Motor soft landing control method and system based on finite time state observer and motor

Abstract

The invention provides a motor soft landing control method and system based on a finite time state observer and a motor. According to the method, the external disturbing force is estimated in real time through a finite time state observer, the approaching speed is dynamically adjusted according to the difference value between the target retention force and the actually estimated external force, and the force-adaptive soft landing process is achieved. Compared with a traditional method, the technology does not need a large amount of pre-test data, saves working hours, is high in universality and short in convergence time, almost has no lag, and meets the high-beat production requirement. The system does not need a special force sensor and can realize accurate force control only by using motor current and position information, so that the product quality is remarkably improved and the cost is reduced.

Description

Technical Field

[0001] This application relates to the field of motor control technology, specifically to a motor soft landing control method, system, and motor based on a finite-time state observer. Background Technology

[0002] Electric motors, such as voice coil motors, are widely used in high-precision positioning systems, including high-precision positioning platforms, image stabilization systems, precision medical equipment, and flexible robots, due to their simple structure, fast dynamic response, high linearity, and long lifespan. However, in practical applications, external forces (such as gravity, elasticity, and magnetic forces) can significantly affect the landing accuracy and stability of the motor due to the influence of mechanical structure and load during movement.

[0003] Currently, the main methods used to solve this problem are the lookup table method and the observer method. The lookup table method compensates for the current based on position feedback, but it has the following obvious drawbacks: 1. It requires a large amount of pre-test data, consumes a lot of time, and has high implementation costs; 2. Poor versatility; different lookup tables need to be created for different working conditions, making it difficult to make them universal across products. 3. Difficult to adapt to complex nonlinear external forces (such as cogging force, magnetic springs, viscous friction, etc.); 4. It cannot handle dynamically changing load conditions and has poor adaptability to environmental changes; 5. Low storage and retrieval efficiency, consumes system resources, and increases hardware costs; While conventional observers are more flexible than lookup table methods, traditional linear observers suffer from slow convergence speeds, resulting in significant lag in the compensation current and limited observation accuracy. This makes them unsuitable for meeting the high real-time requirements of fast-paced production scenarios.

[0004] Therefore, there is an urgent need for a solution that allows motors to achieve a smooth and efficient soft landing. Summary of the Invention

[0005] To address the aforementioned problems in the prior art, this paper aims to provide a motor soft landing control method, system, and motor based on a finite-time state observer, which can achieve efficient, smooth, and accurate soft landing of a voice coil motor.

[0006] To solve the above-mentioned technical problems, the specific technical solution presented in this paper is as follows: On the one hand, this paper provides a motor soft landing control method based on a finite-time state observer, the method comprising: S1: Obtain the target force value of the motor during landing, wherein the target force value is a preset value; S2: Obtain the operating data of the motor, the operating data including at least speed data and current data; S3: Design a finite-time state observer to estimate the external force value of the motor during landing in the current state based on the motor's operating data; S4: When the error between the external force value and the target force value is not lower than a preset threshold, adjust the motor's operating data according to the error so that the external force value received by the motor during landing is close to the target force value; S5: Repeat steps S2-S4 according to the preset time step. When the error between the external force value and the target force value is less than the preset threshold, maintain the current operating parameters until the motor lands.

[0007] Furthermore, a finite-time state observer is designed to estimate the external force values ​​experienced by the motor during landing in the current state based on the motor's operating data, including: The speed and current data of the motor are collected at preset time steps; Based on the speed data at the current acquisition time and the observed speed at the previous acquisition time, the speed error at the current acquisition time is determined. The observed speed is a state variable obtained by accumulating and integrating the motion data of the motor using a nonlinear feedback gain algorithm. The initial value of the observed speed is 0. Based on the velocity error and nonlinear observation acceleration gain at the current acquisition time, the derivative of the observation perturbation acceleration at the acquisition time is updated. The observed perturbation acceleration at the current acquisition time is updated based on the derivative of the observed perturbation acceleration at the current acquisition time and the observed perturbation acceleration at the previous acquisition time. Based on the velocity error, current data, observed disturbance acceleration, and nonlinear observed velocity gain at the current acquisition time, the observed velocity derivative at the current acquisition time is updated. Based on the derivative of the observation velocity at the current acquisition time and the observation velocity at the previous acquisition time, the observation velocity at the current acquisition time is updated to be used for estimating the external force value at the next acquisition time. Based on the observed disturbance acceleration at the current acquisition time, the external force value experienced by the motor during landing is estimated.

