CN113755978B - An automatic joint robot compliance device based on tension feedback - Google Patents

Abstract

The invention relates to an automatic piecing robot compliance control device based on tension feedback, comprising a robot, a yarn drawing device, a tension sensor and an industrial computer. The industrial computer runs a force tracking admittance control model and a PID controller based on yarn tension feedback. The robot compliance control algorithm. The present invention adopts the force tracking admittance controller to establish the dynamic relationship between the yarn tension and the robot kinematic parameters during the robot yarn piecing, and at the same time adds PID control to improve the force tracking performance, so that the tension on the yarn during the whole piecing process is improved. Keep it close to the desired tension value. The invention can effectively prevent yarn breakage during the automatic piecing of spun yarns, improve the success rate of piecing, and at the same time provides a solution for automatic piecing of low-strength and high-count pure cotton yarns.

Description

An Automatic Joint Robot Compliant Device Based on Tension Feedback

technical field

The invention relates to an automatic piecing robot compliance control device based on yarn tension feedback, belonging to the technical field of spun yarn automatic piecing devices.

Background technique

Traditional ring spinning has the advantages of a wide range of raw materials, good product usability, wide range of spinnable counts and good yarn strength, accounting for more than 80% of the total yarn output in the country. It is necessary to manually complete the piecing by the workers in the car, and the automatic piecing of ring-spun spun yarn has always been the goal pursued by the domestic and foreign spinning circles. Driven by the demand for automatic piecing robots in the spinning industry and the development of technology, there are relatively mature automatic piecing technologies and devices at home and abroad.

Due to the complexity of finding the end on the broken yarn bobbin, the existing splicing methods mainly use auxiliary yarn feeding splices. "Automatic and intelligent piecing method and device for ring spinning yarn breakage", "an automatic piecing device and method for ring spinning spinning frame" designed in Chinese patent CN113174668A, etc., all use spare yarn to be wound on the broken yarn bobbin, and then pass through The yarn take-off device pulls the spare yarn through the traveler, the balloon ring, the yarn guide hook and feeds the front roller, and the common problems of the existing piecing methods and devices are:

(1) The spare yarn is connected to the yarn drawing device through a long tube, and a large frictional resistance may occur during the yarn drawing process. However, the motion control of the existing yarn drawing device is an open-loop position control. In this case, it is easy to break the yarn and cause the joint to fail.

(2) For the automatic piecing of high-count pure cotton yarn, the problem of yarn breakage due to the yarn tension being greater than the strength is very likely to occur during the yarn drawing process due to the low yarn strength. The existing automatic piecing technologies and devices have not solved this kind of problem. solution to the problem.

SUMMARY OF THE INVENTION

The purpose of the invention is to prevent the yarn breakage during the automatic piecing of spun yarns, effectively improve the success rate of piecing, and to provide a solution for the automatic piecing of high-count pure cotton yarns.

In order to achieve the above purpose, the technical solution of the present invention is to provide an automatic piecing robot compliance control device based on tension feedback, which is characterized in that it includes a robot, the end of the robot is provided with a yarn feeding device, and the end of the yarn feeding device is provided with a tension sensor , the yarn passes through the yarn feeding device and is held by it, and the robot pulls the yarn through the yarn feeding device to complete the automatic piecing of the ring spinning spun yarn; during the entire automatic piecing process of the ring spinning spun yarn, the yarn is obtained in real time through the tension sensor The actual tension is uploaded to the industrial computer. The industrial computer runs the robot compliance control algorithm based on the yarn tension feedback based on the force tracking admittance control model and the PID controller. The robot yarn delivery is established through the robot compliance control algorithm. During piecing, the dynamic relationship between the actual tension of the yarn and the kinematic parameters of the robot keeps the tension on the yarn close to the desired tension value during the entire automatic piecing process of the ring-spun spun yarn, where:

After the industrial computer receives the actual tension, the robot compliance control algorithm uses the force tracking admittance control model to obtain the kinematic parameters of the robot in the Cartesian space, and uses the robot inverse kinematics algorithm to convert the kinematic parameters into each joint angle of the robot; industrial control The machine sends each joint angle to the robot, so that the robot moves to the specified position and completes the motion control of the robot, thereby indirectly controlling the yarn tension during the piecing process to keep the desired tension value near the desired tension value, preventing the piecing failure caused by the yarn breakage during the piecing process. In this process, the robot compliance control algorithm introduces a PID controller to adjust the dynamic and steady-state tension tracking performance of the force tracking admittance control model when the environment changes.

