Dynamic pressure feedback adjustment method and system for a bidirectional self-locking positioning device

Abstract

The application discloses a dynamic pressure feedback adjustment method and system of a bidirectional self-locking positioning device, and relates to the field of positioning device adjustment. First, the control target set by a user is acquired, and the current position, pressure and speed are collected in real time. The information is input into a control state machine decision engine, which intelligently judges and switches the control mode according to the current state. Based on the current control mode, a feedforward compensation instruction is calculated to pre-compensate the known nonlinear effect, a feedback control instruction is calculated to correct the error in real time, and a micro-vibration instruction is calculated to effectively overcome the static friction force and avoid the stick-slip phenomenon. Finally, the three types of instructions are superimposed to generate a driving instruction, and the device action is accurately controlled. This method can effectively avoid the error accumulation and overshoot of the traditional PID control in the dead zone, realize high-precision and high-stability pressure control of the bidirectional self-locking positioning device, and thus guarantee the reliability and safety of the operation.

Description

Technical Field

[0001] This application relates to the field of positioning device adjustment, and more specifically, to a dynamic pressure feedback adjustment method and system for a bidirectional self-locking positioning device. Background Technology

[0002] In fields such as precision manufacturing, medical surgery, and collaborative robotics, bidirectional self-locking devices play a crucial role in scenarios requiring precise and stable force application due to their unique self-locking characteristics. However, this self-locking characteristic also brings unique control challenges, especially the dead zone effect and nonlinear friction problems in the critical region, making the achievement of high-precision and high-stability pressure control an extremely challenging task. Control errors can lead to minor issues such as workpiece damage (e.g., pressure overshoot crushing fragile items) or task failure (e.g., poor contact), and in severe cases, even safety accidents. Therefore, developing a dynamic pressure feedback regulation scheme that can effectively address these challenges is of paramount importance for improving product reliability and quality.

[0003] In existing technologies, pressure control for bidirectional self-locking devices typically employs traditional control algorithms such as PID (Proportional-Integral-Derivative). However, these solutions often exhibit significant limitations when faced with the viscous-slip phenomenon unique to bidirectional self-locking devices. When the controller issues a small movement command to increase pressure, the torque generated by the motor may be insufficient to overcome the static friction of the lead screw and nut pair, causing the system to enter a dead zone where the pressure sensor reading remains almost unchanged, and the controller continuously accumulates errors. Once the static friction is overcome, the system immediately enters a dynamic friction state, and the previously accumulated energy is released instantaneously, causing the gripper to produce a jump displacement far exceeding expectations. The pressure may surge from below to above the target value in an instant, causing overshoot and even damaging the clamped object. Furthermore, the delay and nonlinear relationship between motor rotation (input) and pressure change (final output) further exacerbates the complexity of control, making it difficult for traditional solutions to achieve precise, real-time dynamic adjustment of pressure.

[0004] Therefore, there is an urgent need for a new solution that can achieve stable pressure feedback regulation of a bidirectional self-locking positioning device. Summary of the Invention

[0005] Based on the deficiencies in the aforementioned prior art, according to one aspect of this application, a dynamic pressure feedback adjustment method for a bidirectional self-locking positioning device is provided, comprising: acquiring a control target input by a user, the control target including target pressure, pressure tolerance, contact force threshold, pre-contact position, and final position; acquiring current pressure, current position, and current speed collected by a pressure sensor, a position sensor, and a speed sensor; inputting the current position, current pressure, and control target into a control state machine decision engine to obtain a current control mode; calculating a feedforward compensation command, a feedback control command, and a micro-vibration command based on the current control mode; and superimposing the feedforward compensation command, the feedback control command, and the micro-vibration command to obtain a final drive command.

[0006] According to another aspect of this application, a dynamic pressure feedback adjustment system for a bidirectional self-locking positioning device is provided, comprising: a control target acquisition module for acquiring a control target input by a user, the control target including target pressure, pressure tolerance, contact force threshold, pre-contact position, and final position; a sensor parameter acquisition module for acquiring current pressure, current position, and current velocity collected by a pressure sensor, a position sensor, and a velocity sensor; a control state machine decision module for inputting the current position, current pressure, and control target into a control state machine decision engine to obtain a current control mode; an instruction calculation module for calculating a feedforward compensation instruction, a feedback control instruction, and a micro-vibration instruction based on the current control mode; and a drive instruction generation module for superimposing the feedforward compensation instruction, the feedback control instruction, and the micro-vibration instruction to obtain a final drive instruction.

[0007] Compared with existing technologies, this application provides a dynamic pressure feedback regulation method and system for a bidirectional self-locking device. It aims to solve the pressure control problems caused by dead zone effect, nonlinear friction, and asynchrony between drive and sensing in the critical zone of the bidirectional self-locking device by introducing an intelligent control state machine and multimodal command superposition. Specifically, the system first acquires user-set control targets such as target pressure, tolerance, and contact force threshold, and collects the current position, pressure, and velocity in real time. This information is input into the control state machine decision engine, which intelligently judges and switches control modes based on the current state, for example, switching from pre-contact mode to precise pressure control mode. Based on the current control mode, the system calculates feedforward compensation commands to pre-counteract known nonlinear effects, feedback control commands to correct errors in real time, and micro-vibration commands to effectively overcome static friction and avoid stick-slip phenomena. Finally, these three types of commands are superimposed to generate drive commands for precise control of the device's action. This dynamic and adaptive regulation method effectively avoids error accumulation and overshoot in the dead zone of traditional PID control, achieving high-precision and high-stability pressure control of the bidirectional self-locking device, thereby ensuring operational reliability and safety. Attached Figure Description

[0008] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of this application in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0009] Figure 1 This is a flowchart of a dynamic pressure feedback adjustment method for a bidirectional self-locking device according to an embodiment of this application.

[0010] Figure 2 This is a schematic diagram of the data flow of the dynamic pressure feedback adjustment method of the bidirectional self-locking device according to an embodiment of this application.

[0011] Figure 3 This is a flowchart of step S4 in the dynamic pressure feedback adjustment method of the bidirectional self-locking device according to an embodiment of this application.

[0012] Figure 4 This is a block diagram of the dynamic pressure feedback adjustment system of the bidirectional self-locking device according to an embodiment of this application. Detailed Implementation

[0013] 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.