[0008] Furthermore, the finite-time state observer estimates the external force value using the following formula:

[0009] in, e For speed error; v The velocity data is obtained through the encoder position derivative; z2 The observed velocity is initially set to 0. z3 To observe the acceleration of the disturbance, the initial value is 0;dz2 for z2 The derivative of dz3 for z3 The derivative of k2 and k3 For nonlinear observer gain; dt For time step; I This is the motor's current data; Mn It is the ratio of the moving mass to the torque constant; sign (e) The sign function for velocity error; abs(e) This represents the absolute value of the speed error. F est To estimate the external force acting on the motor.

[0010] Furthermore, when the error between the external force value and the target force value is not lower than a preset threshold, the operating data of the motor is adjusted according to the error, including: Based on the error between the external force value and the target force value, the speed data of the motor is updated using a proportional-integral algorithm. Adjust the current data of the motor to obtain updated speed data of the motor.

[0011] Furthermore, the speed data of the motor is updated using the following formula:

[0012] in, v For speed data; k p This is the proportionality coefficient; k i Integral coefficient ；F target The target force value; F est To estimate the external force value of the obtained motor.

[0013] Furthermore, the motor's operating data also includes terminal position data, and is further included before step S1. S01: Pre-landing step, the motor is controlled by a preset current to complete the pre-landing, and the terminal position data of the motor at the pre-landing time is obtained. The external force value at the pre-landing time is less than the target force value. The distance between the terminal position data and the initial position of the motor is calculated, and the motion state of the motor is divided into high-speed approach stage, transition stage, force-controlled approach stage and final positioning stage based on the distance.

[0014] Furthermore, when the distance between the terminal position data and the initial position of the motor is greater than a preset interval, the distance is divided into a high-speed interval, a transition interval, and a force-controlled approach interval. The motor is controlled to enter the high-speed approach phase at full speed, and the motor speed data is reduced according to a preset rule. When the speed data is lower than the first preset value and the position data of the motor enters the transition range, the current running data is maintained to control the motor to enter the force-controlled approach range, and step S1 is executed with the current running data.

[0015] Furthermore, when the error between the external force value and the target force value is less than a preset threshold, and the position data of the motor is consistent with the terminal position data of the motor, the motor completes landing and enters the final positioning stage.

[0016] On the other hand, this paper also provides a motor soft landing control system based on a finite-time state observer, the system including a motor and a target workpiece; The motor includes a controller configured to execute the motor soft landing control method based on a finite-time state observer as described above.

[0017] Finally, this paper also provides a motor, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the motor soft landing control method based on a finite-time state observer as described above.

[0018] By adopting the above technical solution, the motor soft landing control method, system and motor based on finite-time state observer described in this paper estimate the external disturbance force in real time through the finite-time state observer, and dynamically adjust the approach speed according to the difference between the target holding force and the actual estimated external force, so as to realize the force adaptive soft landing process. Through position feedback and external force estimation, precise force control is achieved in the absence of pressure sensors, ensuring that the force is controllable and the transition is smooth during the landing process.

[0019] To make the above and other objects, features and advantages of this document more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments or prior art described herein, the accompanying drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this article. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1This document illustrates the steps of the motor soft landing control method based on a finite-time state observer provided in the embodiments of this paper. Figure 2 A schematic diagram of the framework of the motor soft landing control system based on a finite-time state observer provided in the embodiments of this paper is shown. Detailed Implementation

[0022] The technical solutions in the embodiments described below will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments described herein, and not all of the embodiments. Based on the embodiments described herein, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this document.

[0023] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings herein are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, apparatus, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0024] Currently, the main methods for controlling voice coil motors are lookup table method and observer method. The lookup table method compensates for current based on position feedback. Although conventional observers are more flexible than the lookup table method, traditional linear observers have a slow convergence speed, resulting in a significant lag in the compensation current and limited observation accuracy, which cannot meet the high real-time requirements of fast-paced production scenarios.

