Cooperative control system for safe stacking of metal strips

Abstract

The invention discloses a cooperative control system for safe stacking of metal strips, and relates to the technical field of cooperative robot control, the cooperative control system comprises a cooperative robot, a tail end force sense holder, a motion controller and a central processing unit; the tail end force sense clamping device is mounted at the tail end of the collaborative robot and used for grabbing the metal strip and monitoring an actual internal force signal borne by the metal strip in real time; the motion controller is used for driving the cooperative robot to move according to the control instruction; the central processing unit is electrically connected with the tail end force sense clamping device and the motion controller, and the central processing unit internally comprises a motion task planning module which is used for generating an expected motion instruction of a cooperative robot according to a stacking task; the dynamic characteristic identification module is used for receiving an expected motion instruction and an actual internal force signal and estimating the dynamic model mismatch degree of the metal strip in real time; the problems that existing stacking is extremely low in safety and low in efficiency are solved.

Description

Technical Field

[0001] This invention relates to the field of collaborative robot control technology, specifically a collaborative control system for the safe stacking of metal strips. Background Technology

[0002] Metal strips are characterized by their heavy weight, susceptibility to deformation, and susceptibility to scratches. Automated palletizing of these strips typically requires the collaborative operation of multiple robots. In existing technologies, collaborative control systems employ high-rigidity controllers to achieve high handling efficiency and high repeatability. However, because metal strips are inherently flexible, and slight asynchrony in movement is easily observed between multiple robots, high-rigidity control can instantly generate enormous internal stress within the strip, leading to bending, permanent deformation, or violent vibrations, resulting in extremely low safety.

[0003] To address the aforementioned issues, conventional impedance control employs fixed, low-stiffness parameters to make the robot behave compliantly. While this method can absorb some vibration, the parameters must be set extremely conservatively to ensure safety for all different batches of strip. This results in significant swaying of the strip during high-speed starts, stops, or turns, severely limiting handling speed and leading to extremely low palletizing efficiency. Therefore, designing a safe and efficient collaborative control system for the safe palletizing of metal strip is essential. Summary of the Invention

[0004] The purpose of this invention is to provide a collaborative control system for the safe stacking of metal strips, so as to solve the problems mentioned in the background art.

[0005] To address the aforementioned technical problems, this invention provides the following technical solution: a collaborative control system for the safe palletizing of metal strip, comprising a collaborative robot, an end effector force sensor gripper, a motion controller, and a central processing unit; the end effector force sensor gripper is installed at the end of the collaborative robot for gripping the metal strip and monitoring the actual internal force signal it bears in real time; the motion controller is used to drive the collaborative robot to move according to control commands; the central processing unit is electrically connected to the end effector force sensor gripper and the motion controller, and the central processing unit internally includes: The motion task planning module is used to generate the desired motion instructions for the collaborative robot based on the palletizing task. The dynamic characteristic identification module is used to receive the desired motion command and the actual internal force signal, and to estimate the dynamic model mismatch of the metal strip in real time. The adaptive stiffness control module is used to adjust the control stiffness of the motion controller in real time online according to the mismatch of the dynamic model, and generate a compensation motion signal.

[0006] According to the above technical solution, the dynamic characteristic identification module further includes a static model storage unit, a desired internal force calculation unit, and a mismatch calculation unit; the static model storage unit is used to store the reference dynamic model of the metal strip; the desired internal force calculation unit is used to calculate the theoretical desired internal force signal based on the reference dynamic model and the desired motion command; the mismatch calculation unit is used to calculate the difference between the actual internal force signal and the desired internal force signal in real time, and output the difference as the dynamic model mismatch.

[0007] According to the above technical solution, the adaptive stiffness control module further includes a control stiffness calculation unit, which is used to calculate the current optimal control stiffness based on the dynamic model mismatch.

[0008] According to the above technical solution, the adaptive stiffness control module further includes a compensation signal generation unit, which is used to generate a compensation motion signal for actively absorbing vibration based on the dynamic model mismatch degree. The motion controller ultimately executes a combined motion command on the collaborative robot, consisting of the desired motion command and the compensated motion signal.