[0014] In view of the technical defects exposed by the above background technology, this application proposes a dynamic pressure feedback adjustment method for a bidirectional self-locking positioning device. Figure 1 This is a flowchart of a dynamic pressure feedback adjustment method for a bidirectional self-locking device according to an embodiment of this application. Figure 2 This is a schematic diagram of the data flow in the dynamic pressure feedback adjustment method of the bidirectional self-locking device according to an embodiment of this application. Figure 1 and Figure 2As shown, the dynamic pressure feedback adjustment method of the bidirectional self-locking positioning device according to an embodiment of this application includes: S1, acquiring a control target input by a user, the control target including target pressure, pressure tolerance, contact force threshold, pre-contact position, and final position; S2, acquiring the current pressure, current position, and current speed collected by a pressure sensor, a position sensor, and a speed sensor; S3, inputting the current position, current pressure, and control target into a control state machine decision engine to obtain a current control mode; S4, calculating a feedforward compensation command, a feedback control command, and a micro-vibration command based on the current control mode; S5, superimposing the feedforward compensation command, the feedback control command, and the micro-vibration command to obtain a final drive command.

[0015] In step S1, the control objectives input by the user are obtained. These objectives include target pressure, pressure tolerance, contact force threshold, pre-contact position, and final position. It should be understood that in applications such as precision manufacturing and medical surgery, the accuracy and safety requirements for parameters such as clamping force and contact position are extremely high. Without clear control objectives, the device will be unable to determine when the expected state is reached or when adjustments are needed, and may even damage the workpiece or cause safety accidents due to blind operation. For example, when clamping fragile items, strict target pressure and pressure tolerance must be set to avoid overshoot and crushing; during precision assembly, the pre-contact position and contact force threshold ensure that the device decelerates before contact and applies the initial force in a controlled manner. These control objectives provide the basis for subsequent control state machine decisions and instruction calculations, enabling the device to adopt the most appropriate control strategy at different stages according to specific task requirements. This effectively solves the problems mentioned in the background art, such as dead zone effect, nonlinear friction, and overshoot, achieving high-precision and high-stability dynamic pressure feedback regulation.

[0016] In this embodiment, step S1 is executed as follows: it can be implemented through a human-machine interface or a preset program file. For example, the user can input or select these parameters on a graphical user interface via a touchscreen, keyboard, or host computer software. Specifically, the target pressure refers to the desired force value that the device ultimately needs to apply. For example, when clamping a glass test tube, the user may set the target pressure to 5.0N. Pressure tolerance refers to the allowable deviation range of the target pressure. For example, setting it to ±0.1N means that the final pressure should be between 4.9N and 5.1N; exceeding this range is considered a control failure or a risk. The contact force threshold refers to the minimum force value at which the device determines contact when it approaches an object and makes initial contact. This parameter is used to identify the object in the pre-contact stage and trigger the switch from rapid approach to pre-contact detection mode. For example, setting it to 0.05N means that when the pressure sensor reading first exceeds this value, it indicates that the device has made contact with the object. The pre-contact position refers to the position point at which the device switches from rapid approach mode to pre-contact detection mode when approaching the target object. This position is set very close to the target object's surface but before contact, used to decelerate in advance and prepare for fine contact. For example, it might be set to a position 10 mm from the target object's surface. The home position refers to the initial safe position the device is in when completing a task or starting up. This position is the device's mechanical zero point or a preset standby position, used to ensure the device's safety and repeatability in non-operating states. For example, it might be set to a position where the device is fully open and far from the work area. These parameters are presented on the user interface as numerical input boxes or drop-down menus. After user input, the data is transmitted via communication interfaces such as serial ports or Ethernet to the device's controller memory for storage, to be called by subsequent control algorithms. For example, in a scenario involving clamping a glass test tube, the user might input: target pressure = 5.0 N, pressure tolerance = 0.1 N, contact force threshold = 0.05 N, pre-contact position = 10 mm, home position = 0 mm.

[0017] In step S2, the current pressure, current position, and current velocity are acquired by the pressure sensor, position sensor, and velocity sensor. Correspondingly, the dead zone effect, nonlinear friction, and asynchrony between drive and sensing mentioned in the background art all require the controller to accurately sense changes in the physical quantities of the device. Current position information is the basis for determining whether the device has reached a preset key point (such as a pre-contact position or a final position), and is also the basis for calculating displacement and velocity; current pressure information is the core of pressure feedback control, directly reflecting the force applied by the device to the object, and is crucial for avoiding overshoot crushing or poor contact; while current velocity information reflects the movement trend and speed of the device, and is of guiding significance for feedforward compensation and avoiding viscous-slip phenomena. Without these real-time and accurate physical quantity data, the controller will be unable to perform effective state judgment, error calculation, and command generation, thus failing to achieve refined and dynamic control of the device, and unable to effectively solve the control problems in the prior art. Therefore, real-time and accurate acquisition of these sensor data is a key prerequisite for realizing the dynamic pressure feedback regulation method of this invention.

[0018] In this embodiment, step S2 is executed as follows: it is achieved through various sensors integrated into the bidirectional self-locking device. Specifically, the current pressure is acquired through a high-precision pressure sensor. This pressure sensor is installed at the clamping end of the bidirectional self-locking device or at a location in direct contact with the clamped object. For example, a piezoresistive or piezoelectric force sensor with a range of 0-10N and an accuracy of 0.01N can be selected. The sensor converts the sensed pressure into an analog electrical signal, which is then converted into a digital signal by an analog-to-digital converter (ADC) after signal conditioning circuitry such as amplification and filtering. This digital signal is transmitted to the controller in real time via a high-speed data bus, such as SPI, I2C, or CAN bus. For example, when the device clamps a glass test tube, the pressure sensor continuously outputs the current pressure, such as 4.85N.