[0025] To address the aforementioned issues, this paper presents a motor soft landing control method based on a finite-time state observer, which enables efficient, smooth, and accurate soft landing of a voice coil motor. Figure 1 This is a schematic diagram illustrating the steps of the motor soft landing control method based on a finite-time state observer provided in the embodiments of this document. This specification provides the operational steps of the method described in the embodiments or flowcharts, but based on conventional or non-inventive labor, more or fewer operational steps may be included. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only execution order. In actual system or device products, the methods shown in the embodiments or drawings can be executed sequentially or in parallel. Specifically, as shown in the figures... Figure 1 As shown, the method may include: S1: Obtain the target force value of the motor during landing, wherein the target force value is a preset value; S2: Obtain the operating data of the motor, the operating data including at least speed data and current data; S3: Design a finite-time state observer to estimate the external force value of the motor during landing in the current state based on the motor's operating data; S4: When the error between the external force value and the target force value is not lower than a preset threshold, adjust the motor's operating data according to the error so that the external force value received by the motor during landing is close to the target force value; S5: Repeat steps S2-S4 according to the preset time step. When the error between the external force value and the target force value is less than the preset threshold, maintain the current operating parameters until the motor lands.

[0026] An electric motor can be understood as an electromagnetic device that converts or transmits electrical energy based on the law of electromagnetic induction. It is widely used in engineering machinery, such as high-precision positioning platforms, image stabilization systems, precision medical equipment, and flexible robots. Voice coil motors, for example, are characterized by high response, high precision, frictionlessness, and no cogging effect, and are widely used in precision positioning, autofocus, and tactile feedback. This specification's embodiments first design a finite-time state observer to accurately estimate the external force acting on the motor during its movement. In the motor control process, this allows for real-time or periodic adjustments to the motor's operating data based on a comparison between the estimated external force value and the target force value. This ensures that the external force acting on the motor gradually approaches the target force value, enabling high-precision control during the motor's soft landing process. This improves the workpiece's processing reliability and the stability of the motor control. The target force value can be the processing accuracy or requirement of the target workpiece.

[0027] In this process, the motor contacts the target workpiece through the terminal and completes the processing of the target workpiece. The motor terminal can be understood as the end effector, which is the contact element between the motor and the workpiece and is used to process the workpiece. Different types of end effectors can be configured according to the material type of different target workpieces and processing requirements, thereby expanding the application scenarios and production adaptability of the motor.

[0028] The embodiments in this specification periodically acquire the operating data of the motor during operation. Combined with the designed finite-time state observer, the external forces acting on the motor can be estimated in a timely manner, which facilitates timely adjustment of the motor operating data and improves the accuracy and timeliness of motor control.

[0029] The execution logic of the finite-time state observer is as follows: The speed and current data of the motor are collected at preset time steps; Based on the speed data at the current acquisition time and the observed speed at the previous acquisition time, the speed error at the current acquisition time is determined. The observed speed is a state variable obtained by accumulating and integrating the motion data of the motor using a nonlinear feedback gain algorithm. The initial value of the observed speed is 0. Based on the velocity error and nonlinear observation acceleration gain at the current acquisition time, the derivative of the observation perturbation acceleration at the acquisition time is updated. The observed perturbation acceleration at the current acquisition time is updated based on the derivative of the observed perturbation acceleration at the current acquisition time and the observed perturbation acceleration at the previous acquisition time. Based on the velocity error, current data, observed disturbance acceleration, and nonlinear observed velocity gain at the current acquisition time, the observed velocity derivative at the current acquisition time is updated. Based on the derivative of the observation velocity at the current acquisition time and the observation velocity at the previous acquisition time, the observation velocity at the current acquisition time is updated to be used for estimating the external force value at the next acquisition time. Based on the observed disturbance acceleration at the current acquisition time, the external force value experienced by the motor during landing is estimated.

[0030] In essence, the observer in this embodiment uses position and velocity as state variables for estimating external forces, and uses historical data (such as the previous acquisition node) as the basis for updating subsequent operating data. It achieves finite-time convergence by utilizing nonlinear feedback gain. Initially, the observed velocity is zero. The observer updates the observed disturbance acceleration and observed velocity in the observer by combining the actual speed data and current data of the motor, and estimates the external force value of the motor in each acquisition cycle. This achieves rapid convergence estimation of the external force on the motor, greatly improving the convergence speed and observation accuracy.