[0009] According to the above technical solution, the collaborative control method for safe stacking of metal strips in the system includes the following steps: Step S1: The motion task planning module generates highly dynamic desired motion instructions, which drive the motion controller to enable the robot to start high-speed handling of metal strips; Step S2: During high-speed transport, the dynamic characteristic identification module works in parallel, receiving the desired motion command and the actual internal force signal in real time, and calculating the dynamic model mismatch degree. Step S3: The adaptive stiffness control module calculates the new control stiffness in real time based on the calculated dynamic model mismatch and generates a compensation motion signal; Step S4: The motion controller executes the combined instruction of the desired motion command and the compensated motion signal with the new control stiffness, driving the collaborative robot to complete the motion.

[0010] According to the above technical solution, in step S2, the specific steps for the dynamic characteristic identification module to calculate the dynamic model mismatch degree include: Step S21: Extract the desired acceleration at time T from the desired motion command. ; Step S22: Obtain the actual internal signal fed back by the end effector force sensor at time T. ; Step S23: Cache the expected acceleration at time T-1 of the previous control cycle. and actual internal strength ; Step S24: Calculate the trend of desired acceleration change = ; Calculate the actual internal force variation trend ; Step S25: Generate a status flag bit ; when and When judged as a serious deviation, set ; when and When the trend is synchronized, the settings are adjusted accordingly. ; when It is determined to be a non-acceleration zone, and settings are adjusted accordingly. ; Step S26: Set the status flag bit As a dynamic model mismatch, it is output to the adaptive stiffness control module.

[0011] According to the above technical solution, step S3 further includes: Step S31: Accumulate the count using a stiffness-maintaining counter. When a value is received... When, its calculation expression is: ,in The stiffness is maintained by the counter count value; when At that time, ; Step S32: Based on the status flag bit and stiffness retention counter Graded calculation to control stiffness : In response to The situation was determined to be transient instability, and immediate action was taken. ,in This is the preset minimum safety stiffness value; In response to ,and Then execute ;in To stabilize the periodic threshold, High stiffness as a benchmark; In response to and Then execute ; Step S33: Through the compensation signal generation unit, based on the status flag bit... Synchronous generation of compensated motion signals ,in: In response to Generate active damping signal ,in It is the damping coefficient, used to actively counteract the tendency of internal forces to change in the opposite direction; In response to Then generate .

[0012] According to the above technical solution, in step S32, the reference high stiffness It is preset based on the reference dynamic model in the static model storage unit of the metal strip; the minimum safety stiffness It is a safety lower limit determined by the maximum internal force impact that the end effector can withstand and the safety operation specifications of the collaborative robot.

[0013] According to the above technical solution, in step S33, the damping coefficient in the active damping signal Further based on the actual internal force change trend The amplitude is adjusted when The increase in amplitude is a synchronous increase. The value is adjusted to provide a stronger vibration damping effect.

[0014] Compared with the prior art, the beneficial effects achieved by the present invention are: (1) This invention creatively transforms the high-dynamic motion commands that cause system oscillations into excitation sources for identification through the strong linkage between the dynamic characteristic identification module and the adaptive stiffness control module. When the system is running at high speed, once an instability trend is predicted, it immediately switches to a safe mode and automatically restores high stiffness after stabilization, thus perfectly solving the core contradiction that safety and efficiency cannot be balanced. (2) This invention achieves a predictive safety control by comparing the expected acceleration trend with the actual internal force trend. It does not passively stop after the internal force exceeds the threshold, but actively intervenes before the oscillation occurs, that is, when the trend just begins to deviate, thus eliminating the risk of internal force overload and oscillation from the root. (3) By setting up a detection algorithm, no additional jitter or calibration test is required. The identification process and the handling task occur in parallel, reducing the invalid time of model identification to zero and greatly improving the production cycle. Attached Figure Description