[0019] The current position is acquired using a position sensor. This sensor may be a high-resolution encoder or a linear displacement sensor. The encoder is directly mounted on the drive motor shaft or mechanically connected to the moving parts of the device, and is used to measure the absolute or relative position of the device. For example, an incremental encoder with a resolution of 10,000 pulses / revolution can be selected, and the current position of the device is accurately calculated by counting its output pulse signals. For linear displacement sensors, such as optical scales or magnetostrictive displacement sensors, the opening and closing distance of the grippers is directly measured. The sensor converts the position information into a digital signal and transmits it to the controller at a preset sampling frequency, such as 1000 Hz. For example, when the device grippers are in a certain position, the position sensor will output its current position coordinates, such as 15 mm from the home position.

[0020] The current speed is obtained through a speed sensor. This sensor is acquired by the controller after receiving continuous position data, and by performing real-time calculations and estimations on this data. The controller estimates the speed by performing differential operations on the position data. For example, a first-order differential method can be used: Current speed = Current position - Previous sampling position / Sampling period, where the sampling period is, for example, every 1 ms. This speed calculated based on position data, after appropriate filtering such as low-pass filtering, can provide smooth and accurate speed information. For example, when the gripper moves at a speed of 0.5 mm / s, the speed sensor will output this estimated current speed.

[0021] In step S3, the current position, current pressure, and control target are input into the control state machine decision engine to obtain the current control mode. It should be understood that the physical state and control requirements of the bidirectional self-locking device are dynamically changing during task execution. From moving away from the target object to precise clamping, and then to holding or retracting, the requirements for control accuracy, speed, and force are drastically different at each stage. For example, efficiency is the primary consideration during the rapid approach stage; while after contact with the object, extremely high force control accuracy is required to avoid damage. The dead zone effect and nonlinear friction problems mentioned in the background art also exhibit different behaviors and corresponding strategies at different stages. Therefore, a single control algorithm is difficult to adapt to all working conditions. To address this, this application introduces a control state machine decision engine, which can intelligently determine the current stage of the device based on real-time sensor data and preset user control targets, and dynamically switch to the control mode most suitable for that stage. This phased, adaptive control strategy effectively avoids the limitations of traditional control under complex working conditions, ensuring that the device maintains optimal performance throughout the entire operation, thereby solving the high-precision, high-stability pressure control problem proposed in the background art.

[0022] In this embodiment, step S3 is executed as follows: It is worth noting that the control state machine decision engine is a software module based on a finite state machine. Its core architecture consists of a series of predefined control modes (states) and state transition rules. In this embodiment, the current control modes include: rapid approach mode, pre-contact detection mode, self-locking mode, fine pressure regulation mode, and retreat mode. The state transition rules are based on the current position, current pressure, and the control target input by the user. The control state machine decision engine can be implemented using a lookup table method or conditional judgment statements. For example, a simplified state transition logic can be expressed as follows: if the current mode is rapid approach mode and the current position ≤ pre-contact position, then switch to pre-contact detection mode; if the current mode is pre-contact detection mode and the current pressure ≥ contact force threshold, then switch to fine pressure regulation mode; if the current mode is fine pressure regulation mode and abs(current pressure - target pressure) ≤ pressure tolerance and duration > 0.5s, then switch to self-locking mode. If the user inputs a retreat command, then switch to retreat mode.

[0023] Specifically, the controller continuously receives current position, current pressure, and current speed data from pressure, position, and speed sensors. Simultaneously, the user-defined control target is stored in the controller's memory. The operating logic of the control state machine decision engine is as follows: The device starts from its home position, for example, 0 mm, at which point the control state machine is in the initial stage of either retreat mode or rapid approach mode. When the device needs to move from its home position to near the target object, the state machine enters rapid approach mode. In this mode, the decision is primarily based on a comparison between the current position and the pre-contact position, for example, 10 mm. For example, if the current position is greater than the pre-contact position and the device is moving towards the target, the rapid approach mode is maintained.

[0024] When the device's current position approaches or reaches the pre-contact position, for example, the current position is 10.5 mm and it is moving towards the target, the state machine switches from rapid approach mode to pre-contact detection mode. In this mode, the main focus is on whether the current pressure reaches the contact force threshold, for example, 0.05 N. For example, if the current pressure is less than 0.05 N, it continues to approach at a lower speed; once the current pressure exceeds 0.05 N for the first time, it indicates that the device has made contact with the object, and the state machine switches to fine pressure adjustment mode. Once the device makes contact with the object and the current pressure exceeds the contact force threshold, for example, the current pressure is 0.06 N, the state machine enters fine pressure adjustment mode. In this mode, the core judgment criterion is the relationship between the current pressure, the target pressure, and the pressure tolerance. If the current pressure is not within the target pressure ± pressure tolerance range, for example, the current pressure is 4.8 N and the target is 5.0 N, the fine pressure adjustment mode is maintained, and precise pressure adjustment is performed.

[0025] When the device's current pressure reaches and stabilizes within the target pressure tolerance range (e.g., current pressure 5.05 N, target 5.0 N, tolerance ±0.1 N), and remains stable for a period of time (e.g., 0.5 seconds), the state machine switches from fine pressure regulation mode to self-locking holding mode. In this mode, the device primarily relies on its self-locking characteristics to maintain the clamping force, with the controller making only minor adjustments to cope with external disturbances or internal drift, ensuring the pressure remains stable within the target range. When the user issues a withdrawal command, the task is completed, or an abnormal situation is detected, the state machine switches to withdrawal mode. In this mode, the device safely returns from its current position to its home position, e.g., 0 mm.

[0026] In step S4, based on the current control mode, feedforward compensation commands, feedback control commands, and micro-vibration commands are calculated. Correspondingly, considering the multiple challenges faced by the dynamic pressure control of the bidirectional self-locking device, including nonlinear friction, dead-zone effects, and inherent system delays, a single control strategy is insufficient to effectively address these complex factors. Therefore, this application decomposes the control commands into three components: feedforward, feedback, and micro-vibration, and selectively calculates and superimposes them according to the current control mode, enabling more precise and robust control of the device. The feedforward compensation command is used to pre-counteract known or predictable nonlinear effects, the feedback control command is used to correct errors in real time, and the micro-vibration command is specifically designed to overcome static friction and avoid stick-slip phenomena. This multi-command synergistic strategy significantly improves control accuracy and stability, effectively solving the control problems mentioned in the background art.