[0031] In the embodiments of this specification, different acquisition cycles (i.e., preset time steps) can be set according to different workpiece processing requirements and motor configuration parameters. Optionally, it can be 1ms-5ms, such as 1ms, 2ms, or 3ms. The shorter the time, the faster the convergence speed of the observer and the more precise the control of the motor, but the higher the performance requirements of the motor and the greater the computational resources required. Therefore, it is necessary to select an appropriate acquisition cycle according to actual needs.

[0032] Based on the execution logic of the finite-time state observer provided above, this specification also provides an implementation method for the finite-time observer, as shown in the following formula:

[0033] in,e For speed error; v The velocity data is obtained through the encoder position derivative; z2 The observed velocity is initially set to 0. z3 To observe the acceleration of the disturbance, the initial value is 0; dz2 for z2 The derivative of dz3 for z3 The derivative of k2 and k3 For nonlinear observer gain; dt For time step; I This is the motor's current data; Mn It is the ratio of the moving mass to the torque constant; sign (e) The sign function for velocity error; abs(e) This represents the absolute value of the speed error. F est To estimate the external force acting on the motor.

[0034] By utilizing the difference between the actual speed and the observed speed, the observation speed of the motor is updated integrally by performing a fractional power feedback gain on the observed disturbance acceleration during the motor's motion. This allows the entire observer to achieve a nonlinear gain effect. Simultaneously, by combining the motor's current speed and torque constant, the periodic estimation of the external force on the motor is achieved, which is consistent with the data acquisition frequency (time step). This enables real-time and rapid convergence of the estimation of the external force on the motor, avoiding the lag problem of traditional observers.

[0035] The torque constant is a property of the motor's own operating performance. In the embodiments of this specification, it can be a fixed value, or the torque constant can change as the operating state of the motor is adjusted.

[0036] In the embodiments of this specification, the target force value can be the standard for the processing requirements of the target workpiece, that is, the contact force between the motor terminal and the target workpiece when the processing requirements are met, representing the magnitude of the force applied by the motor terminal to the target workpiece. Therefore, during the motor control process, the external force on the motor (which should represent the reaction force between the motor and the target workpiece) should be gradually made closer to the target force value to ensure the processing requirements of the target workpiece are met. Specifically, the motor operating parameters can be adaptively adjusted according to the comparison between the estimated external force value and the target force value to make the external force value gradually approach the target force value. Specifically: When the error between the external force value and the target force value is not lower than a preset threshold, the operating data of the motor is adjusted according to the error, including: Based on the error between the external force value and the target force value, the speed data of the motor is updated using a proportional-integral algorithm. Adjust the current data of the motor to obtain updated speed data of the motor.

[0037] This can be understood as follows: In order to achieve adaptive adjustment of motor operating data, when the external force value has not yet reached the target force value, the motor speed data can be updated using a proportional-integral algorithm based on the error between the estimated external force value and the target force value each time. This speed data is generally achieved by controlling the motor's operating current. In this way, based on the motor operating data collected based on the time step, the estimated external force value is updated, and then the motor operating data is adjusted based on the relationship between the external force value and the target force value, thereby achieving cyclic adaptive control of the motor, achieving the effect of continuous control, avoiding mechanical adjustments, and improving the motor control capability and accuracy.

[0038] The preset threshold can be the precision requirement for processing the target workpiece. The smaller the preset threshold, the higher the processing requirement, and vice versa. Therefore, the preset threshold can be determined according to the type of the target workpiece.

[0039] This specification describes an embodiment that uses a finite-time state observer to achieve rapid and accurate estimation of external forces. By establishing an observer model that includes three state variables—position, velocity, and external force—and utilizing nonlinear feedback gain to achieve finite-time convergence, it significantly improves convergence speed and observation accuracy compared to traditional linear observers. The observer employs a fractional-power feedback gain structure, ensuring convergence within a finite time and exhibiting strong suppression capabilities against external disturbances.

