A robot joint module current closed-loop control method, system and storage medium

Abstract

The application relates to a robot joint module current closed-loop control method and system and a storage medium, and relates to the technical field of computers.The application comprises the following steps: collecting feedback current of a permanent magnet synchronous motor; generating an initial voltage control amount based on the feedback current and a preset instruction current; generating back electromotive force feedforward compensation voltage by using a preset sliding mode algorithm based on current observation error; performing real-time estimation processing on inverter dead zone voltage distortion to generate dead zone compensation voltage; performing voltage superposition processing on the initial voltage control amount, the back electromotive force feedforward compensation voltage and the dead zone compensation voltage to generate a voltage instruction; and generating a driving signal based on the voltage instruction to drive the permanent magnet synchronous motor to control the robot joint. The application has the effects of improving the control accuracy and response speed of the current loop under complex disturbances, resisting torque fluctuation caused by sudden change of back electromotive force, eliminating low-speed vibration caused by the dead zone effect, and enhancing stability under variable load conditions.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a method, system and storage medium for closed-loop current control of a robot joint module. Background Technology

[0002] In related technologies, the current closed-loop control of robot joint modules typically uses a proportional-integral (PI) controller as the core regulator. Specifically, the three-phase current of a permanent magnet synchronous motor is collected by a current sensor, and the feedback current in the rotating coordinate system is obtained through coordinate transformation. The error between the feedback current and the command current is input to the PI controller, which outputs a voltage control quantity, which is then pulse-width modulated to generate a drive signal to control the motor operation.

[0003] Regarding the aforementioned technologies, the proportional-integral (PI) controller is essentially an error-based linear regulator, and its control performance depends on a mathematical model. However, robot joint modules experience disturbances during actual operation: First, the back electromotive force generated by the permanent magnet synchronous motor changes drastically under high-speed or variable acceleration conditions, causing the integral action of the PI controller to lag and fail to offset the voltage disturbances caused by the sudden change in back electromotive force, resulting in current waveform distortion and torque fluctuations. Second, the dead time set by the inverter to prevent shoot-through between the upper and lower bridge arms generates a voltage clamping effect near the current zero-crossing point, introducing periodic low-frequency harmonic disturbances. However, the PI controller cannot effectively suppress nonlinear distortion, leading to vibration and noise in the joint module during low-speed crawling. Third, the equivalent moment of inertia and friction coefficient of the robot joints change in real time with the posture, while the parameters of the PI controller remain constant. Under variable load conditions, overshoot and oscillation phenomena will occur, indicating room for improvement. Summary of the Invention

[0004] To overcome the shortcomings of existing current closed-loop control methods, such as low current control accuracy, large torque ripple, and slow dynamic response, which reduce the precision operation performance of robot joint modules, this application provides a current closed-loop control method for robot joint modules.

[0005] In a first aspect, this application provides a closed-loop control method for the current of a robot joint module, which adopts the following technical solution: The system collects the feedback current of the permanent magnet synchronous motor; based on the feedback current and a preset command current, it generates an initial voltage control quantity; based on the current observation error, it generates a back EMF feedforward compensation voltage using a preset sliding mode algorithm; it performs real-time estimation processing on the inverter dead-zone voltage distortion to generate a dead-zone compensation voltage; it performs voltage superposition processing on the initial voltage control quantity, the back EMF feedforward compensation voltage, and the dead-zone compensation voltage to generate a voltage command; based on the voltage command, it generates a drive signal to drive the permanent magnet synchronous motor to control the robot joints.

[0006] Secondly, this application provides a closed-loop control system for the current of a robot joint module, which adopts the following technical solution: The acquisition module is used to acquire the feedback current of the permanent magnet synchronous motor; the memory is used to store the program of the above-mentioned robot joint module current closed-loop control method; the processor can load and execute the program in the memory to implement the above-mentioned robot joint module current closed-loop control method.

[0007] Thirdly, this application provides a computer storage medium capable of storing corresponding programs, which facilitates the implementation of a closed-loop current control method for a robot joint module, and adopts the following technical solution: A computer-readable storage medium storing a computer program that can be loaded by a processor and executed by any of the above-described robot joint module current closed-loop control methods.

[0008] The above-described embodiments of this disclosure have the following beneficial effects: The robot joint module current closed-loop control method of some embodiments of this disclosure improves the control accuracy and response speed of the current loop under complex disturbances, effectively suppresses torque fluctuations caused by sudden changes in back EMF, eliminates low-speed vibrations caused by dead-zone effects, and enhances the stability of robot joint motion under variable load conditions. Specifically, the reasons for low current control accuracy, large torque pulsation, and slow response speed are: the proportional-integral controller relies on linear error feedback and cannot offset voltage disturbances caused by sudden changes in back EMF; it cannot suppress the nonlinear distortion introduced by the inverter dead time; and the fixed parameters of the proportional-integral controller cannot adapt to changes in the rotational inertia and friction coefficient of the joint module during actual motion. Based on this, the robot joint module current closed-loop control method of some embodiments of this disclosure first collects the feedback current of the permanent magnet synchronous motor. This provides real-time physical quantity input for subsequent current closed-loop control, enabling the control system to accurately obtain the current state of the motor, avoiding current estimation errors caused by model mismatch in open-loop control, and providing a data basis for current regulation. Secondly, based on the aforementioned feedback current and the preset command current, an initial voltage control quantity is generated. This ensures the system's tracking capability under steady-state conditions and provides a stable reference control quantity for subsequent compensation stages. Next, based on the current observation error, a preset sliding mode algorithm is used to generate a back EMF feedforward compensation voltage. This allows for real-time estimation of lumped disturbances such as back EMF within a finite time, and the abrupt impact of physical back EMF is offset by voltage feedforward. This effectively avoids the torque fluctuations and response lag problems caused by back EMF disturbances in traditional methods. Furthermore, the inverter dead-zone voltage distortion is estimated in real-time to generate a dead-zone compensation voltage. Thus, by using a dynamic extended state observer to expand the voltage distortion caused by the dead zone into the system state and track it in real-time, the voltage clamping effect near the current zero-crossing point can be accurately estimated, and a reverse compensation voltage can be generated to offset it. This effectively eliminates current distortion and torque pulsation near the zero-crossing point and reduces the speed fluctuation rate of the joint modules. Finally, the aforementioned initial voltage control quantity, the aforementioned back EMF feedforward compensation voltage, and the aforementioned dead-zone compensation voltage are superimposed to generate a voltage command. This achieves the parallel integration of multiple disturbance suppression methods, ensuring that back EMF abrupt changes and dead-zone distortion can be compensated independently, providing a voltage reference value for the inverter. Finally, based on the aforementioned voltage command, a drive signal is generated to drive the permanent magnet synchronous motor to control the robot joints. This directly drives the inverter switching transistors, enabling the actual motor current to quickly track the commanded current. This allows the joint module to remain stable under varying load conditions, improving the stability and accuracy of robot operations.Therefore, this embodiment introduces a sliding mode observation and extended state estimation mechanism in core components such as back EMF feedforward compensation, real-time dead zone compensation, and multi-source voltage superposition. This effectively adapts to the operational requirements of the joint module under varying load conditions and possesses collaborative suppression capabilities against various disturbances such as sudden changes in back EMF and dead zone distortion. Thus, by combining nonlinear disturbance observation with multi-source voltage fusion, the control accuracy, torque stability, and dynamic response speed of the current loop are improved, providing technical support for enhancing the performance of the robot joint module in precision operation and dynamic scenarios. Attached Figure Description