[0015] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of the system architecture of the present invention; Figure 2This is a schematic diagram of the central processing unit module of the present invention; Figure 3 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Please see Figure 1 This invention provides a technical solution: a collaborative control system for the safe palletizing of metal strip, comprising a collaborative robot, an end effector force sensor gripper, a motion controller, and a central processing unit (CPU); the end effector force sensor gripper is installed at the end of the collaborative robot for gripping the metal strip and monitoring the actual internal force signal it bears in real time; the motion controller is used to drive the collaborative robot to move according to control commands; the CPU is electrically connected to the end effector force sensor gripper and the motion controller, and the CPU internally includes: The motion task planning module is used to generate the desired motion instructions for the collaborative robot based on the palletizing task. The dynamic characteristic identification module is used to receive the desired motion command and the actual internal force signal, and to estimate the dynamic model mismatch of the metal strip in real time. The adaptive stiffness control module adjusts the control stiffness of the motion controller in real time based on the dynamic model mismatch and generates compensating motion signals. This invention addresses the predictive safety issue of when to intervene by judging the divergence between the expected and actual trends; it then solves the stability issue of how to safely recover by using graded stiffness and stable climbing; finally, it solves the precision issue of how much force to intervene through dynamic damping. This interconnected mechanism ultimately achieves safe, efficient, and intelligent palletizing of metal strips.

[0018] The dynamic characteristic identification module further includes a static model storage unit, a desired internal force calculation unit, and a mismatch calculation unit; the static model storage unit is used to store the reference dynamic model of the metal strip; the desired internal force calculation unit is used to calculate the theoretical desired internal force signal based on the reference dynamic model and the desired motion command; the mismatch calculation unit is used to calculate the difference between the actual internal force signal and the desired internal force signal in real time, and output the difference as the dynamic model mismatch.

[0019] The adaptive stiffness control module further includes a control stiffness calculation unit, which is used to calculate the current optimal control stiffness based on the dynamic model mismatch.

[0020] The adaptive stiffness control module further includes a compensation signal generation unit, which generates a compensation motion signal for actively absorbing vibration based on the dynamic model mismatch. The motion controller ultimately executes a combined motion command on the collaborative robot, consisting of the desired motion command and the compensation motion signal.

[0021] A collaborative control method for the safe stacking of metal strips, comprising the following steps: Step S1: The motion task planning module generates highly dynamic desired motion instructions, which drive the motion controller to enable the robot to start high-speed handling of metal strips. Step S2: During high-speed transport, the dynamic characteristic identification module works in parallel, receiving the desired motion command and the actual internal force signal in real time, and calculating the dynamic model mismatch degree. Step S3: The adaptive stiffness control module calculates the new control stiffness in real time based on the calculated dynamic model mismatch and generates a compensation motion signal; Step S4: The motion controller executes the combined instruction of the desired motion command and the compensated motion signal with the new control stiffness, driving the collaborative robot to complete the motion.

[0022] In step S2, the specific steps for the dynamic characteristic identification module to calculate the dynamic model mismatch degree include: Step S21: Extract the desired acceleration at time T from the desired motion command. ; Step S22: Obtain the actual internal signal fed back by the end effector force sensor at time T. ; Step S23: Cache the expected acceleration at time T-1 of the previous control cycle. and actual internal strength ; Step S24: Calculate the trend of desired acceleration change = ; Calculate the actual internal force variation trend ; Step S25: Generate a status flag bit ; when and When judged as a serious deviation, set ; when and When the trend is synchronized, the settings are adjusted accordingly. ; when It is determined to be a non-acceleration zone, and settings are adjusted accordingly. ; Step S26: Set the status flag bit As a dynamic model mismatch, it is output to the adaptive stiffness control module.