[0027] In this embodiment, Figure 3 This is a flowchart of step S4 in the dynamic pressure feedback adjustment method of the bidirectional self-locking device according to an embodiment of this application. Figure 3 As shown, step S4, based on the current control mode, calculates the feedforward compensation command, feedback control command, and micro-vibration command, including: S41, in response to the current control mode being a rapid approach mode or a fine voltage regulation mode, calculating the feedforward compensation command based on the current speed; S42, in response to the current control mode not being a rapid approach mode or a fine voltage regulation mode, setting the feedforward compensation command to zero. It is understood that the feedforward compensation command is mainly used to counteract speed-related friction, especially viscous friction and Coulomb friction. In rapid approach mode, the device needs to move quickly to approach the target, at which point the speed change is significant, and friction has a large impact on the driving torque. Without feedforward compensation, inaccurate speed control or increased energy consumption may occur. For example, when the gripper approaches rapidly at a speed of 0.02 m / s, friction consumes a portion of the driving force. Feedforward compensation can provide additional driving force in advance to overcome this friction, ensuring that the gripper moves at the expected speed.

[0028] In fine-tuning mode, the device requires high-precision and high-stability pressure adjustment, involving micron-level displacement control. Due to the nonlinear frictional characteristics of the bidirectional self-locking device, even at extremely low speeds, minute speed changes can cause significant fluctuations in frictional force, thus affecting the stability of pressure output. Especially when fine-tuning within the dead zone, changes in frictional force can easily trigger viscous-slip phenomena, leading to discontinuous pressure response or even overshoot. To address this, a feedforward compensation mechanism is introduced to preload the torque required to counteract friction in the early stages of movement, enabling the device to smoothly enter or maintain near the target pressure. For example, when adjusting at a speed of 0.001 m / s near a target pressure of 5.0 N, feedforward compensation can effectively eliminate frictional interference, allowing the feedback controller to focus on precise correction of pressure errors, thereby improving control accuracy and stability. In rapid approach mode, the device needs to move towards the target position at a higher speed, where dynamic friction becomes the main resistance. If relying solely on feedback control, the system must wait for position or speed errors to occur before correction, easily causing response lag, or even failing to reach the set speed due to excessive friction, or overshooting due to inertia when approaching the target. By calculating and superimposing feedforward compensation commands based on the current speed, the controller can pre-apply a driving torque matched to the speed, effectively counteracting dynamic friction resistance and improving the acceleration performance and motion stability of the device. For example, when the device moves from the 15mm position to the 10mm pre-contact point at a speed of 0.02m / s, the feedforward compensation dynamically generates torque commands based on the speed and friction model, overcoming motion resistance in advance, ensuring that the device reaches speed efficiently and decelerates smoothly, significantly improving the system's response speed and control accuracy.

[0029] In the pre-contact detection mode, self-locking mode, and retreat mode, the feedforward compensation command is set to zero because the control target or device motion characteristics in these modes make speed-related friction compensation no longer the primary concern. In the pre-contact detection mode, the device moves at extremely low speeds or intermittently, with the main objective being contact detection. Friction has a relatively small impact, and sensitivity to contact force is emphasized. In the self-locking mode, the device relies primarily on its self-locking characteristics to maintain pressure; ideally, the speed is zero or near zero, and friction is mainly static. Feedforward compensation is less meaningful in this mode and may even introduce unnecessary disturbances. In the retreat mode, the device typically returns to its home position along a preset path and speed. Precise speed control is less critical, and the impact of friction can be effectively handled by other control methods (such as position control). Therefore, selectively applying feedforward compensation can make the control strategy more targeted and efficient.

[0030] In this embodiment, in response to the current control mode being either a rapid approach mode or a fine voltage regulation mode, calculating the feedforward compensation command based on the current speed includes: calculating the feedforward compensation command based on the current speed using the following formula, wherein the formula is: ;in, and Here, are constants, representing Coulomb friction, static friction, characteristic velocity, viscous friction coefficient, and torque conversion coefficient, respectively. At the current speed, To take the absolute value, It is the value of an exponential function with the natural constant e as its base. It is a symbolic function, if ,but ,if ,but ,if ,but , It is friction. The compensation torque serves as the feedforward compensation command. Specifically, Coulomb friction represents the frictional force that is related to the direction of velocity but independent of its magnitude. It is determined by measuring steady-state friction at different velocities, for example, by setting... . Static friction represents the maximum frictional force required to overcome a stationary state. It is typically greater than Coulomb friction and is measured at extremely low speeds during startup, for example, by setting... . Characteristic velocity represents the velocity range of the transition from static friction to Coulomb friction, obtained by fitting a friction force-velocity curve, for example, by setting... . The coefficient of viscous friction represents the coefficient of friction that is proportional to velocity. It is obtained by measuring the relationship between friction and velocity at relatively high speeds, for example, by setting... . The torque conversion factor represents the proportionality coefficient that converts frictional force into the driving torque required by the motor, and it depends on the efficiency and geometric parameters of the transmission mechanism. For example, setting... If the current speed (In fine voltage regulation mode), then: Substituting these values ​​into the above formula yields... Thus, in the fine pressure regulation mode, even at extremely low speeds or even close to zero speeds, the model can accurately estimate and compensate for friction, especially overcome static friction, thereby effectively suppressing the stick-slip phenomenon and avoiding pressure overshoot or undershoot caused by sudden changes in friction. This allows the device to more accurately reach and maintain the target pressure, significantly improving the control accuracy and stability of the bidirectional self-locking device in the critical region.

[0031] In this embodiment, step S4, based on the current control mode, calculates the feedforward compensation command, feedback control command, and micro-vibration command, and further includes: responding to the current control mode being a fine pressure regulation mode, calculating the current pressure error and error change rate based on the current pressure and target pressure; inputting the current pressure error and error change rate into the PD controller to obtain the feedback control command. It should be understood that although feedforward compensation can pre-counteract predictable frictional forces, many uncertainties still exist in actual operating conditions, such as unknown load changes, sensor noise, model errors, and the nonlinear characteristics of the device itself. These factors can cause deviations between the actual pressure and the desired target. The core function of feedback control is to dynamically adjust the drive command using the error between the real-time measured current pressure and the target pressure, thereby eliminating or reducing these deviations and ensuring that the device can accurately and stably reach and maintain the target pressure. Especially in the fine pressure regulation mode of the bidirectional self-locking positioning device, the accuracy requirements for pressure control are extremely high. Feedback control is key to achieving closed-loop regulation, improving system robustness and anti-interference capabilities, and can effectively solve the problems of pressure overshoot, undershoot, and difficulty in fine adjustment mentioned in the background art.