[0009] Figure 1 This is a flowchart of some embodiments of the robot joint module current closed-loop control method according to the present disclosure. Detailed Implementation

[0010] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0011] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0012] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0013] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0014] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0015] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0016] refer to Figure 1 The diagram illustrates a flow 100 of some embodiments of a robot joint module current closed-loop control method according to the present disclosure. This robot joint module current closed-loop control method includes the following steps: Step 101: Collect the feedback current of the permanent magnet synchronous motor.

[0017] In some embodiments, the execution entity (e.g., an electronic device) of the above-described robot joint module current closed-loop control method can be hardware or software. When the computing device is hardware, it can be implemented as a distributed cluster composed of multiple servers or terminal devices, or as a single server or a single terminal device. When the computing device is software, it can be installed in the hardware devices listed above. It can be implemented as multiple software or software modules to provide distributed services, or as a single software or software module. No specific limitations are made here.

[0018] In some embodiments, the aforementioned actuator can collect the feedback current of the permanent magnet synchronous motor. This feedback current can be the actual current flowing through the three-phase stator windings of the permanent magnet synchronous motor. The feedback current can be detected in real time by a current sensor. The feedback current can reflect the current armature reaction state of the motor. The aforementioned permanent magnet synchronous motor can be a synchronous motor in which the rotor is excited by permanent magnets and the stator is supplied with three-phase symmetrical alternating current to generate a rotating magnetic field. The rotational speed of the aforementioned permanent magnet synchronous motor is synchronized with the power supply frequency.

[0019] In practice, the aforementioned actuator (e.g., the servo drive controller in a robot joint module, which can be a microcontroller with an ARM+DSP or FPGA architecture) can sample the three-phase current signal in real time using current sensors (e.g., Hall effect current sensors or shunt resistors with isolation amplifiers) arranged on the three-phase power supply line of the motor. Then, an analog-to-digital converter is used to convert the analog signal into a digital quantity. To eliminate sampling noise, digital filtering (e.g., moving average filtering) can be applied to the sampled values. For example, in a specific robot joint module, the current sensor collects the three-phase current signal at a sampling frequency of 16,000 times per second (triggered by a 16kHz PWM cycle interrupt), denoted as... Then, the rotor electrical angle fed back from the encoder is used for coordinate transformation to finally obtain the direct-axis feedback current and quadrature-axis feedback current in the rotating coordinate system. It should be noted that the "feedback current" collected in this step can refer to the direct-axis current and quadrature-axis current after coordinate transformation, rather than the original three-phase current, because the subsequent control algorithm is performed in the rotating coordinate system.

[0020] Step 102: Generate an initial voltage control quantity based on the feedback current and the preset command current.

[0021] In some embodiments, the aforementioned actuator can generate an initial voltage control quantity based on the aforementioned feedback current and a preset command current. The preset command current can be a current setpoint in a rotating coordinate system calculated based on the target torque or speed command of the robot joint module, and can include: a direct-axis command current and a quadrature-axis command current. The direct-axis command current can generally be set to zero to achieve maximum torque-to-current ratio control. The quadrature-axis command current is proportional to the desired output torque. The initial voltage control quantity can be the voltage value output after linearly adjusting the current error using a proportional-integral controller. The proportional-integral controller can be a linear regulator combining proportional amplification and integral accumulation based on the error. The output of the proportional-integral controller can be the cumulative sum of the proportional coefficient multiplied by the current error and the integral coefficient multiplied by the error. The proportional-integral controller can be used to achieve zero steady-state error tracking.

[0022] In practice, firstly, the difference between the direct-axis feedback current and the direct-axis command current can be calculated to obtain the direct-axis current error. Simultaneously, the difference between the quadrature-axis feedback current and the quadrature-axis command current can be calculated to obtain the quadrature-axis current error. Then, these two current errors are input into a proportional-integral (PI) controller with pre-configured proportional and integral coefficients. The PI controller iteratively calculates according to a preset control cycle (usually synchronized with the PWM cycle, e.g., 16kHz), outputting the direct-axis initial voltage control quantity and the quadrature-axis initial voltage control quantity, respectively. These two initial voltage control quantities can be used as the initial voltage control quantities. It should be noted that the proportional and integral coefficients in this step can be fixed values ​​or adaptively adjusted values. For example, in a specific robot joint module, the direct-axis command current is set to 0 amps, the quadrature-axis command current is set to 5 amps, the currently acquired direct-axis feedback current is 0.1 amps, and the quadrature-axis feedback current is 4.5 amps. Then the direct-axis current error is -0.1 amps, and the quadrature-axis current error is 0.5 amps. After calculation, the proportional-integral controller (with a proportional coefficient of 10 and an integral coefficient of 100) outputs a direct-axis initial voltage control quantity of -1 volt (mainly from the integral term) and a quadrature-axis initial voltage control quantity of 5.5 volts (the proportional term contributes 5 volts, and the integral term contributes 0.5 volts).

[0023] Step 103: Based on the current observation error, generate the back EMF feedforward compensation voltage using a preset sliding mode algorithm.