[0040] Specifically, the solution provided in this specification has significant advantages over traditional lookup table methods and conventional observers in soft landing control: 1. No need for massive amounts of test data: Unlike the table lookup method, it does not require the collection of a large amount of data in advance, significantly saving time and implementation costs. 2. Fast convergence speed: It converges rapidly within a finite time, with an observation delay of less than 1ms, avoiding the lag problem of traditional observers. 3. Strong adaptability: It can adapt to various complex nonlinear external forces and dynamically changing load conditions, and is robust to environmental disturbances. 4. Excellent real-time performance: Millisecond-level response to changes in external forces, meeting the demands of high-cycle production. 5. High versatility: The same algorithm is applicable to various working conditions and products, eliminating the need for redesign for different scenarios. 6. Low resource consumption: The algorithm is lightweight, eliminating the need to store large lookup tables and reducing hardware costs. The comparison process is shown in Table 1 below. Table 1. Advantages of this solution compared to existing technologies

[0041] In the embodiments of this specification, based on the estimated external force, an adaptive speed control algorithm based on external force feedback is used to update the approach speed between the motor end and the workpiece. The speed data update of the motor in each acquisition cycle can be expressed by the following formula:

[0042] Where v is the approach speed, i.e. the speed data of the updated motor; kp is the proportional coefficient, which is used to linearly amplify the current error, enabling a fast response, which can improve the system response speed and reduce the early steady-state error; ki is the integral coefficient, which is used to amplify the accumulated value of the error, "accounting for" past errors, pushing the error to zero, and eliminating steady-state error (i.e., the case where the long-term error is not zero).

[0043] It should be noted that when ki is too large, it can easily lead to slow system response or oscillation or even instability (integral saturation); Ftarget is the target holding force; Fest is the estimated external force on the motor. Among them, kp and ki are set according to the actual situation, and Ftarget is set according to the processing requirements of the target workpiece.

[0044] This can be understood as follows: a finite-time state observer can obtain the external force received by the motor in real time, and update the motor's approach speed based on this external force. This enables adaptive adjustment of the approach speed at the motor's end effector (i.e., the terminal), converting force errors into speed commands. This achieves adaptive adjustment where "the greater the force, the smaller the speed; the smaller the force, the greater the speed," ensuring the accuracy of force control during the contact process. When the contact force approaches the target value, the speed automatically decreases to achieve a smooth transition; when external disturbances cause force changes, the speed automatically adjusts to maintain the target force value.

[0045] It should be noted that by designing a finite-time state observer, the motor operation data can be adjusted and updated throughout the entire motor landing process. However, in the early stages of motor operation, when there is a certain distance between the motor and the target workpiece or the contact force is still very small, performing adaptive adjustment of the motor operation data by the observer at this time will increase the computational cost and resources, reduce the motor processing efficiency, and the adjustment effect will not be ideal. Therefore, a pre-landing step for the motor can be set to ensure that the motor reaches the pre-landing conditions in the fastest time or with the fastest efficiency, and then switch to using the observer to refine the motor operation data in a timely manner. Specifically, the motor operation data also includes terminal position data, and before step S1, the following steps are also included: S01: Pre-landing step, the motor is controlled by a preset current to complete the pre-landing, and the terminal position data of the motor at the pre-landing time is obtained. The external force value at the pre-landing time is less than the target force value. The distance between the terminal position data and the initial position of the motor is calculated, and the motion state of the motor is divided into high-speed approach stage, transition stage, force-controlled approach stage and final positioning stage based on the distance.

[0046] In other words, by dividing the entire operating state of the motor into multiple stages based on the distance between the motor's terminal position data and its initial position, different control logic can be executed in different stages. In the high-speed approach stage, the motor can be controlled at a faster speed to quickly reach the transition state stage, and then rapidly switch to the force-controlled approach stage. This allows the observer to update the motor's operating data in this stage, achieving dynamic control of the motor. The different stage divisions can be determined based on the relationship between the terminal position data and the motor's initial position, for example: When the distance between the terminal position data and the initial position of the motor is greater than a preset interval, the distance is divided into a high-speed interval, a transition interval, and a force-controlled approach interval. The motor is controlled to enter the high-speed approach phase at full speed, and the motor speed data is reduced according to a preset rule. When the speed data is lower than the first preset value and the position data of the motor enters the transition range, the current running data is maintained to control the motor to enter the force-controlled approach range, and step S1 is executed with the current running data.