Preferably, the kinematic parameters of the robot include the pose, velocity and acceleration of the robot end, then the force tracking admittance control model is shown in the following formula (1):

代表机器人完成接头动作的期望轨迹的位姿、速度、加速度；X(t)、

代表机器人的实际运动位姿、速度、加速度；F_d(t)代表接头过程中的期望张力；F_e(t)代表接头过程中通过张力传感器测得的实际张力；In formula (1), M _d , B _d , K _d are the predetermined expected robot inertia, expected damping and expected stiffness matrix, and the dimension of the expected stiffness matrix depends on the degree of freedom of the robot; X _d (t),

The pose, velocity, and acceleration representing the desired trajectory of the robot to complete the joint action; X(t),

Represents the actual motion pose, velocity, and acceleration of the robot; F _d (t) represents the expected tension in the joint process; F _e (t) represents the actual tension measured by the tension sensor in the joint process;

In order to facilitate the application of the robot compliance control algorithm based on yarn tension feedback in the actual sampling-based control system, the differential equation of equation (1) is written in the form of the differential equation shown in equation (2) below

第n+1个控制周期的机器人接头过程中的速度

以及第n+1个控制周期的机器人接头过程中的位姿X((n+1)T)。In formula (2), nT represents the nth control cycle, n=1, 2, 3..., T is the sampling frequency, so as to obtain the acceleration during the nth control cycle of the robot joint process

Velocity during robot jointing in the n+1th control cycle

And the pose X((n+1)T) during the robot joint process in the n+1th control cycle.

均为0，此时通过式(1)求得所述力跟踪导纳控制模型的参数K_d，再根据二阶系统的动态特性与系统仿真结果确定M_d、B_d；Preferably, when the force tracking admittance control model reaches a steady state,

are all 0, at this time, the parameter K _d of the force tracking admittance control model is obtained by formula (1), and then M _d and B _d are determined according to the dynamic characteristics of the second-order system and the system simulation results;

Then the force tracking admittance control model is simulated based on the calculated parameters K _d , M _d , B _d , M _{d and B d are continuously adjusted according to the simulation results, and finally the M d and} B _d with the best force tracking effect are selected _. the value of;

During simulation, the environmental dynamics model is used to simulate _Fe (t), which is expressed by the following formula (3):

表示纱线的环境速度；K_e表示纱线的纱线刚度。In formula (3), _{Be represents the damping coefficient between the yarn drawing device and the yarn; X e (} t) represents the environmental position of the yarn;

represents the ambient velocity of the yarn; _Ke represents the yarn stiffness of the yarn.

Preferably, in order to improve the robustness of tension tracking of the force tracking admittance control model to changes in environmental position, stiffness and other factors, the PID controller is used to adjust the dynamic and steady state tension of the force tracking admittance control model when the environment changes Tracking performance, e(nT)=F _e (nT)-F _d (nT), the ideal PID control law of the continuous control system is expressed as the following formula (4):

In Equation (4), u(nT) represents the control amount passed by the PID controller to the force tracking admittance control model in the nth control cycle; k _p is the proportional coefficient of PID control; T _t is the integral time constant; T _D is the differential Time constant; e(nT) is the deviation between the actual tension and the expected tension in the nth control cycle;

The PID controller shown in Equation (4) is written in the form of the difference equation shown in Equation (5) below:

In formula (5), E(nT) represents the sum of the deviations of all tensions in the nth control cycle; k _i and k _d represent the integral coefficient and differential coefficient of PID control respectively; F _e (nT) represents the nth The actual tension measured by the tension sensor during the splicing process of the control cycle; F _d (nT) represents the desired tension during the splicing process of the nth control cycle.