[0024] In some embodiments, the aforementioned execution entity may generate a back EMF feedforward compensation voltage based on the current observation error using a preset sliding mode algorithm.

[0025] In some optional implementations of certain embodiments, the execution entity may generate a back EMF feedforward compensation voltage based on the current observation error using a preset sliding mode algorithm, which may include the following steps: The first step is to construct the current estimation state equation based on a preset rotating coordinate system. This preset rotating coordinate system can be a coordinate system that rotates synchronously with the direction of the rotor magnetic field of the permanent magnet synchronous motor. This coordinate system can be a dq rotating coordinate system, where the d-axis coincides with the rotor magnetic pole axis, and the q-axis leads the d-axis by 90 electrical degrees. The current estimation state equation can be a differential equation describing the change of the estimated current value over time. This current estimation state equation takes voltage commands and estimated current values ​​as inputs and outputs the rate of change of the estimated current value, which can be used to simulate the electrical dynamic behavior of the motor online.

[0026] The second step involves performing error assessment on the feedback current and the estimated current value, based on the aforementioned current estimation state equation, to obtain the direct-axis current error and the quadrature-axis current error. The estimated current value can be the predicted current value calculated after inputting the voltage command into the current estimation state equation. This estimated current value reflects the current that the motor should generate under ideal conditions. The error assessment process involves comparing the feedback current with the estimated current value and calculating the difference between them. The direct-axis current error can be the difference between the direct-axis feedback current and the estimated direct-axis current value. The quadrature-axis current error can be the difference between the quadrature-axis feedback current and the estimated quadrature-axis current value.

[0027] In practice, within each control cycle, the direct-axis current error is obtained by subtracting the estimated direct-axis current from the current direct-axis feedback current. Similarly, the quadrature-axis current error is obtained by subtracting the estimated quadrature-axis current from the current quadrature-axis feedback current.

[0028] The third step involves applying sliding mode control to the direct-axis current error and the quadrature-axis current error based on the aforementioned sliding mode algorithm, yielding the total direct-axis disturbance value and the total quadrature-axis disturbance value. The sliding mode algorithm can be a nonlinear control strategy that designs a switching function to allow the system state to reach and maintain a preset sliding mode within a finite time, exhibiting insensitivity to parameter perturbations and external disturbances. The sliding mode control process can involve constructing a sliding surface using the current error and then generating the control quantity through nonlinear functions (e.g., square root, sign function, and integral). The total direct-axis disturbance value can be a comprehensive disturbance estimate including the back EMF coupling term in the direct-axis direction and the unmodeled voltage drop (e.g., inverter dead-zone effect, power device on-state voltage drop, line stray resistance loss, and magnetic circuit saturation). The total quadrature-axis disturbance value can also be a comprehensive disturbance estimate including the back EMF coupling term in the quadrature-axis direction and the unmodeled voltage drop.

[0029] The fourth step is to determine the aforementioned total direct-axis disturbance value and the aforementioned total quadrature-axis disturbance value as the back EMF feedforward compensation voltage. This back EMF feedforward compensation voltage can be the voltage component used to counteract the back EMF interference generated during the rotation of the permanent magnet synchronous motor. In practice, the back EMF feedforward compensation voltage can be superimposed on the initial voltage control quantity, allowing the actual current to follow the command current more quickly and reducing the adjustment burden on the proportional-integral controller.

[0030] In some optional implementations of certain embodiments, the execution entity described above may construct the current estimation state equation based on a preset rotating coordinate system, which may include the following steps: The first step is to determine the direct-axis voltage equation and quadrature-axis voltage equation of the aforementioned permanent magnet synchronous motor in a rotating coordinate system. The direct-axis voltage equation can be a mathematical expression describing the relationship between the direct-axis voltage, direct-axis current, quadrature-axis current, and motor parameters. The quadrature-axis voltage equation can also be a mathematical expression describing the relationship between the quadrature-axis voltage, quadrature-axis current, direct-axis current, and motor parameters. In practice, the mathematical expression for the direct-axis voltage equation can be... The mathematical expression for the above quadrature-axis voltage equation can be: Among them, the above It can be a stator resistor. (The above...) It can be a direct-axis voltage. (The above...) It can be a quadrature-axis voltage. (The above...) This can be the component of the motor stator current in the direct axis direction. (The above...) This could be the component of the motor stator current in the quadrature-axis direction. The above... It could be an inductor. (The above...) It could be angular velocity. (The above...) It can be a constant magnetic flux generated by a permanent magnet. (The above...) This could be the rate of change of the direct-axis current with respect to time. (The above...) This could be the rate of change of the quadrature-axis current with respect to time. (The above...) The inductor voltage drop can be caused by the combined effect of the magnetoresistance characteristics of the direct-axis magnetic circuit and the rate of change of the direct-axis current. (The above...) The inductor voltage drop can be caused by the combined effect of the magnetoresistance characteristics of the quadrature-axis magnetic circuit and the rate of change of the quadrature-axis current. (The above...) It can be a direct-axis back EMF coupling term, or it can be derived from the quadrature-axis current. The resulting rotating magnetic field induces a back electromotive force along the direct axis. This value is negative, indicating that its direction is opposite to the direct-axis voltage direction, creating a disturbance in the direct-axis circuit. The above... It can be a quadrature-axis inductive coupling term, which can be derived from the direct-axis current. The generated rotating magnetic field produces a direct-axis magnetic field, which induces a back electromotive force in the quadrature-axis direction. This value is positive, indicating that it is in the same direction as the quadrature-axis voltage, forming a coupled disturbance in the quadrature-axis loop. The above... It can be the back electromotive force term of a permanent magnet, which can be the no-load back electromotive force induced in the quadrature axis winding by a rotating permanent magnet flux linkage.

[0031] The second step involves identifying the back-EMF coupling terms and the unmodeled voltage drop in the aforementioned direct-axis and quadrature-axis voltage equations as lumped disturbance terms. Here, the back-EMF coupling terms can refer to speed-related terms in the equations. In practice, the back-EMF coupling terms in the direct-axis equations can be... The aforementioned back electromotive force coupling term can be represented in the cross-axis equation as follows: The unmodeled voltage drop mentioned above refers to the voltage loss that is not precisely described by the equations due to factors such as parameter variations, nonlinear friction, and inverter nonlinearity. The lumped disturbance term mentioned above can be a combination of all unknown or difficult-to-model disturbances into a single total variable to be estimated.