[0032] In this embodiment, step S4 is executed as follows: First, in response to the current control mode being fine pressure regulation mode, the current pressure error and error change rate are calculated based on the current pressure and the target pressure. When the control state machine decision engine determines that the current control mode is fine pressure regulation mode, the controller will immediately start the feedback control module. The current pressure error is the difference between the target pressure and the current pressure, i.e.: current pressure error = target pressure - current pressure. The error change rate is the rate of change of the current pressure error over time, estimated by differential or filtered differential of the current pressure error, i.e., error change rate = (current pressure error - pressure error at the previous sampling time) / sampling period. Taking the above values ​​as an example: the target pressure is 5.0N. The current pressure is 4.85N. Then the current pressure error = 5.0 - 4.85 = 0.15N. For example, if the pressure error at the previous sampling time is 0.151N and the sampling period is 0.001s, then the error change rate = (0.15 - 0.151) / 0.001 = -1N / s.

[0033] Next, the current pressure error and error change rate are input into the PD controller to obtain the feedback control command. In this embodiment, inputting the current pressure error and error change rate into the PD controller to obtain the feedback control command includes: the PD controller processes the current pressure error and error change rate based on the proportional gain and derivative gain using the following formula to obtain the feedback control command, wherein the formula is: ;in, and Indicates the current pressure error and the rate of change of error. and For proportional gain and differential gain, This is a feedback control command.

[0034] Specifically, and These are key parameters of the PD controller; these gains are obtained through offline tuning or optimization algorithms based on the device's dynamic characteristics and desired control performance. For example, setting the proportional gain... Differential gain Substituting these values ​​into the above formula yields... In other words, the proportional term It generates a positive driving torque of 0.75 Nm based on the current positive pressure error of 0.15 Newtons, attempting to directly drive the grippers to continue clamping, in order to quickly compensate for the difference between the current pressure and the target value. However, the differential term... Since the error rate of change is negative, it indicates that the current pressure is rapidly rising towards the target pressure of 5.0 Newtons. To prevent this rapid rise from causing the pressure to exceed the target value, the differential term generates a reverse damping torque of -0.3 Nm, which serves as a predictive adjustment. The final superimposed feedback command indicates that the controller judges that although the current pressure is slightly lower than the target, its downward trend needs to be suppressed immediately. Therefore, a weakened but still positive drive command is issued, which allows for smooth deceleration while continuing to compensate for the error. This ensures that the device can stop accurately and stably at the target pressure point, effectively avoiding the pressure oscillation and overshoot problems commonly encountered in fine pressure regulation.

[0035] It is understandable that traditional PD controllers, when dealing with systems like bidirectional self-locking devices that exhibit significant nonlinearities (such as friction and dead zones) and dynamic characteristic variations, often struggle to simultaneously meet the requirements of fast response and high-precision stability with their fixed gain. Especially under certain special operating conditions, significant numerical differences may exist between pressure errors and error change rates, causing the PD controller to output an excessively large or small reverse torque, leading to overshoot, oscillation, or sluggish response. Therefore, it is practically desirable to increase the gain through fine-tuning. And reduce To optimize.

[0036] Based on this, preferably, in this embodiment, inputting the current pressure error and error change rate into the PD controller to obtain the feedback control command includes: first, obtaining the proportional gain and derivative gain. It should be understood that the proportional gain and derivative gain determine the controller's response strength to the error and its ability to predict the error change trend. Specifically, these values ​​are obtained in the same way as described above.

[0037] Next, the current pressure error and the rate of change of error are adjusted based on the reaction fundamental function to obtain the reaction current pressure error and the reaction error rate of change, that is: ;in, Used as a difference reference factor, it reflects the absolute difference between the error and the rate of change of the error. Used as an equilibrium point, it reflects the average level of error and the rate of change of error. It is based on the natural logarithm function. and These are the current pressure error of the reaction force and the rate of change of the reaction force error, respectively.

[0038] Correspondingly, in the actual operation of a bidirectional self-locking positioning device, the values ​​of the current pressure error and the rate of change of error may differ significantly. For example, when the pressure rapidly approaches the target, the current pressure error may be large while the rate of change of error may be small, or both may be small near a steady state. Directly using such numerical differences for gain adjustment could lead to unreasonable gain optimization, resulting in overshoot or sluggish response. Therefore, a reaction-based fundamental function is introduced to nonlinearly adjust these original error signals, thereby driving the current pressure error. and error change rate By changing in the opposite direction, the original error signal is brought to numerical equilibrium, allowing subsequent gain optimization to more accurately reflect the dynamic demands of the system and making adjustments for large error values ​​more sensitive and small error values ​​smoother. This nonlinear mapping of the original error signal results in… and The numerical values ​​are more balanced, avoiding deviations in subsequent gain adjustments caused by excessive differences in the original values. This allows the controller to respond more quickly to large errors and adjust more precisely to small errors, improving the adaptability and robustness of the control.

[0039] Then, the reaction current pressure error is calculated using the differential operator to obtain the reaction current pressure smoothing rate of change, i.e.: ;in, It is the reaction force that smooths the rate of change of the current pressure.

[0040] It is understandable that abrupt or non-smooth gain adjustments can lead to system oscillations or instability. To ensure that the adaptive adjustment process of the PD gain is smooth and controlled, a mechanism is needed to measure and limit the rate of gain adjustment. The differential operator reaction smoothing rate of change calculation aims to achieve this; it ensures the smoothness of gain adjustment and avoids system oscillations caused by abrupt gain changes by calculating the rate of change of the error adjustment relative to the difference reference factor. Thus, regardless of... Regardless of the value, the differential operators all have the same amplitude and opposite direction, which makes the gain change smoothly decay and avoids abrupt changes. It provides smooth gradient information for subsequent gain optimization, effectively preventing system oscillations caused by excessively rapid gain adjustment and improving the stability of the control system.