The invention adopts the force tracking admittance controller to establish the dynamic relationship between the yarn tension and the kinematic parameters of the robot during the robot yarn feeding and piecing, and at the same time adds PID control to improve the force tracking performance, so that the tension on the yarn during the whole piecing process is improved. Keep it close to the desired tension value. The invention can effectively prevent yarn breakage during the automatic piecing of spun yarns, improve the success rate of piecing, and at the same time provides a solution for automatic piecing of low-strength and high-count pure cotton yarns.

Description of drawings

Fig. 1 is the control flow chart of the embodiment of the present invention;

2 is a block diagram of a control algorithm according to an embodiment of the present invention;

FIG. 3 is a mechanical structure diagram of an embodiment of the present invention.

Detailed ways

The present invention is further described below in conjunction with specific embodiments. It should be understood that these examples are only used to illustrate the present invention and not to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

A tension feedback-based automatic piecing robot compliance control device provided by the present invention includes a robot 101, a yarn drawing device 102, a tension sensor 104 and an industrial computer. A yarn feeding device 102 is assembled at the end of the robot 101 , and the yarn 103 passes through the yarn feeding device 102 and is held by the yarn feeding device 102 . The robot 101 pulls the yarn 103 through the yarn drawing device 102 to complete the entire automatic piecing of the ring-spun spun yarn. The tension sensor 104 is assembled at the end of the yarn drawing device 102. During the whole automatic piecing process of the ring spinning spun yarn, the actual tension of the yarn 103 is obtained in real time through the tension sensor 104 and uploaded to the industrial computer.

In this embodiment, the robot 101 adopts an industrial-grade six-axis robot to meet the continuous operation requirements of high-precision multi-position. The yarn drawing device 102 adopts a unidirectional nozzle, and the pulling and clamping of the yarn 103 can be realized by controlling the size and direction of the incoming air flow. The tension sensor 104 adopts the FS1-200-USB type tension sensor of Germany SCHMIDT company, the maximum range is 200cN, and the maximum sampling frequency is 200HZ. The industrial computer adopts Intel Core i7 processor to realize real-time processing and feedback of data, and adopts large-capacity hard disk to realize the storage of original data and processed data, which is convenient for subsequent analysis.

The industrial computer runs the robot compliance control algorithm based on the yarn tension feedback based on the force tracking admittance control model and the PID controller. After the industrial computer receives the actual tension, the robot compliance control algorithm uses the force tracking admittance control model to obtain the kinematic parameters of the robot 101 , and calculates each joint angle of the robot 101 based on the kinematic parameters. The industrial computer sends each joint angle to the robot 101, so that the robot 101 moves to the specified pose and completes the motion control of the robot 101, thereby indirectly controlling the yarn tension during the piecing process to keep the desired tension value near, preventing the yarn during the piecing process. Joint failure due to breakage.

In the actual control process, the tracking performance of the yarn tension of the yarn 103 using the tension sensor 104 by the robot compliance control algorithm may be deteriorated due to changes in environmental position, stiffness and other factors, and even tension tracking failure occurs, causing the yarn tension to exceed A situation where the yarn is broken by a strong pull. Therefore, the robot compliance control algorithm introduces a PID controller to adjust the dynamic and steady-state tension tracking performance of the force tracking admittance control model when the environment changes.

In the present invention, the robot compliant control algorithm is used to establish the dynamic relationship between the yarn tension and the kinematic parameters of the robot 101 when the robot 101 draws and splices the yarn, so that the tension on the yarn 103 is maintained near the desired tension value during the entire splicing process. .