[0032] The third step involves adding the lumped disturbance term as an unknown state variable to the initial current estimation state equation, generating the extended state equation. The initial current estimation state equation can be the original current estimation equation excluding the lumped disturbance term. It can also be a system of equations that calculates the rate of change of current based on known voltage and nominal parameters. The extended state equation can be an augmented system of equations obtained by treating the lumped disturbance term as a new state variable. This extended state equation can simultaneously describe the dynamic relationship between the current state and the disturbance state.

[0033] Fourth, based on the extended state equations described above, a recursive estimation process is performed using the voltage command and feedback current of the current cycle to obtain the lumped disturbance estimate for the current cycle. This lumped disturbance estimate can be the initial observation value for the sliding mode control process in the next cycle. The voltage command for the current cycle can be the voltage reference value before the back EMF feedforward compensation voltage is superimposed, typically derived from the output of the previous control cycle. The recursive estimation process refers to the iterative calculation process of updating the current cycle's estimate value using the estimate from the previous cycle, combined with the measured value of the current cycle, according to the extended state equations. The lumped disturbance estimate can be an approximation of the lumped disturbance term obtained through the recursive estimation process. The initial observation value can be the reference value used as the initial state of the integral term when the sliding mode control process starts in the next cycle. It should be noted that the "voltage command for the current cycle" here is not the back EMF feedforward compensation voltage being calculated in step 103, nor is it the final voltage command not yet generated in the current cycle. Rather, it refers to the voltage reference value stored in the controller memory after the end of the previous control cycle, synthesized before inverse Park transformation and SVPWM modulation. In the first control cycle after system startup, the initial value of the voltage command is set to zero. By using the voltage command from the previous cycle, circular dependencies are avoided, and recursive updates of the observer are achieved.

[0034] In practice, at the beginning of each control cycle, the lumped disturbance estimate stored in the previous cycle can be read, combined with the voltage command and feedback current of the current cycle, and substituted into the extended state equation for a one-step Euler recursion to obtain the lumped disturbance estimate of the current cycle.

[0035] The fifth step involves low-pass filtering the lumped disturbance estimate to obtain the current estimation state equation. This low-pass filtering can refer to a signal processing operation that allows low-frequency signals to pass while attenuating high-frequency noise. In practice, a first-order low-pass filter is typically used, with its cutoff frequency set to 2 to 3 times the current loop bandwidth. The current estimation state equation can be the updated state equation obtained after low-pass filtering, used for current estimation in the next cycle. The disturbance term in the current estimation state equation has already had high-frequency chattering filtered out.

[0036] In some optional implementations of certain embodiments, the execution entity may perform sliding mode control processing on the direct-axis current error and the quadrature-axis current error based on the sliding mode algorithm to obtain the total direct-axis disturbance value and the total quadrature-axis disturbance value, which may include the following steps: The first step is to perform a square root operation on the aforementioned direct-axis current error to obtain the direct-axis square root result. This square root operation can be a mathematical operation involving calculating the arithmetic square root of a non-negative number. In practice, the absolute value of the direct-axis current error is taken before taking the square root, or the absolute value of the error is directly taken to ensure the result is a real number. The direct-axis square root result can then be the square root of the absolute value of the direct-axis current error.

[0037] The second step involves multiplying the square root result of the direct axis by the sign function of the direct axis current error to generate a direct axis nonlinear proportional term. This sign function can be a function with an output of +1 (positive input), -1 (negative input), or 0 (zero input), which can be used to preserve the direction information of the error. The direct axis nonlinear proportional term can refer to the portion of the sliding mode control law that is proportional to the square root of the current error (this can provide fast convergence).

[0038] The third step involves integrating the sign function of the direct-axis current error to generate a direct-axis nonlinear integral term. This integration can be achieved by summing the time-varying signal (accumulating once per control cycle). The direct-axis nonlinear integral term can be a portion obtained by integrating the sign function in the sliding mode control law (which can be used to eliminate steady-state errors and converge within a finite time).

[0039] The fourth step is to sum the aforementioned direct-axis nonlinear proportional term and the aforementioned direct-axis nonlinear integral term to generate the total direct-axis perturbation value. Here, the summation can refer to an arithmetic operation of adding two values. The aforementioned total direct-axis perturbation value can be an estimate of the lumped perturbation (back EMF coupling term and unmodeled voltage drop) along the direct axis.

[0040] The fifth step is to perform a square root operation on the aforementioned quadrature-axis current error to obtain the quadrature-axis square root result. This result can be the square root of the absolute value of the quadrature-axis current error.

[0041] Step 6: Multiply the square root result of the cross-axis by the sign function of the cross-axis current error to generate the cross-axis nonlinear proportional term. This cross-axis nonlinear proportional term can refer to the portion of the sliding mode control law that is proportional to the square root of the current error in the cross-axis direction.

[0042] Step 7: Integrate the sign function of the quadrature-axis current error to generate a quadrature-axis nonlinear integral term. This quadrature-axis nonlinear integral term can refer to the portion obtained by integrating the sign function of the quadrature-axis direction in the sliding mode control law. Step 8: Summate the aforementioned cross-axis nonlinear proportional term with the aforementioned cross-axis nonlinear integral term to obtain the total cross-axis perturbation value. This total cross-axis perturbation value can be an estimate of the lumped perturbation along the cross-axis direction.

[0043] In practice, the above calculations for the direct axis and quadrature axis can be performed in parallel within each control cycle, generating the total disturbance value for the direct axis and the total disturbance value for the quadrature axis.

[0044] For example, we can assume the current direct-axis current error is -0.1 amperes, with the square root of its absolute value being approximately 0.316. Multiplying this by the sign function (-1) yields a direct-axis nonlinear proportional term of approximately -0.316. The integral term of the sign function can be assumed to be -0.5, resulting in a total direct-axis disturbance of -0.816 volts, which can be the direct-axis back EMF feedforward compensation voltage. Similarly, the quadrature-axis component can be calculated. In this way, the sliding mode algorithm can estimate the back EMF disturbance within a finite time and cancel it out in the form of voltage feedforward.

[0045] Step 104: Real-time estimation of inverter dead-zone voltage distortion is performed to generate dead-zone compensation voltage.