[0041] Next, based on the smoothed rate of change of the current reaction pressure, the proportional gain and differential gain are subjected to an exponential form based on the natural constant to perform gradient reduction of the reaction basis function, thereby obtaining the optimized proportional gain and optimized differential gain, i.e.: ;in, and For proportional gain and differential gain, and These are optimizing the proportional gain and optimizing the derivative gain, respectively.

[0042] Correspondingly, traditional PD controllers have fixed gains, making it difficult to adapt to the nonlinear characteristics and dynamic changes of the device under different operating conditions. By applying the previously calculated smoothed rate of change to the initial gain and restoring it using an exponential form based on the natural constant, dynamic and nonlinear adjustment of the gain can be achieved. This adjustment mechanism can dynamically adjust the gain according to the characteristics of the real-time error and the rate of change of the error. and This makes it more suitable for current control needs, thereby improving the controller's adaptability and robustness. In other words, through this exponential-based reduction, it achieves... and Fine-tuning. It introduces a reactionary fundamental function through the numerical differences in the dynamic numerical system as a mechanism to drive the two variables to change in opposite directions, while not changing the overall value of the system. Furthermore, it uses the differential rate of change to avoid oscillatory imbalances, thereby suppressing the divergence tendency of large differences and achieving coefficient... and This adaptive fine-tuning allows the PD controller to dynamically adjust its response characteristics based on real-time operating conditions, thereby maintaining high accuracy and stability throughout the entire operation.

[0043] Finally, the PD controller processes the current pressure error and error change rate based on the optimized proportional gain and the optimized derivative gain to obtain the feedback control command.

[0044] This should be understood as the final output stage of the PD controller. After the aforementioned complex adaptive optimization process, the PD controller uses these optimized gains to calculate the final feedback control command. This adaptive adjustment allows the controller to better adapt to the nonlinear characteristics and dynamic changes of the device under different operating conditions, thereby maintaining high precision and stability throughout the entire operation, effectively suppressing pressure overshoot and oscillation, and ensuring that the bidirectional self-locking device can accurately reach and maintain the target pressure. In particular, this processing method is the same as the formula for generating the feedback control command.

[0045] In this embodiment, step S4, which calculates the feedforward compensation command, feedback control command, and micro-vibration command based on the current control mode, further includes: setting the micro-vibration command to zero in response to the current control mode not being a pre-contact detection mode or a fine pressure regulation mode; and calculating the micro-vibration command based on the current pressure error in response to the current control mode being a pre-contact detection mode or a fine pressure regulation mode. It is worth noting that the core purpose of the micro-vibration command is to overcome the static friction inherent in bidirectional self-locking devices and solve the dead zone effect and viscous-slip phenomenon. As clearly stated in the background art, static friction causes the controller to be unable to drive the device within a small error range, thus accumulating errors and ultimately causing overshoot. Micro-vibration, by superimposing a high-frequency, small-amplitude vibration signal into the drive command, can continuously vibrate the device, keeping it always in or close to a dynamic friction state, thereby effectively eliminating the influence of static friction on control accuracy. This allows the device to respond to minute drive commands, achieving smooth, continuous movement and precise pressure regulation.

[0046] Specifically, in pre-contact detection mode, the device needs to identify the first contact with the workpiece with extremely high sensitivity. Due to the presence of static friction, even if the gripper has made slight contact with the workpiece, the resulting reaction force may still be insufficient to overcome the friction, causing the system to fail to detect the contact state in time, forming a dead zone and affecting the accuracy of detection. To solve this problem, the system applies high-frequency, small-amplitude micro-vibration commands, keeping the device in a micro-motion state at all times, thereby effectively weakening or even eliminating the influence of static friction. This continuous vibration significantly improves the device's sensitivity to minute contact forces, ensuring that the sensor can quickly capture contact once it occurs, achieving hysteresis-free, high-precision pre-contact identification and avoiding the uncertainty caused by friction dead zones. In fine pressure adjustment mode, the device is in a near-static or micron-level adjustment state, and the static friction and its transition characteristics to dynamic friction can easily cause viscous-slip phenomena, resulting in pressure fluctuations and making it difficult to achieve stable control. To address this, the system dynamically generates micro-vibration commands based on the current pressure error and superimposes them into the drive signal, continuously perturbing the system to overcome the influence of friction, enabling the gripper to respond to extremely small displacement changes and achieve continuous and smooth pressure adjustment.

[0047] In rapid approach mode, self-locking mode, and retreat mode, the micro-vibration command is set to zero because the motion characteristics of the control target or device in these modes make micro-vibration unnecessary or potentially negative. In rapid approach mode, the device speed is high, dynamic friction dominates, and static friction has a small impact. In self-locking mode, the device mainly relies on its self-locking characteristics to maintain pressure; ideally, there is no motion, and micro-vibration may interfere with self-locking stability. In retreat mode, the device is far from the target, and accuracy requirements are not high; micro-vibration may increase energy consumption or cause unnecessary wear. Therefore, selectively applying micro-vibration can make the control strategy more targeted and efficient.

[0048] In this embodiment, in response to the current control mode being either a pre-contact detection mode or a fine pressure regulation mode, the micro-vibration command is calculated based on the current pressure error, including: First, based on the current pressure error, the adaptive amplitude is calculated using the following formula: ;in, This is the base amplitude, used to ensure that even with very small pressure errors, a basic jitter force is provided to overcome static friction. This value is determined experimentally and should be slightly greater than the minimum static friction torque of the device, for example, set to 0.001 Nm. As an adaptive gain, it determines the sensitivity of the micro-vibration amplitude to changes in pressure error; a larger gain... This value means that as the pressure error increases, the amplitude of the micro-vibration will increase more rapidly, thus providing stronger vibration force to accelerate the elimination of the error. This value is also calibrated experimentally to balance response speed and system stability. For example, setting it to 0.02 Nm / N and substituting the above value into the equation yields... .

[0049] Next, the micro-vibration command is generated based on the adaptive amplitude. That is, the micro-vibration command is generated based on the adaptive amplitude controller. This micro-vibration command is a high-frequency sine wave or square wave signal, and its amplitude is the calculated value. The frequency is set between tens and hundreds of hertz to ensure that it can effectively excite the tiny movements of the device without causing macroscopic vibrations. For example, a sine wave signal with a frequency of 100 hertz and an amplitude of 0.004 Nm can be generated as a micro-vibration command.