[0023] Step S3 further includes: Step S31: Accumulate the count using a stiffness-maintaining counter. When a value is received... When, its calculation expression is: ,in The stiffness is maintained by the counter count value; when At that time, ; Step S32: Based on the status flag bits and stiffness retention counter Graded calculation to control stiffness : In response to The situation was determined to be transient instability, and immediate action was taken. ,in This is the preset minimum safety stiffness value; In response to ,and Then execute ;in To stabilize the periodic threshold, High stiffness as a benchmark; In response to and Then execute ; Step S33: Through the compensation signal generation unit, based on the status flag bit... Synchronous generation of compensated motion signals ,in: In response to Generate active damping signal ,in It is the damping coefficient, used to actively counteract the tendency of internal forces to change in the opposite direction; In response to Then generate .

[0024] In step S32, the reference high stiffness It is preset based on the reference dynamic model in the static model storage unit of the metal strip; minimum safety stiffness It is a safety lower limit determined by the maximum internal force impact that the end effector gripper can withstand and the safety operation specifications of collaborative robots.

[0025] In step S33, the damping coefficient in the active damping signal Further based on the actual trend of internal force changes The amplitude is adjusted when The increase in amplitude is a synchronous increase. The value is adjusted to provide a stronger vibration damping effect; Through the above steps, this invention resolves the core contradiction of balancing safety and efficiency in the collaborative handling of flexible strip materials. The advantage of this application lies in its design of an intelligent closed-loop system that links trend prediction and graded response, avoiding both consistently high stiffness (high efficiency but dangerous) and consistently low stiffness (safe but inefficient). First, this invention utilizes a trend divergence detector to creatively compare the desired acceleration command with the actual internal force feedback in real time. This avoids passively waiting for the internal force to exceed the danger threshold (at which point oscillation has already occurred), and instead actively detects anomalous critical phenomena—the instant when the system commands acceleration but the internal force decreases in the opposite direction. Second, once the detector issues a warning, the system immediately executes a graded response tactic: First, it immediately switches the system stiffness from a high-efficiency mode to a minimum safety mode to ensure absolute safety; second, it simultaneously triggers an active damping signal, the strength of which is dynamically adjusted according to the severity of the divergence (i.e., the amplitude of internal force change), achieving precise compensation with stronger suppression as the divergence worsens, actively counteracting the oscillation trend. Finally, this invention also includes a sophisticated recovery and execution mechanism. When the danger (deviation signal) disappears, the system does not recklessly jump back to high stiffness immediately. Instead, it triggers a stiffness ramp-up process through a stiffness maintenance counter, allowing the stiffness to smoothly recover to the baseline high stiffness, thus avoiding secondary shocks caused by sudden stiffness changes. Furthermore, throughout the execution process, the system's damping dynamically and inversely correlates with the stiffness; that is, high stiffness is matched with low damping, and low stiffness is matched with high damping, ensuring the system remains stable in any mode, without jittering or swaying. In summary, this invention, through this interconnected design from trend prediction to graded stiffness, then to dynamic compensation and inverse damping, ultimately achieves maximum efficiency most of the time, only instantaneously switching to a safe mode in the milliseconds before instability, and smoothly recovering after the danger has passed. Thus, without sacrificing safety, it maximizes the operational efficiency of metal strip collaborative palletizing.

[0026] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0027] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0028] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0029] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A collaborative control system for the secure stacking of metal strip, characterized in that, The system includes a collaborative robot, an end effector gripper, a motion controller, and a central processing unit; the end effector gripper is installed at the end of the collaborative robot to grasp metal strips and monitor the actual internal force signals it experiences in real time; the motion controller is used to drive the collaborative robot to move according to control commands. The central processing unit is electrically connected to the end effector force sensor and the motion controller, and the central processing unit internally includes: The motion task planning module is used to generate the desired motion instructions for the collaborative robot based on the palletizing task. The dynamic characteristic identification module is used to receive the desired motion command and the actual internal force signal, and to estimate the dynamic model mismatch of the metal strip in real time. The adaptive stiffness control module is used to adjust the control stiffness of the motion controller in real time online according to the mismatch of the dynamic model, and generate a compensation motion signal.