In this embodiment, the kinematic parameters of the robot 101 include the pose, velocity and acceleration of the end of the robot 101, and the force tracking admittance control model described above is shown in the following formula (1):

代表机器人101完成接头动作的期望轨迹的位姿、速度、加速度；X(t)、

代表机器人101的实际运动位姿、速度、加速度；F_d(t)代表接头过程中的期望张力；F_e(t)代表接头过程中通过张力传感器104测得的实际张力。In formula (1), M _d , B _d , K _d are the predetermined expected robot inertia, expected damping and expected stiffness matrix, and the dimension of the expected stiffness matrix depends on the degrees of freedom of the robot 101; X _d (t),

The pose, velocity, and acceleration representing the desired trajectory of the robot 101 to complete the joint action; X(t),

represents the actual motion pose, speed, and acceleration of the robot 101; F _d (t) represents the expected tension during the jointing process; F _e (t) represents the actual tension measured by the tension sensor 104 during the jointing process.

The formula (1) is Laplace transform to obtain the following formula (2):

It can be seen from equation (2) that in the piecing process, when there is a deviation ΔF between the actual tension _{Fe (t) of the yarn 103 and the expected tension F d (} t), the deviation ΔF is input into the force tracking admittance control model. The kinematic parameters X(s) of the robot can be obtained, and the force deviation ΔF can be reduced by changing the kinematic parameters of the robot. Negative feedback regulation is thus formed until the actual tension of the yarn follows the desired yarn tension.

In order to establish the force tracking admittance control model shown in formula (1), in this embodiment, M _d , B _d and K _d are calculated in the simulation environment. In the simulation environment, F _e (t) is expressed by the following formula (3):

表示纱线103的环境速度；K_e表示纱线103的纱线刚度。In formula (3), _{Be represents the damping coefficient between the yarn drawing device 102 and the yarn 103; X e (} t) represents the environmental position of the yarn 103;

represents the ambient speed of the yarn 103; _Ke represents the yarn stiffness of the yarn 103.

均为0，此时由式(1)可以求得力跟踪导纳控制模型的参数K_d，再根据二阶系统的动态特性确定M_d、B_d，进而建立如式(1)所示的力跟踪导纳控制模型。When the simulated automatic joint robot compliance control device reaches a steady state,

are all 0. At this time, the parameter K _d of the force tracking admittance control model can be obtained from equation (1), and then M _d and B _d are determined according to the dynamic characteristics of the second-order system, and then the force shown in equation (1) is established. Tracking admittance control model.

In order to apply the robot compliance control algorithm in the actual automatic joint robot compliance control device, the differential equation of equation (1) is written in the form of the difference equation shown in the following equation (4):

In formula (4), nT represents the nth control cycle, n=1, 2, 3..., T is the sampling frequency.

The PID controller is used to adjust the deviation ΔF between the actual tension and the desired tension, ΔF=F _e (nT)-F _d (nT). In the industrial process, the ideal PID control law of the continuous control system is expressed as the following formula (5):

In the formula (5), u(nT) is the output signal of the PID controller; k _o is the proportional gain, and k _p has a reciprocal relationship with the proportionality; T _t is the integral time constant; T _D is the differential time constant; e(nT ) is the difference between the given value r(nT) and the measured value, the given value r(nT) is the expected tension, and the measured value is the actual tension.

Similarly, the PID controller shown in Equation (5) is written into the differential equation form shown in Equation (6) below:

加速度

In formula (6), e(nT) represents the deviation between the actual tension and the expected tension in the nth control cycle; E(nT) represents the sum of the deviations of all tensions in the nth control cycle; k _p , k _i , k _d represent the proportional coefficient, integral coefficient and differential coefficient of PID control respectively; u(nT) represents the control amount passed by the PID controller to the force tracking admittance control system in the nth control cycle; F _e (nT) represents the nth The actual tension measured by the tension sensor during the splicing process of the control cycle; F _d (nT) represents the desired tension during the splicing process of the nth control cycle. According to Equation (4), Equation (5) and Equation (6), a program is written to complete the robot compliance control based on yarn tension feedback, and the kinematic parameters of the robot are obtained, including the pose X _d (t), the speed during the robot joint process

acceleration

For the industrial-grade six-axis robot used in this embodiment, the Cartesian space coordinates output by the force tracking admittance control model are converted into the angles θ ₁ , θ corresponding to each joint of the robot through the inverse kinematics of the robot known to those skilled in the art ₂ , θ ₃ , θ ₄ , θ ₅ , θ ₆ , and send this group of joint angles to the robot to complete the motion control of the robot, which includes the following steps:

Equation (7) is the coordinate transformation matrix of two adjacent joints of the robot:

For the industrial-grade six-axis robot used in this embodiment, the coordinate transformation matrix between any two adjacent connecting rods of the robot is sequentially obtained from the formula (7), as shown in the following formula (8):

Thus, the transformation moment between the end effector coordinate system and the base coordinate system is obtained as shown in equation (9):

Then, the joint angles θ ₁ , θ ₂ , θ ₃ , θ ₄ , θ ₅ , θ ₆ corresponding to the kinematic parameters calculated by the force tracking admittance controller are obtained through inverse matrix transformation, and the joint angles are sent to the robot. , the robot moves to the specified pose.

As shown in FIG. 3 , the structure of an automatic ring spinning piecing method and device based on tension feedback control according to an embodiment of the present invention includes a robot 101, a yarn drawing device 102, a yarn 103, a tension sensor 104, an industrial computer and a Yarn tension feedback robot compliance control algorithm; the robot 101 is used to pull the yarn 103 to complete the automatic piecing work of the entire ring spinning spun yarn; the yarn pulling device 102 is assembled at the end of the robot 101, the yarn 103 passes through the yarn feeding device 102 and is held by the yarn feeding device 102; the tension sensor 104 is assembled at the end of the yarn feeding device 102, and is used to upload the yarn tension data obtained in real time during the entire piecing process To the industrial computer; the robot compliance control algorithm based on yarn tension feedback adjusts the kinematic parameters of the robot 101 in real time according to the tension data fed back by the tension sensor 104, and the kinematic parameters of the robot 101 include the robot end pose, velocity and acceleration.

According to the actual working environment of the ring spinning frame, the automatic piecing action of the robot 101 is designed to obtain the original position control trajectory of the piecing action of the robot 101, and the original position control trajectory is used as the robot compliance based on the yarn tension feedback. The reference trajectory of the control algorithm; obtain the environmental information interacting with the robot 101, including the yarn stiffness _ke , the environmental position x _e , and the damping coefficient b _e between the yarn pulling device 102 and the yarn 103; to be When the tension tracking control system reaches a steady state, the parameter K _d of the force tracking admittance control model is obtained, and then according to the dynamic characteristics of the second-order system, M _d and B _d are determined by simulation and experiment, and the force tracking admittance control model is established. .

During the piecing process, the robot compliance control algorithm based on the yarn tension feedback calculates the kinematic parameters of the robot 101 according to the real-time acquisition of the tension data of the yarn 103 by the tension sensor 104, and obtains the kinematic parameters of the robot 101 through the inverse kinematics algorithm of the robot. Each joint angle within one control cycle is sent to the robot 101, and the robot 101 moves according to the kinematic parameters to perform the automatic piecing work of ring spinning; finally, it is judged whether the piecing work is completed, and if it is not completed, it continues to execute, and if it is completed, the program Exit, the compliant control piecing robot based on yarn tension feedback completes the automatic piecing of ring spinning.

Claims (3)

