein, The micro servo motor is detected for a fault according to a three-dimensional fault judgment space, and if it is determined that a fault condition exists, a miniaturized protection mechanism is triggered, and specifically includes the following steps. The temperature, current and voltage of the micro servo motor are obtained, and the temperature, current and voltage are normalized; The normalized temperature, current and voltage are input into the three-dimensional fault judgment space, and a fault detection value is obtained through weighted Euclidean distance calculation; If the fault detection value is greater than or equal to a fault judgment threshold value, it is determined that the micro servo motor is in a fault state, the PWM duty ratio is reduced, the upper bridge MOSFET is cut off, and the dynamic bleeder circuit is completely powered off and started.

9. The method of claim 1, wherein, The protection parameter threshold values of the micro servo motor are adjusted again according to the moment of inertia and the maximum allowable acceleration, and specifically includes the following steps. The moment of inertia and the maximum allowable acceleration are input into a protection parameter threshold value adjustment formula to update the current protection threshold value and the temperature protection threshold value in real time; The protection parameter threshold value adjustment formula satisfies wherein represents a current protection threshold, represents an updated current protection threshold, represents a temperature protection threshold, represents an updated temperature protection threshold, represents a moment of inertia, represents a maximum allowed acceleration, represents a nominal moment of inertia, represents a nominal maximum allowed acceleration, represents a temperature-inertia coupling coefficient.

10. A micro-servo motor control system, characterized by, The system specifically includes: A first control module is configured to generate an acceleration continuous curve according to the moment of inertia and the maximum allowable acceleration of the micro servo motor, dynamically adjust a turning point time by detecting the load current and the position deviation of the micro motor in real time, and provide an initial stable state for an extended Kalman filter model; A second control module is configured to estimate the load torque of the micro servo motor in real time through the extended Kalman filter model, input the estimated load torque into a feedforward controller to generate a compensation voltage, superimpose the compensation voltage on a voltage control parameter output by a PID controller, and dynamically adjust the PWM duty ratio; A third control module is configured to input the PWM duty ratio and the armature current of the micro servo motor into the sliding mode observer to generate a speed observation value of the micro servo motor, and determine whether to generate a braking signal according to a deviation between the speed observation value and a preset target speed; A fourth control module is configured to adjust the feedback current of the micro servo motor and the PWM duty ratio in real time according to the speed observation value when it is determined that the braking signal is generated. The fifth control module is used for setting a three-dimensional fault judgment space containing temperature, current and voltage, and performing fault detection on the micro servo motor according to the three-dimensional fault judgment space, and if the fault condition is judged, the micro protection mechanism is triggered, and the protection parameter threshold of the micro servo motor is re-adjusted through the moment of inertia and the maximum allowable acceleration.

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