[0050] In step S5, the feedforward compensation command, feedback control command, and micro-vibration command are superimposed to obtain the final drive command. It should be understood that a single control strategy is insufficient to comprehensively address challenges such as nonlinear friction, dynamic response requirements, and dead-zone effects in a system. The feedforward compensation command aims to preemptively offset predictable frictional forces, improving the system's response speed and efficiency; the feedback control command is responsible for real-time correction of deviations caused by unknown disturbances and model errors, ensuring control accuracy and stability; and the micro-vibration command is specifically designed to overcome static friction, eliminate viscous-slip phenomena, and enable the device to respond to minute commands. Superimposing these three types of commands fully leverages their respective advantages, forming a synergistic comprehensive control strategy. This superposition mechanism allows the final drive command to simultaneously possess pre-compensation, real-time error correction, and static friction overcoming capabilities, effectively solving problems mentioned in the background art such as pressure control overshoot, jumps, and difficulty in fine adjustment, achieving high-precision and high-stability dynamic pressure feedback regulation.

[0051] In this embodiment, step S5 is executed as follows: Inside the controller, the feedforward compensation command, feedback control command, and micro-vibration command, after being generated by their respective calculation modules, are aggregated at a summation point and superimposed. This superposition process is linear, meaning the final drive command is the algebraic sum of these three types of commands. Final drive command = feedforward compensation command + feedback control command + micro-vibration command.

[0052] Based on the above calculations, the feedforward compensation command is 0.012 Nm, the feedback control command is 0.45 Nm, and the micro-vibration command is a sine wave signal with a frequency of 100 Hz and an amplitude of 0.004 Nm. In each control cycle (e.g., with a sampling frequency of 1000 Hz, each cycle is 0.001 seconds), the controller acquires and superimposes the instantaneous values ​​of these three commands in real time. For example, at a certain time t, the instantaneous value of the micro-vibration command is... Therefore, the final driving command at this moment will be... This final drive command is a time-varying torque command, which is sent to the device's driver, such as a motor driver. The driver generates a corresponding current or voltage based on this command, thereby driving the motor and controlling the movement and clamping force of the bidirectional self-locking device through the transmission mechanism.

[0053] In summary, the dynamic pressure feedback adjustment method for the bidirectional self-locking device based on the embodiments of this application is explained. It aims to solve the pressure control problems caused by the dead zone effect, nonlinear friction, and asynchrony between drive and sensing in the critical zone of the bidirectional self-locking device by introducing an intelligent control state machine and multimodal command superposition. Specifically, the system first acquires the user-set target pressure, tolerance, contact force threshold, and other control targets, and collects the current position, pressure, and velocity in real time. This information is input into the control state machine decision engine, which intelligently judges and switches the control mode based on the current state, for example, switching from a pre-contact mode to a precise pressure control mode. Based on the current control mode, the system calculates a feedforward compensation command to pre-counteract known nonlinear effects, a feedback control command to correct errors in real time, and a micro-vibration command to effectively overcome static friction and avoid stick-slip phenomena. Finally, these three types of commands are superimposed to generate a drive command, precisely controlling the device's action. This dynamic and adaptive adjustment method effectively avoids the error accumulation and overshoot in the dead zone of traditional PID control, achieving high-precision and high-stability pressure control of the bidirectional self-locking device, thereby ensuring operational reliability and safety.

[0054] Figure 4 This is a block diagram of the dynamic pressure feedback adjustment system of the bidirectional self-locking positioning device according to an embodiment of this application. Figure 4 As shown, the dynamic pressure feedback adjustment system 100 of the bidirectional self-locking positioning device according to an embodiment of this application includes: a control target acquisition module 110, used to acquire a control target input by a user, the control target including target pressure, pressure tolerance, contact force threshold, pre-contact position, and final position; a sensor parameter acquisition module 120, used to acquire the current pressure, current position, and current speed collected by a pressure sensor, a position sensor, and a speed sensor; a control state machine decision module 130, used to input the current position, current pressure, and control target into the control state machine decision engine to obtain the current control mode; an instruction calculation module 140, used to calculate a feedforward compensation instruction, a feedback control instruction, and a micro-vibration instruction based on the current control mode; and a drive instruction generation module 150, used to superimpose the feedforward compensation instruction, the feedback control instruction, and the micro-vibration instruction to obtain the final drive instruction.

[0055] Here, those skilled in the art will understand that the specific operation of each step in the dynamic pressure feedback regulation system of the above-described bidirectional self-locking device has been referenced above. Figures 1 to 3 The dynamic pressure feedback adjustment method of the bidirectional self-locking device has been described in detail, and therefore, its repeated description will be omitted.

[0056] As described above, the dynamic pressure feedback adjustment system 100 of the bidirectional self-locking device according to the embodiments of this application can be implemented in various wireless terminals, such as servers with a dynamic pressure feedback adjustment algorithm for the bidirectional self-locking device. In one possible implementation, the dynamic pressure feedback adjustment system 100 of the bidirectional self-locking device according to the embodiments of this application can be integrated into the wireless terminal as a software module and / or a hardware module. For example, the dynamic pressure feedback adjustment system 100 of the bidirectional self-locking device can be a software module in the operating system of the wireless terminal, or it can be an application developed for the wireless terminal; of course, the dynamic pressure feedback adjustment system 100 of the bidirectional self-locking device can also be one of many hardware modules of the wireless terminal.

[0057] Alternatively, in another example, the dynamic pressure feedback adjustment system 100 of the bidirectional self-locking device and the wireless terminal may also be separate devices, and the dynamic pressure feedback adjustment system 100 of the bidirectional self-locking device may be connected to the wireless terminal via wired and / or wireless networks, and transmit interactive information in accordance with an agreed data format.