1. an automatic piecing robot compliance control device based on tension feedback, is characterized in that, comprises a robot, and the end of robot is provided with a yarn drawing device, and the yarn drawing device end is provided with a tension sensor, and the yarn passes through the yarn drawing device and is provided with a yarn drawing device. Holding, the robot pulls the yarn through the yarn feeding device to complete the automatic piecing work of the entire ring spinning spun yarn; during the entire automatic piecing process of the ring spinning spun yarn, the actual tension of the yarn is obtained in real time through the tension sensor and uploaded to the industrial computer. , the industrial computer runs the robot compliance control algorithm based on the yarn tension feedback based on the force tracking admittance control model and the PID controller. The dynamic relationship between the kinematic parameters keeps the tension on the yarn close to the desired tension value throughout the automatic piecing of ring spun yarns, where: After the industrial computer receives the actual tension, the robot compliance control algorithm uses the force tracking admittance control model to obtain the kinematic parameters of the robot in the Cartesian space, and uses the robot inverse kinematics algorithm to convert the kinematic parameters into each joint angle of the robot; industrial control The machine sends each joint angle to the robot, so that the robot moves to the specified position and completes the motion control of the robot, thereby indirectly controlling the yarn tension during the piecing process to keep the desired tension value near the desired tension value, preventing the piecing failure caused by the yarn breakage during the piecing process. ;In this process, the robot compliance control algorithm introduces a PID controller to adjust the dynamic and steady-state tension tracking performance of the force tracking admittance control model when the environment changes; The kinematic parameters of the robot include the position, velocity and acceleration of the robot end, then the force tracking admittance control model is shown in the following formula (1):

In formula (1), M _d , B _d , K _d are the predetermined expected robot inertia, expected damping and expected stiffness matrix, and the dimension of the expected stiffness matrix depends on the degree of freedom of the robot; X _d (t),

represents the position, velocity, and acceleration of the desired trajectory of the robot to complete the joint action; X(t),

Represents the actual motion position, speed, and acceleration of the robot; F _d (t) represents the expected tension in the joint process; F _e (t) represents the actual tension measured by the tension sensor in the joint process; In order to facilitate the application of the robot compliance control algorithm based on yarn tension feedback in the actual sampling-based control system, the differential equation of equation (1) is written in the form of the differential equation shown in equation (2) below

In formula (2), nT represents the nth control cycle, n=1, 2, 3..., T is the sampling frequency, so as to obtain the acceleration during the nth control cycle of the robot joint process

Velocity during robot jointing in the n+1th control cycle

and the position X((n+1)T) during the robot joint process of the n+1th control cycle. 2. The automatic joint robot compliance control device based on tension feedback according to claim 1, wherein when the force tracking admittance control model reaches a steady state,

are all 0, at this time, the parameter K _d of the force tracking admittance control model is obtained by formula (1), and then M _d and B _d are preliminarily determined according to the dynamic characteristics of the second-order system and the system simulation results; Then the force tracking admittance control model is simulated based on the calculated parameters K _d , M _d , B _d , M _{d and B d are continuously adjusted according to the simulation results, and finally the M d and} B _d with the best force tracking effect are selected _. the value of; During simulation, the environmental dynamics model is used to simulate _Fe (t), which is expressed by the following formula (3):

In formula (3), _{Be represents the damping coefficient between the yarn drawing device and the yarn; X e (} t) represents the environmental position of the yarn;

represents the speed of the yarn; _Ke represents the yarn stiffness of the yarn. 3. a kind of automatic joint robot compliance control device based on tension feedback as claimed in claim 1 is characterized in that, in order to improve the tension tracking robustness of force tracking admittance control model, described PID controller is used for regulating force tracking The dynamic and steady-state tension tracking performance of the admittance control model when the environment changes, e(nT)=F _e (nT)-F _d (nT), the ideal PID control law of the continuous control system is expressed as the following formula (4):

In Equation (4), u(nT) represents the control amount passed by the PID controller to the force tracking admittance control model in the nth control cycle; k _p is the proportional coefficient of PID control; T _t is the integral time constant; T _D is the differential Time constant; e(nT) is the deviation between the actual tension and the expected tension in the nth control cycle; The PID controller shown in Equation (4) is written in the form of the difference equation shown in Equation (5) below:

In formula (5), E(nT) represents the sum of the deviations of all tensions in the nth control cycle; k _i and k _d represent the integral coefficient and differential coefficient of PID control respectively; F _e (nT) represents the nth The actual tension measured by the tension sensor during the splicing process of the control cycle; F _d (nT) represents the desired tension during the splicing process of the nth control cycle.

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