[0046] In some embodiments, the aforementioned execution entity can perform real-time estimation of inverter dead-zone voltage distortion to generate a dead-zone compensation voltage. The dead-zone compensation voltage refers to the voltage component used to offset the dead-zone effect. In practice, the dead-zone compensation voltage can be superimposed on the initial voltage control quantity to eliminate waveform distortion near the current zero-crossing point.

[0047] As an example, in a robot joint module, the inverter switching frequency is 16kHz and the dead time is set to 2 microseconds. When the motor current approaches zero crossing, the dead time effect causes the output voltage to be distorted by about 10 volts.

[0048] In some optional implementations of certain embodiments, the aforementioned execution entity can perform real-time estimation of inverter dead-zone voltage distortion, and generating a dead-zone compensation voltage may include the following steps: The first step involves acquiring the current output voltage command from the inverter and the feedback current from the permanent magnet synchronous motor. The inverter can be a power electronic device that converts DC to AC to drive the permanent magnet synchronous motor, and can be configured with six switching transistors (e.g., IGBTs or MOSFETs) in a three-phase full-bridge topology. The current output voltage command refers to the voltage command calculated at the end of the previous control cycle and then subjected to amplitude limiting (i.e., the output from step 105 below). This voltage command value is stored in the controller's register for use in the current cycle. In the first control cycle after system startup, the initial value of the output voltage command is zero.

[0049] The second step is to define the voltage distortion caused by the inverter dead zone as an extended state variable. The inverter dead zone can be a short-time delay interval set to prevent the simultaneous conduction of two switches on the same bridge arm of the inverter. When both switches are turned off during the inverter dead zone, a deviation occurs between the actual output voltage and the commanded voltage; this deviation is the voltage distortion value. The extended state variable can be an unknown disturbance term not belonging to the original system state equations, introduced as a new state variable into the state equations, which can be estimated in real time using an observer.

[0050] The third step involves constructing the state equations of the augmented system based on the aforementioned output voltage command, feedback current, and extended state variables. These state equations can be a system of differential equations that combine the original system state (e.g., motor current) with the extended state variables (dead-zone voltage distortion), describing the evolution of the system state and disturbances over time. In practice, based on the motor electrical model (e.g., voltage equations), the dead-zone distortion can be treated as an unknown input applied to the output, and the augmented equations can be expressed as follows: Among them, the above It can be a current state. (The above) This could be a voltage command. (The above) It could be dead zone distortion.

[0051] The fourth step involves establishing a dynamic extended state observer based on the state equations of the augmented system described above, which determines the system state and extended state variables. This dynamic extended state observer can be a dynamic algorithm that estimates the system state and extended state in real time using system input and output data. The prediction error can be corrected by introducing an observer gain matrix, allowing the estimated value to converge quickly to the true value. The extended state can refer to the state where the observer simultaneously estimates both the original state and the extended perturbation state.

[0052] The fifth step involves using the aforementioned dynamic extended state observer to estimate the voltage distortion value at the current moment in real time, generating an estimated dead-zone distortion value for that moment. This estimated dead-zone distortion value can be an approximation of the actual voltage distortion caused by the inverter's dead zone, and can be updated in real time as the motor's operating conditions change.

[0053] The sixth step is to perform a compensation polarity transformation on the estimated dead zone distortion value at the current moment to generate a dead zone compensation voltage. The compensation polarity transformation can be performed by taking the inverse of the estimated distortion value (i.e., multiplying it by -1; to cancel the distortion, a voltage of equal magnitude but opposite direction needs to be applied).

[0054] In some optional implementations of certain embodiments, the execution entity can utilize the aforementioned dynamic extended state observer to estimate the voltage distortion value at the current moment in real time. Generating the dead-zone distortion estimate at the current moment may include the following steps: The first step is to determine the gain parameters of the aforementioned dynamically extended state observer, where the estimation bandwidth of the dynamically extended state observer is higher than the response bandwidth of the current loop. The gain parameters can refer to the coefficient matrix in the observer used to amplify the prediction error, and can be denoted as... The value of this value determines the convergence speed and noise immunity of the observer. The estimated bandwidth mentioned above can be the highest frequency of the signal that the observer can effectively track. The higher the bandwidth, the faster the observer response, but the more sensitive it is to noise. The response bandwidth of the current loop mentioned above can be the highest frequency at which the current closed-loop control system can effectively track the command current, and can be from hundreds to thousands of hertz.

[0055] In practice, the observer gain parameters can be pre-calculated using the pole placement method or the bandwidth parameterization method and stored in the controller memory to ensure that the observer response speed is faster than the current loop, so as to compensate for dead-zone disturbances in a timely manner.

[0056] The second step involves acquiring the estimated system state value and the estimated dead-zone distortion value from the previous control cycle. The estimated system state value can be the motor current estimate calculated by the observer at the previous sampling time (e.g., the previous PWM interrupt). The estimated dead-zone distortion value can be the dead-zone voltage distortion value estimated at the previous sampling time. In practice, these two values ​​can be stored in the controller's registers or memory for use in the current cycle.

[0057] The third step involves performing a one-step recursive calculation on the system state value and dead-zone distortion value based on the state equation of the augmented system. This calculation utilizes the current output voltage command and feedback current to obtain the predicted system state value and dead-zone distortion value for the current moment. This one-step recursive calculation can be performed by extrapolating the estimated value from the previous cycle to the predicted value for the current cycle using the state equation, employing methods such as the Euler method or the Runge-Kutta method. The predicted system state value can be the estimated value of the motor current at the current moment, which has not yet been corrected by actual measurements. The predicted dead-zone distortion value can be the estimated value of the dead-zone distortion at the current moment.

[0058] In practice, the estimated value from the previous period can be substituted into the augmented state equation, multiplied by the sampling period, and added to the estimated value from the previous period to obtain the predicted system state and dead zone distortion values ​​at the current moment.

[0059] The fourth step is to compare the predicted system state value with the measured feedback current value collected at the current moment to obtain the state prediction error. This state prediction error can be the difference between the predicted system state value and the measured feedback current value.

[0060] Fifth, multiply the aforementioned state prediction error by the aforementioned gain parameter to obtain the correction vector. This correction vector can be an adjustment amount used to correct the predicted value.