2. The collaborative control system for secure palletizing of metal strips according to claim 1, characterized in that: The dynamic characteristic identification module further includes a static model storage unit, a desired internal force calculation unit, and a mismatch calculation unit; the static model storage unit is used to store the reference dynamic model of the metal strip; the desired internal force calculation unit is used to calculate the theoretical desired internal force signal based on the reference dynamic model and the desired motion command; the mismatch calculation unit is used to calculate the difference between the actual internal force signal and the desired internal force signal in real time, and output the difference as the dynamic model mismatch.

3. A collaborative control system for secure palletizing of metal strips according to claim 1, characterized in that: The adaptive stiffness control module further includes a control stiffness calculation unit, which is used to calculate the current optimal control stiffness based on the dynamic model mismatch.

4. A collaborative control system for secure palletizing of metal strips according to claim 3, characterized in that: The adaptive stiffness control module further includes a compensation signal generation unit, which is used to generate a compensation motion signal for actively absorbing vibration based on the dynamic model mismatch degree. The motion controller ultimately executes a combined motion command on the collaborative robot, consisting of the desired motion command and the compensated motion signal.

5. A collaborative control method for secure stacking of metal strip based on the system described in any one of claims 1-4, characterized in that: The method includes the following steps: Step S1: The motion task planning module generates highly dynamic desired motion instructions, which drive the motion controller to enable the robot to start high-speed handling of metal strips; Step S2: During high-speed transport, the dynamic characteristic identification module works in parallel, receiving the desired motion command and the actual internal force signal in real time, and calculating the dynamic model mismatch degree. Step S3: The adaptive stiffness control module calculates the new control stiffness in real time based on the calculated dynamic model mismatch and generates a compensation motion signal; Step S4: The motion controller executes the combined instruction of the desired motion command and the compensated motion signal with the new control stiffness, driving the collaborative robot to complete the motion.

6. A collaborative control method for secure stacking of metal strips according to claim 5, characterized in that: In step S2, the specific steps for the dynamic characteristic identification module to calculate the dynamic model mismatch degree include: Step S21: Extract the desired acceleration at time T from the desired motion command. ; Step S22: Obtain the actual internal signal fed back by the end effector force sensor at time T. ; Step S23: Cache the expected acceleration at time T-1 of the previous control cycle. and actual internal strength ; Step S24: Calculate the trend of desired acceleration change = ; Calculate the actual internal force variation trend ; Step S25: Generate a status flag bit ; when and When this is judged as a serious deviation, a setting is made. ; when and When the trend is synchronized, the settings are adjusted accordingly. ; when It is determined to be a non-acceleration zone, and settings are adjusted accordingly. ; Step S26: Set the status flag bit As a dynamic model mismatch, it is output to the adaptive stiffness control module.

7. A collaborative control method for secure stacking of metal strips according to claim 6, characterized in that: Step S3 further includes: Step S31: Accumulate the count using a stiffness-maintaining counter. When a value is received... When, its calculation expression is: ,in The stiffness is maintained by the counter count value; when At that time, ; Step S32: Based on the status flag bit and stiffness retention counter Graded calculation to control stiffness : In response to The situation was determined to be transient instability, and immediate action was taken. ,in This is the preset minimum safety stiffness value; In response to ,and Then execute ;in To stabilize the periodic threshold, High stiffness as a benchmark; In response to and Then execute ; Step S33: Through the compensation signal generation unit, based on the status flag bit... Synchronous generation of compensated motion signals ,in: In response to Generate active damping signal ,in It is the damping coefficient, used to actively counteract the tendency of internal forces to change in the opposite direction; In response to Then generate .

8. A collaborative control method for secure stacking of metal strips according to claim 7, characterized in that: In step S32, the reference high stiffness It is preset based on the reference dynamic model in the static model storage unit of the metal strip; the minimum safety stiffness It is a safety lower limit determined by the maximum internal force impact that the end effector can withstand and the safety operation specifications of the collaborative robot.

9. A collaborative control method for secure stacking of metal strips according to claim 7, characterized in that: In step S33, the damping coefficient in the active damping signal Further based on the actual internal force change trend The amplitude is adjusted when The increase in amplitude is a synchronous increase. The value is adjusted to provide a stronger vibration damping effect.

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