[0047] The different intervals and divisions mentioned above correspond to different stages. The distance traveled by the motor is used as the basis for switching between different stages. In specific implementation, after the target workpiece is assembled in place, the motor's working logic is configured according to processing requirements, and the motor is started and controlled. During the motor's movement, based on the distance traveled by the terminal, the motor's operating state is divided into a high-speed approach stage, a transition stage, a force-controlled approach stage, and a final positioning stage. Different stages correspond to different distance intervals. For example, the interval corresponding to the high-speed approach stage is the initial distance interval, which can be 0-2cm from the initial position of the motor. The interval corresponding to the transition stage is the subsequent second distance interval, which is 0-2cm from the initial position of the motor. The positioning distance can be 2-2.5cm, and so on until the interval corresponding to the final positioning stage is reached. The high-speed approach stage is the control strategy during the initial movement of the motor, aiming to make the terminal approach the target workpiece as quickly as possible for a soft landing. At this time, it can move at a relatively high speed, such as full speed, and reduce the motor speed data according to preset rules. When the speed data falls below a first preset value and the motor position data enters the transition interval, the motor needs to be adjusted to switch to the transition state stage. In this stage, the motor is set to hold the current value as the reference force for the force-controlled approach stage, completing a smooth transition from speed control to force control, maintaining the current operating data to control the motor to enter the force-controlled approach interval. It should be noted that this stage is short in duration but crucial for preventing shocks during mode switching. After entering the force-controlled approach interval from the transition interval, motor operating data can be collected, and external force values ​​can be estimated based on a pre-designed finite-time state observer, thereby achieving automatic takeover and adaptive adjustment of the motor operating data until a successful soft landing.

[0048] The full speed can be set according to the distance between the target workpiece and the terminal, as well as the performance of the motor itself. The specific value is not limited. In addition, the first preset value is also to improve the reliability of the motor control strategy switching. During the high-speed approach phase, it can move at the initial speed and gradually reduce the speed until it is lower than the first preset value to avoid the speed being too fast when approaching the target workpiece, so as to improve the control capability in the transition phase.

[0049] The system then switches to the force-controlled approach phase, the core of the soft landing process. This phase enables smooth and efficient contact and positioning between the terminal and the target workpiece, improving the reliability and efficiency of workpiece processing and further increasing the workpiece yield. An adaptive force control is achieved by using a finite-time state observer to estimate the external force in real time and dynamically adjusting the approach speed based on the difference between the target force and the actual force.

[0050] During the force control approach phase, it is necessary to monitor in real time the relationship between the external force value and the target force value on the motor, as well as whether the motor terminal has entered the final positioning phase, in order to take over and adjust the motor's working logic. Specifically: When the error between the external force value and the target force value is less than a preset threshold, and the position data of the motor is consistent with the terminal position data of the motor, the motor completes landing and enters the final positioning stage.

[0051] In another embodiment of this specification, the approach speed can be precisely controlled using a finite-time state observer and adaptive adjustment of the approach speed, ensuring a smooth establishment of the contact force while avoiding the oscillation and instability problems that are prone to occur in traditional force control. To accurately determine whether the contact condition has been met, i.e., the termination condition of the force-controlled approach phase, can be: When satisfied If so, it is determined that the motor has successfully achieved a soft landing during the force-controlled approach phase.

[0052] in, F threshold Force error threshold v threshold For speed threshold, pos min This is the minimum position threshold.

[0053] In other words, the system only determines that a soft landing is complete and proceeds to the next stage when the force error is less than a threshold (indicating stable contact force), the velocity is less than a threshold (indicating dynamic stability), and the position exceeds a safety threshold (indicating that contact has indeed occurred, i.e., the final positioning stage has been reached). This multi-condition judgment effectively avoids false completion situations and improves control reliability.

[0054] In the embodiments described in this specification, after the motor successfully soft-landes during the force-controlled approach phase, the position between the motor terminal and the target workpiece is acquired in real time. When the position reaches the maximum position limit, the motor is moved to the final positioning phase. That is, when the terminal and the target workpiece meet the conditions for soft landing, a stable contact force needs to be maintained, and the position continuously monitored to ensure a safe and stable contact state. After completing the entire contact process, the motor remains stable in the final position, continuously monitoring for possible positional deviations or changes in contact force to ensure long-term stability.