[0061] Step 6: Superimpose the above-mentioned correction vector onto the result of the recursive calculation in the previous step to generate the corrected system state estimate and the corrected dead-zone distortion estimate at the current time. The corrected system state estimate at the current time can be the current estimate after actual measurement feedback correction. The corrected dead-zone distortion estimate at the current time can be the corrected dead-zone voltage distortion estimate.

[0062] Step 7: Determine the dead zone distortion estimate after correction at the current time as the dead zone distortion estimate at the current time.

[0063] Step 105: Perform voltage superposition processing on the initial voltage control quantity, back EMF feedforward compensation voltage, and dead zone compensation voltage to generate a voltage command.

[0064] In some embodiments, the execution entity may perform voltage superposition processing on the initial voltage control quantity, the back EMF feedforward compensation voltage, and the dead zone compensation voltage to generate a voltage command.

[0065] In some optional implementations of certain embodiments, the execution entity may perform voltage superposition processing on the initial voltage control quantity, the back EMF feedforward compensation voltage, and the dead-zone compensation voltage to generate a voltage command, which may include the following steps: The first step involves acquiring the direct-axis initial voltage control quantity, the direct-axis back EMF feedforward compensation voltage, and the direct-axis dead-zone compensation voltage. The initial voltage control quantity can be the initial voltage control quantity corresponding to the direct-axis direction of the permanent magnet synchronous motor, or the output value of the proportional-integral controller on the direct axis. The direct-axis back EMF feedforward compensation voltage can be the voltage component used to compensate for the back EMF disturbance in the direct-axis direction, i.e., the total direct-axis disturbance value estimated by the sliding mode algorithm. The direct-axis dead-zone compensation voltage can be the compensation quantity used to compensate for the voltage distortion caused by the inverter dead-zone effect on the direct axis.

[0066] The second step involves algebraically adding the aforementioned direct-axis initial voltage control value, the aforementioned direct-axis back EMF feedforward compensation voltage, and the aforementioned direct-axis dead-zone compensation voltage to generate the direct-axis voltage component. This algebraic addition can be achieved by summing the three values ​​algebraically, i.e., direct-axis voltage component = direct-axis initial voltage control value + direct-axis back EMF feedforward compensation voltage + direct-axis dead-zone compensation voltage. The aforementioned direct-axis voltage component can be the total voltage reference value applied along the direct-axis direction.

[0067] The third step involves acquiring the quadrature-axis initial voltage control quantity, the quadrature-axis back EMF feedforward compensation voltage, and the quadrature-axis dead-zone compensation voltage. The quadrature-axis initial voltage control quantity can be the initial voltage control quantity corresponding to the quadrature-axis direction of the permanent magnet synchronous motor. The quadrature-axis back EMF feedforward compensation voltage can be the voltage component used to compensate for the back EMF disturbance in the quadrature-axis direction, i.e., the total quadrature-axis disturbance value estimated by the sliding mode algorithm. The quadrature-axis dead-zone compensation voltage can be the compensation quantity used to compensate for the voltage distortion caused by the inverter dead-zone effect on the quadrature axis.

[0068] The fourth step involves algebraically adding the aforementioned quadrature-axis initial voltage control value, the aforementioned quadrature-axis back EMF feedforward compensation voltage, and the aforementioned quadrature-axis dead-zone compensation voltage to generate the quadrature-axis voltage component. The aforementioned quadrature-axis voltage component can be the total voltage reference value applied in the quadrature-axis direction, i.e., quadrature-axis voltage component = quadrature-axis initial voltage control value + quadrature-axis back EMF feedforward compensation voltage + quadrature-axis dead-zone compensation voltage.

[0069] The fifth step is to use the aforementioned direct-axis voltage component and the aforementioned quadrature-axis voltage component as the initial voltage command. The initial voltage command can be the original voltage reference value before it has undergone amplitude limiting processing, and can be composed of both the direct-axis voltage component and the quadrature-axis voltage component, represented in a rotating coordinate system.

[0070] The sixth step involves limiting the initial voltage command to obtain the final voltage command. This limiting process restricts the voltage command amplitude to a preset maximum allowable range to prevent the output voltage from exceeding the maximum value provided by the inverter's DC bus voltage, thus avoiding inverter saturation or overmodulation. The preset maximum allowable range can be determined based on the inverter's DC bus voltage and the linear modulation region of the modulation algorithm (e.g., space vector pulse width modulation). For example, for a system with a DC bus voltage of 300 volts, the root mean square values ​​of the direct-axis and quadrature-axis voltage components are typically limited to approximately 173 volts. The voltage command can be the final voltage reference value after the limiting process. This voltage command can then be used to generate the actual switching signal for driving the permanent magnet synchronous motor.

[0071] In practice, firstly, the magnitude of the initial voltage command can be calculated ( If the amplitude exceeds a preset limiting threshold (e.g., the DC bus voltage divided by...), The direct-axis and quadrature-axis voltage components are reduced simultaneously using a proportional scaling method, ensuring the composite vector lies within the voltage limit circle. If the threshold is not exceeded, the original value remains unchanged. This limiting process ensures the inverter operates in the linear modulation region, preventing output voltage distortion.

[0072] Step 106: Based on the voltage command, generate a drive signal to drive the permanent magnet synchronous motor to control the robot joints.

[0073] In some embodiments, the aforementioned execution entity can generate drive signals based on the aforementioned voltage commands to drive the aforementioned permanent magnet synchronous motor to control the robot joints. The aforementioned voltage commands, in a rotating coordinate system (dq axis), can be composed of both direct-axis and quadrature-axis voltage components. The aforementioned drive signals can be used to control the on / off state of the power switching transistors (e.g., IGBTs or MOSFETs) in the inverter via pulse-width modulation waveforms, typically six interconnected pulse signals, driving the three upper and three lower bridge arms of the inverter respectively. The aforementioned robot joints can be movable connections between two adjacent links of the robot, and can be composed of a permanent magnet synchronous motor, a harmonic reducer, an encoder, and a servo drive board, enabling precise rotational movement.