[0058] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A dynamic pressure feedback adjustment method for a bidirectional self-locking positioning device, characterized in that, include: The device acquires control targets input by the user, including target pressure, pressure tolerance, contact force threshold, pre-contact position, and home position. The contact force threshold is the minimum force value at which the device determines contact when it approaches an object and makes initial contact. This threshold is used to identify the object during the pre-contact phase and trigger a switch from rapid approach mode to pre-contact detection mode. The pre-contact position is the location point at which the device switches from rapid approach mode to pre-contact detection mode when approaching the target object. The home position is the initial safe position of the device upon completion of the task or startup. Acquire the current pressure, current position, and current velocity collected by the pressure sensor, position sensor, and velocity sensor; The current position, current pressure, and control target are input into the control state machine decision engine to obtain the current control mode, which includes: rapid approach mode, pre-contact detection mode, self-locking mode, fine pressure regulation mode, and retreat mode. Based on the current control mode, calculate the feedforward compensation command, feedback control command, and micro-vibration command, including: in response to the current control mode being fine pressure regulation mode, calculate the current pressure error and error change rate based on the current pressure and target pressure; input the current pressure error and error change rate into the PD controller to obtain the feedback control command; The feedforward compensation command, feedback control command, and micro-vibration command are superimposed to obtain the final drive command; The process of inputting the current pressure error and error change rate into the PD controller to obtain the feedback control command includes: acquiring the proportional gain and derivative gain; adjusting the current pressure error and error change rate based on the reaction basis function to obtain the reaction current pressure error and reaction error change rate; calculating the reaction smooth change rate using the derivative operator on the reaction current pressure error to obtain the reaction current pressure smooth change rate; performing gradient restoration of the reaction basis function based on the reaction current pressure smooth change rate using the proportional gain and derivative gain in an exponential form based on the natural constant to obtain the optimized proportional gain and optimized derivative gain; and processing the current pressure error and error change rate based on the optimized proportional gain and optimized derivative gain to obtain the feedback control command.

2. The dynamic pressure feedback adjustment method for the bidirectional self-locking positioning device according to claim 1, characterized in that, Based on the current control mode, the feedforward compensation command, feedback control command, and micro-vibration command are calculated, including: in response to the current control mode being a rapid approach mode or a fine voltage regulation mode, the feedforward compensation command is calculated based on the current speed; in response to the current control mode not being a rapid approach mode or a fine voltage regulation mode, the feedforward compensation command is set to zero.

3. The dynamic pressure feedback adjustment method for the bidirectional self-locking positioning device according to claim 2, characterized in that, In response to the current control mode being either fast approach mode or fine voltage regulation mode, the feedforward compensation command is calculated based on the current speed, including: calculating the feedforward compensation command based on the current speed using the following formula, wherein the formula is: ;in, and Here, are constants, representing Coulomb friction, static friction, characteristic velocity, viscous friction coefficient, and torque conversion coefficient, respectively. At the current speed, To take the absolute value, Based on the natural constant The value of the exponential function with base 0. It is a symbolic function. It is friction. The compensation torque serves as the feedforward compensation command.

4. The dynamic pressure feedback adjustment method for the bidirectional self-locking positioning device according to claim 3, characterized in that, The current pressure error and error change rate are input into the PD controller to obtain the feedback control command, including: the PD controller processes the current pressure error and error change rate based on the proportional gain and derivative gain using the following formula to obtain the feedback control command, wherein the formula is: ;in, and Indicates the current pressure error and the rate of change of error. and For proportional gain and differential gain, This is a feedback control command.

5. The dynamic pressure feedback adjustment method for the bidirectional self-locking positioning device according to claim 1, characterized in that, Based on the current control mode, the calculation of feedforward compensation command, feedback control command, and micro-vibration command further includes: in response to the current control mode not being a pre-contact detection mode or a fine pressure regulation mode, setting the micro-vibration command to zero; and in response to the current control mode being a pre-contact detection mode or a fine pressure regulation mode, calculating the micro-vibration command based on the current pressure error.

6. The dynamic pressure feedback adjustment method for the bidirectional self-locking positioning device according to claim 5, characterized in that, In response to the current control mode being either pre-contact detection mode or fine pressure regulation mode, the micro-vibration command is calculated based on the current pressure error, including: calculating the adaptive amplitude based on the current pressure error using the following formula: ;in, Indicates the current pressure error, Basic amplitude, For adaptive gain, The adaptive amplitude is used; based on the adaptive amplitude, the micro-vibration command is generated.

7. A dynamic pressure feedback adjustment system for a bidirectional self-locking positioning device, characterized in that, include: The control target acquisition module is used to acquire control targets input by the user. These control targets include target pressure, pressure tolerance, contact force threshold, pre-contact position, and home position. The contact force threshold refers to the minimum force value at which the device determines contact when it approaches an object and makes initial contact. The contact force threshold is used to identify the object during the pre-contact phase and trigger a switch from rapid approach mode to pre-contact detection mode. The pre-contact position refers to the location point at which the device switches from rapid approach mode to pre-contact detection mode when approaching the target object. The home position refers to the initial safe position of the device upon completion of the task or startup. The sensor parameter acquisition module is used to acquire the current pressure, current position, and current speed collected by the pressure sensor, position sensor, and speed sensor. The control state machine decision module is used to input the current position, current pressure and control target into the control state machine decision engine to obtain the current control mode. The current control modes include: rapid approach mode, pre-contact detection mode, self-locking mode, fine pressure regulation mode and retreat mode. The instruction calculation module is used to calculate feedforward compensation instructions, feedback control instructions, and micro-vibration instructions based on the current control mode, including: responding to the current control mode being a fine pressure regulation mode, calculating the current pressure error and error change rate based on the current pressure and the target pressure; and inputting the current pressure error and error change rate into the PD controller to obtain the feedback control instructions; The drive command generation module is used to superimpose feedforward compensation commands, feedback control commands, and micro-vibration commands to obtain the final drive command. The process of inputting the current pressure error and error change rate into the PD controller to obtain the feedback control command includes: acquiring the proportional gain and derivative gain; adjusting the current pressure error and error change rate based on the reaction basis function to obtain the reaction current pressure error and reaction error change rate; calculating the reaction smooth change rate using the derivative operator on the reaction current pressure error to obtain the reaction current pressure smooth change rate; performing gradient restoration of the reaction basis function based on the reaction current pressure smooth change rate using the proportional gain and derivative gain in an exponential form based on the natural constant to obtain the optimized proportional gain and optimized derivative gain; and processing the current pressure error and error change rate based on the optimized proportional gain and optimized derivative gain to obtain the feedback control command.

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