[0055] The essence of soft landing control is to achieve smooth contact between the motor and the target object, avoiding impact forces while ensuring stable contact force. The embodiments in this specification estimate external forces in real time and dynamically adjust the approach speed to maintain an ideal contact force curve before and after contact, achieving a truly "soft" landing.

[0056] This specification provides an embodiment of a motor soft landing control method based on a finite-time state observer. This method estimates external disturbance forces in real time using a finite-time state observer and achieves soft landing control based on a multi-stage control strategy. The system dynamically adjusts the approach speed according to the difference between the target holding force and the actual estimated external force, achieving a force-adaptive soft landing process. Compared to the traditional lookup table method, this technology does not require a large amount of pre-test data, saving time and offering strong versatility. Compared to conventional observers, the convergence time is less than 1 millisecond, with almost no lag, meeting the demands of high-cycle production. The system does not require a dedicated force sensor; precise force control can be achieved using only motor current and position information, significantly improving product quality and reducing costs.

[0057] In another embodiment of the specification, to improve the reliability of motor monitoring and the safety of operation, the following method may also be included: The operating status of the motor is acquired in real time, including load data, moving resistance data of the motor end actuator, current change data, and motor temperature data. When the operating status indicates that the motor is in an abnormal state, the motor end effector is controlled to move to a preset position to avoid damaging the workpiece.

[0058] In other words, by adding detection steps to the environment where faults may occur during the operation of the motor, the actual status of the motor during operation can be detected in real time, risks can be monitored and avoided in advance, and the safety of equipment and workpieces can be ensured. For example, if blockage, overload or other abnormal conditions are detected, the system will immediately execute the error recovery procedure, reset and move to a safe position to avoid damage to equipment or products.

[0059] The solutions provided in the embodiments of this specification only use the current and position feedback built into the motor, eliminating the need for additional force sensors, thus reducing system cost and complexity. They employ fractional power feedback gain (nonlinear observer) to achieve finite-time convergence, significantly improving observation speed. The approach speed is dynamically adjusted based on the real-time estimated external force, adapting to different materials and contact conditions. From high-speed approach to fine force control, and then to stable holding, the entire process achieves optimal control.

[0060] Based on the motor soft landing control method based on a finite-time state observer provided above, this specification also provides a motor soft landing control system based on a finite-time state observer, such as... Figure 2 The diagram shown is a schematic of the system framework. The system includes a motor 10 and a position sensor 20. The position sensor is used to collect the distance between the motor terminal 12 and the initial position of the motor. The motor 10 includes a controller 11 configured to execute the motor soft landing control method based on a finite-time state observer as described above.

[0061] This embodiment provides a motor. The motor includes a processor, a memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used for communication with external terminals via a network connection.

[0062] In one embodiment, an electric motor is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0063] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0064] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0065] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0066] It should also be understood that, in the embodiments herein, the term "and / or" is merely a description of the relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following associated objects have an "or" relationship.

[0067] 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, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. 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 document.

[0068] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0069] In the embodiments provided herein, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of 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 couplings or direct couplings or communication connections shown or discussed may be indirect couplings or communication connections through some interfaces, devices, or units, or they may be electrical, mechanical, or other forms of connection.

[0070] 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 the embodiments described herein, depending on actual needs.

[0071] This document uses specific embodiments to illustrate the principles and implementation methods of this document. The descriptions of the embodiments above are only for the purpose of helping to understand the methods and core ideas of this document. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this document. Therefore, the content of this specification should not be construed as a limitation of this document.

Claims

1. A motor soft landing control method based on a finite-time state observer, characterized in that, The method includes: S1: Obtain the target force value of the motor during landing, wherein the target force value is a preset value; S2: Obtain the operating data of the motor, the operating data including at least speed data and current data; S3: Design a finite-time state observer to estimate the external force value of the motor during landing in the current state based on the motor's operating data; S4: When the error between the external force value and the target force value is not lower than a preset threshold, adjust the motor's operating data according to the error so that the external force value received by the motor during landing is close to the target force value; S5: Repeat steps S2-S4 according to the preset time step. When the error between the external force value and the target force value is less than the preset threshold, maintain the current operating parameters until the motor lands.