[0074] In practice, firstly, an inverse Park transformation can be performed on the voltage command to convert the direct-axis voltage components and quadrature-axis voltage components in the rotating coordinate system into two-phase voltage components in the stationary coordinate system (commonly referred to as...). Axis voltage components and (Axis voltage component). Then, space vector pulse width modulation calculation is performed on the above two-phase voltage components to determine the conduction time of the six switching transistors of the inverter, generating the corresponding six pulse width modulation signals (drive signals). Finally, the six drive signals are output to the inverter's drive circuit, driving the power switching transistors in the inverter to operate according to the preset switching sequence, applying the corresponding voltage to the three-phase stator windings of the permanent magnet synchronous motor, generating a rotating magnetic field, driving the motor rotor to rotate, and then driving the robot joints to complete the movement after the torque is amplified by the harmonic reducer.

[0075] For example, in a specific robot joint module, the voltage command can be a 5-volt direct-axis voltage component and a 10-volt quadrature-axis voltage component. The execution unit (e.g., the space vector pulse width modulation module in the servo drive controller) performs inverse Park transform and SVPWM modulation at a 16kHz PWM carrier frequency to calculate the three-phase duty cycles of 30%, 50%, and 70%, generating six complementary drive signals with a 2-microsecond dead time. These signals drive the inverter to output the corresponding three-phase AC voltage, enabling the permanent magnet synchronous motor to output rated torque and rotate the robot joint at a constant speed of 0.5 radians per second. In this way, the voltage command calculated by the control algorithm can be converted into actual electromagnetic torque, achieving precise control of the robot joint.

[0076] The above-described embodiments of this disclosure have the following beneficial effects: The robot joint module current closed-loop control method of some embodiments of this disclosure improves the control accuracy and response speed of the current loop under complex disturbances, effectively suppresses torque fluctuations caused by sudden changes in back EMF, eliminates low-speed vibrations caused by dead-zone effects, and enhances the stability of robot joint motion under variable load conditions. Specifically, the reasons for low current control accuracy, large torque pulsation, and slow response speed are: the proportional-integral controller relies on linear error feedback and cannot offset voltage disturbances caused by sudden changes in back EMF; it cannot suppress the nonlinear distortion introduced by the inverter dead time; and the fixed parameters of the proportional-integral controller cannot adapt to changes in the rotational inertia and friction coefficient of the joint module during actual motion. Based on this, the robot joint module current closed-loop control method of some embodiments of this disclosure first collects the feedback current of the permanent magnet synchronous motor. This provides real-time physical quantity input for subsequent current closed-loop control, enabling the control system to accurately obtain the current state of the motor, avoiding current estimation errors caused by model mismatch in open-loop control, and providing a data basis for current regulation. Secondly, based on the aforementioned feedback current and the preset command current, an initial voltage control quantity is generated. This ensures the system's tracking capability under steady-state conditions and provides a stable reference control quantity for subsequent compensation stages. Next, based on the current observation error, a preset sliding mode algorithm is used to generate a back EMF feedforward compensation voltage. This allows for real-time estimation of lumped disturbances such as back EMF within a finite time, and the abrupt impact of physical back EMF is offset by voltage feedforward. This effectively avoids the torque fluctuations and response lag problems caused by back EMF disturbances in traditional methods. Furthermore, the inverter dead-zone voltage distortion is estimated in real-time to generate a dead-zone compensation voltage. Thus, by using a dynamic extended state observer to expand the voltage distortion caused by the dead zone into the system state and track it in real-time, the voltage clamping effect near the current zero-crossing point can be accurately estimated, and a reverse compensation voltage can be generated to offset it. This effectively eliminates current distortion and torque pulsation near the zero-crossing point and reduces the speed fluctuation rate of the joint modules. Finally, the aforementioned initial voltage control quantity, the aforementioned back EMF feedforward compensation voltage, and the aforementioned dead-zone compensation voltage are superimposed to generate a voltage command. This achieves the parallel integration of multiple disturbance suppression methods, ensuring that back EMF abrupt changes and dead-zone distortion can be compensated independently, providing a voltage reference value for the inverter. Finally, based on the aforementioned voltage command, a drive signal is generated to drive the permanent magnet synchronous motor to control the robot joints. This directly drives the inverter switching transistors, enabling the actual motor current to quickly track the commanded current. This allows the joint module to remain stable under varying load conditions, improving the stability and accuracy of robot operations.Therefore, this embodiment introduces a sliding mode observation and extended state estimation mechanism in core components such as back EMF feedforward compensation, real-time dead zone compensation, and multi-source voltage superposition. This effectively adapts to the operational requirements of the joint module under varying load conditions and possesses collaborative suppression capabilities against various disturbances such as sudden changes in back EMF and dead zone distortion. Thus, by combining nonlinear disturbance observation with multi-source voltage fusion, the control accuracy, torque stability, and dynamic response speed of the current loop are improved, providing technical support for enhancing the performance of the robot joint module in precision operation and dynamic scenarios.

[0077] Based on the same inventive concept, embodiments of this application provide a robot joint module current closed-loop control system, including: The acquisition module is used to acquire the feedback current of the permanent magnet synchronous motor, the output voltage command of the inverter at the current moment, the feedback current of the permanent magnet synchronous motor, the system state value estimated in the previous control cycle, the dead zone distortion value estimated in the previous control cycle, the direct axis initial voltage control quantity, the direct axis back EMF feedforward compensation voltage and the direct axis dead zone compensation voltage, the quadrature axis initial voltage control quantity, the quadrature axis back EMF feedforward compensation voltage and the quadrature axis dead zone compensation voltage; A memory for storing a program for a closed-loop control method for current in a robot joint module; The processor can load and execute programs in memory to implement a closed-loop current control method for robot joint modules.

[0078] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0079] This application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed as a closed-loop current control method for a robot joint module.

[0080] Computer storage media include, for example, USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media that can store program code.

[0081] Based on the same inventive concept, this application provides an intelligent terminal, including a memory and a processor. The memory stores a computer program that can be loaded and executed by the processor to provide a closed-loop current control method for a robot joint module.

[0082] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0083] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only one example of a series of equivalent or similar features.

Claims

1. A closed-loop control method for current in a robot joint module, characterized in that, include: Collect the feedback current of the permanent magnet synchronous motor; Based on the feedback current and the preset command current, an initial voltage control quantity is generated; Based on the current observation error, a back EMF feedforward compensation voltage is generated using a preset sliding mode algorithm. Real-time estimation and processing of inverter dead-zone voltage distortion is performed to generate dead-zone compensation voltage; The initial voltage control quantity, the back EMF feedforward compensation voltage, and the dead zone compensation voltage are superimposed to generate a voltage command; Based on the voltage command, a drive signal is generated to drive the permanent magnet synchronous motor to control the robot joints.

2. The closed-loop control method for current of a robot joint module according to claim 1, characterized in that, The step of generating the back EMF feedforward compensation voltage based on the current observation error using a preset sliding mode algorithm includes: Based on a preset rotating coordinate system, a current estimation state equation is constructed. Based on the current estimation state equation, error judgment processing is performed on the feedback current and the current estimation value to obtain the direct-axis current error and the quadrature-axis current error. Based on the sliding mode algorithm, the direct-axis current error and the quadrature-axis current error are processed by sliding mode control to obtain the total direct-axis disturbance value and the total quadrature-axis disturbance value. The total disturbance value of the direct axis and the total disturbance value of the quadrature axis are determined to be the back electromotive force feedforward compensation voltage.

3. The closed-loop control method for current of a robot joint module according to claim 2, characterized in that, The step of constructing the current estimation state equation based on the preset rotating coordinate system includes: Determine the direct-axis voltage equation and quadrature-axis voltage equation of the permanent magnet synchronous motor in the rotating coordinate system; The back electromotive force coupling term and the unmodeled voltage drop in the direct-axis voltage equation and the quadrature-axis voltage equation are identified as lumped disturbance terms. The lumped disturbance term is added as an unknown state variable to the initial current estimation state equation to generate the extended state equation; Based on the extended state equation, the voltage command and feedback current of the current cycle are used for recursive estimation to obtain the lumped disturbance estimate of the current cycle, wherein the lumped disturbance estimate of the current cycle is the initial observation value for the sliding mode control process of the next cycle. The lumped disturbance estimate is low-pass filtered to obtain the current estimation state equation.

4. The closed-loop control method for current of a robot joint module according to claim 2, characterized in that, The step of performing sliding mode control processing on the direct-axis current error and the quadrature-axis current error based on the sliding mode algorithm to obtain the total direct-axis disturbance value and the total quadrature-axis disturbance value includes: The square root of the direct-axis current error is performed to obtain the direct-axis square root result; Multiply the square root result of the direct axis by the sign function of the direct axis current error to generate a direct axis nonlinear scaling term; The sign function of the direct-axis current error is integrated to generate a direct-axis nonlinear integral term; The direct-axis nonlinear proportional term and the direct-axis nonlinear integral term are summed to generate the total direct-axis disturbance value; The quadrature axis current error is square rooted to obtain the quadrature axis square root result; Multiply the square root result of the cross-axis by the sign function of the cross-axis current error to generate a cross-axis nonlinear proportional term; The sign function of the cross-axis current error is integrated to generate a cross-axis nonlinear integral term; The total cross-axis disturbance value is obtained by summing the cross-axis nonlinear proportional term and the cross-axis nonlinear integral term.

5. The closed-loop control method for current of a robot joint module according to claim 1, characterized in that, The step of real-time estimation of inverter dead-zone voltage distortion to generate dead-zone compensation voltage includes: The inverter's current output voltage command and the permanent magnet synchronous motor's feedback current are collected. The voltage distortion value caused by the inverter dead zone is determined as an extended state variable; Based on the output voltage command, the feedback current, and the extended state variables, the state equation of the augmented system is constructed. Based on the state equation of the augmented system, a dynamic extended state observer is established to determine the system state and extended state variables; The voltage distortion value at the current moment is estimated in real time using the dynamic expansion state observer, and the dead zone distortion estimate value at the current moment is generated. The dead zone distortion estimate at the current moment is subjected to a compensation polarity transformation to generate a dead zone compensation voltage.

6. The closed-loop control method for current of a robot joint module according to claim 5, characterized in that, The step of using the dynamic extended state observer to estimate the voltage distortion value at the current moment in real time and generating the dead zone distortion estimate value at the current moment includes: Determine the gain parameter of the dynamic extended state observer, wherein the estimated bandwidth of the dynamic extended state observer is higher than the response bandwidth of the current loop; Collect the system state value estimated in the previous control cycle and the dead zone distortion value estimated in the previous control cycle; Based on the state equation of the augmented system, the system state value and the dead zone distortion value are calculated in one step using the output voltage command and feedback current at the current moment to obtain the predicted system state value and the predicted dead zone distortion value at the current moment. The predicted system state value is compared with the measured feedback current value collected at the current moment to obtain the state prediction error; Multiply the state prediction error by the gain parameter to obtain the correction vector; The correction vector is superimposed on the result of the step-by-step recursive calculation to generate the corrected system state estimate and the corrected dead zone distortion estimate at the current time. The corrected dead zone distortion estimate at the current time is determined to be the dead zone distortion estimate at the current time.

7. The closed-loop control method for current of a robot joint module according to claim 1, characterized in that, The step of performing voltage superposition processing on the initial voltage control quantity, the back electromotive force feedforward compensation voltage, and the dead zone compensation voltage to generate a voltage command includes: Collect the direct-axis initial voltage control quantity, the direct-axis back EMF feedforward compensation voltage, and the direct-axis dead-zone compensation voltage; The direct-axis initial voltage control quantity, the direct-axis back electromotive force feedforward compensation voltage, and the direct-axis dead-zone compensation voltage are algebraically added to generate the direct-axis voltage component; Collect the quadrature axis initial voltage control quantity, quadrature axis back EMF feedforward compensation voltage, and quadrature axis dead zone compensation voltage; The quadrature axis initial voltage control quantity, the quadrature axis back electromotive force feedforward compensation voltage, and the quadrature axis dead zone compensation voltage are algebraically added to generate the quadrature axis voltage component; The direct-axis voltage component and the quadrature-axis voltage component are used as the initial voltage command; The initial voltage command is subjected to amplitude limiting processing to obtain the voltage command.

8. A closed-loop control system for current in a robot joint module, characterized in that, include: The acquisition module is used to acquire the feedback current of the permanent magnet synchronous motor. A memory for storing a program of a robot joint module current closed-loop control method as described in any one of claims 1 to 7; The processor and the program in the memory can be loaded and executed by the processor to implement the robot joint module current closed-loop control method as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer program is stored and can be loaded by a processor and executed as described in any one of claims 1 to 7, which is a closed-loop current control method for a robot joint module.

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