2. The motor soft landing control method based on a finite-time state observer according to claim 1, characterized in that, Design a finite-time state observer to estimate the external forces acting on the motor during landing in its current state based on the motor's operating data, including: The speed and current data of the motor are collected at preset time steps; Based on the speed data at the current acquisition time and the observed speed at the previous acquisition time, the speed error at the current acquisition time is determined. The observed speed is a state variable obtained by accumulating and integrating the motion data of the motor using a nonlinear feedback gain algorithm. The initial value of the observed speed is 0. Based on the velocity error and nonlinear observation acceleration gain at the current acquisition time, the derivative of the observation perturbation acceleration at the acquisition time is updated. The observed perturbation acceleration at the current acquisition time is updated based on the derivative of the observed perturbation acceleration at the current acquisition time and the observed perturbation acceleration at the previous acquisition time. Based on the velocity error, current data, observed disturbance acceleration, and nonlinear observed velocity gain at the current acquisition time, the observed velocity derivative at the current acquisition time is updated. Based on the derivative of the observation velocity at the current acquisition time and the observation velocity at the previous acquisition time, the observation velocity at the current acquisition time is updated to be used for estimating the external force value at the next acquisition time. Based on the observed disturbance acceleration at the current acquisition time, the external force value experienced by the motor during landing is estimated.

3. The motor soft landing control method based on a finite-time state observer according to claim 1, characterized in that, The finite-time state observer estimates the external force value using the following formula: in, e For speed error; v The velocity data is obtained through the encoder position derivative; z2 The observed velocity is initially set to 0. z3 To observe the acceleration of the disturbance, the initial value is 0; dz2 for z2 The derivative, dz3 for z3 The derivative, k2 and k3 For nonlinear observer gain; dt For time step; I This is the motor's current data; Mn It is the ratio of the moving mass to the torque constant; sign (e) The sign function for velocity error; abs(e) This is the absolute value of the speed error. F est To estimate the external force acting on the motor.

4. The motor soft landing control method based on a finite-time state observer according to claim 1, characterized in that, When the error between the external force value and the target force value is not lower than a preset threshold, the operating data of the motor is adjusted according to the error, including: Based on the error between the external force value and the target force value, the speed data of the motor is updated using a proportional-integral algorithm. Adjust the current data of the motor to obtain updated speed data of the motor.

5. The motor soft landing control method based on a finite-time state observer according to claim 4, characterized in that, The motor speed data is updated using the following formula: in, v For speed data; k p This is the proportionality coefficient; k i Integral coefficient ；F target The target force value; F est To estimate the external force value of the obtained motor.

6. The motor soft landing control method based on a finite-time state observer according to claim 1, characterized in that, The motor's operating data also includes terminal position data, and before step S1, it also includes: S01: Pre-landing step, the motor is controlled by a preset current to complete the pre-landing, and the terminal position data of the motor at the pre-landing time is obtained. The external force value at the pre-landing time is less than the target force value. The distance between the terminal position data and the initial position of the motor is calculated, and the motion state of the motor is divided into high-speed approach stage, transition stage, force-controlled approach stage and final positioning stage based on the distance.

7. The motor soft landing control method based on a finite-time state observer according to claim 6, characterized in that, The method further includes: When the distance between the terminal position data and the initial position of the motor is greater than a preset interval, the distance is divided into a high-speed interval, a transition interval, and a force-controlled approach interval. The motor is controlled to enter the high-speed approach phase at full speed, and the motor speed data is reduced according to a preset rule. When the speed data is lower than the first preset value and the position data of the motor enters the transition range, the current running data is maintained to control the motor to enter the force-controlled approach range, and step S1 is executed with the current running data.

8. The motor soft landing control method based on a finite-time state observer according to claim 7, characterized in that, When the error between the external force value and the target force value is less than a preset threshold, and the position data of the motor is consistent with the terminal position data of the motor, the motor completes landing and enters the final positioning stage.

9. A motor soft landing control system based on a finite-time state observer, characterized in that, The system includes a motor and a target workpiece; The motor includes a controller configured to perform the motor soft landing control method based on a finite-time state observer as described in any one of claims 1-8.

10. An electric motor, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the motor soft landing control method based on a finite-time state observer as described in any one of claims 1-8.

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