Influence Factors and Compensation of Pneumatic Cylinder Crawling in Low-Speed Motion

Abstract：Through the establishment of aerodynamic model and the joint simulation，pneumatic cylinder crawling at low speed and the source of location error were discussed. Air source pressure，mass of load，and friction difference influence on pneumatic cylinder crawling were analyzed. System is controlled by single neuron PID and adding vibrating signal instead of traditional PID. The results show that big air source pressure，small mass of load，and small difference of static and dynamic friction can help prevent the crawling. And system crawling was solved using single neuron and vibrating signals. It is confirmed that positioning accuracy was improved from ±0.61mm to ±0.25mm by simulation. It provided a more ideal control strategy for pneumatic cylinder smooth running at low speed.

1 Introduction

As the most common actuator in pneumatic system, cylinder is widely used in automatic production. In many industrial applications, it is often necessary to drive at low speed. However, when the cylinder is moving at low speed, due to the influence of cylinder friction resistance and gas compressibility, it often appears the alternating movement of “stop and go” or “fast and slow”, which is called “crawling phenomenon” [1]. The crawling of the cylinder will not only produce a lot of noise and seriously affect the environment, but also lead to the instability of the system and reduce the accuracy of the system.

Literature [2] studies the effect of adding nano particle lubricant to the cylinder lubricant on improving the friction of the cylinder, which greatly reduces the creeping phenomenon of the cylinder. In reference [3], a flutter signal composed of a series of low amplitude pulse signals is superimposed on the controller to compensate the friction of the cylinder; in reference [4], a new type of low friction cylinder is designed, which largely eliminates the problem of low-speed crawling of the cylinder. In order to study the influence trend of the main factors of cylinder crawling and eliminate its influence on the motion state of the pneumatic system, the rodless cylinder system is modeled and co simulated. The single neuron control and superimposed flutter signal control method are adopted to achieve the purpose of solving the crawling phenomenon stably.

Analysis on mechanism and influencing factors of creeping phenomenon of 2 cylinder

2.1 cylinder creeping mechanism

The air source fills a cavity of the air cylinder, and the air cylinder moves under the action of the gas. Due to the influence of the static friction on the inner wall of the piston, when the pressure in the intake chamber reaches a certain value, the thrust overcomes the static friction and the cylinder moves. At this time, the static friction changes into a smaller dynamic friction, while the pressure in the cylinder decreases due to the expansion of the volume, resulting in the pressure less than the dynamic friction, that is, the thrust is less than the resistance, and the cylinder stops gradually; with the air supply, when the pressure in the intake chamber increases again After that, the piston can be pushed to move again, and the cycle of the process forms the crawling of the cylinder.

2.2 influencing factors of cylinder creep

By analyzing the characteristics of the cylinder structure and pneumatic system, it can be concluded that the crawling phenomenon is related to the compressibility of the gas, the main components of the system and the friction of the cylinder. The main factors affecting the crawling of the cylinder are summed up as: air pressure, load, friction characteristics.

  1. Modeling and Simulation of pneumatic system

3.1 pneumatic system model

Taking pneumatic proportional valve controlled rodless cylinder as an example, the model is established. For this kind of nonlinear system, which is difficult to establish accurate model, the advantages of AMESim in graphical modeling are used to establish aerodynamic simulation model. AMESim provides pneumatic library and PCD. Users can use the existing components in the standard library or the combination of component sub models of PCD library to build the required model according to their own simulation purposes [6].

According to the PCD library, a rodless cylinder and a three position five way proportional valve are constructed to connect the pneumatic circuit, as shown in Figure 1. The pressure is provided by the air source, and the gas flow is sent to a cavity of the rodless cylinder through the proportional directional valve. Under the control of the control system, the proportional valve adjusts the opening of the valve port to control the flow and drive the cylinder. A displacement sensor is set at the cylinder, and the position of the cylinder is fed back to the control system through the joint port, which is compared with the target displacement and adjusted in real time to form a closed-loop system The system realizes the cylinder positioning and track tracking.

Pneumatic cylinder
Fig. 1 model of pneumatic system based on AMESim.

The parameters of the sub model are as follows: (1) rodless cylinder: piston diameter 25 mm; piston mass 0.37 kg; stroke 450 mm; viscous friction coefficient C 90 NS / m. (2) Proportional directional control valve: the displacement of valve core is 2.5 mm; the fit between valve core and valve sleeve is negative opening, the covering amount is – 0.1 mm at zero displacement; the mass of valve core is 0.021 kg; the diameter of valve core piston is 11 mm, and the diameter of piston rod is 7 mm.

3.2 co simulation

Matlab / Simulink is a well-known integrated environment in the field of dynamic system simulation; AMESim has a more accurate model, which avoids the error of mathematical modeling, and co simulation using the advantages of the two softwares is helpful to better understand the system performance. The loop model of pneumatic system is established in AMESim, and the control system model is established in Simulink. The dynamic characteristics of the two models are simulated and analyzed jointly [7]. The input displacement signal is slope signal, unit: mm, initial value is 20, slope is 10; the adjusted PID parameters are 50, 50, 6, gain K is 50. In the simulation, under the working conditions of 450 mm stroke and 10 mm / s speed, the PID control of pneumatic system is carried out, and the influence of air source pressure, load mass, dynamic and static friction difference on cylinder crawling is analyzed.

(1) The influence of air source pressure. When the load mass is 2kg and the difference between dynamic and static friction is 5N, the gas source pressure is 0.6MPa, 0.4MPa and 0.2MPa respectively. The simulation results are shown in Fig. 2. The effect of air pressure on creeping is not different, and the creeping is more obvious when the air pressure is low. With the increase of pressure, the piston sealing ring clings to the inner wall of the cylinder, resulting in the increase of friction; at the same time, the increase of pressure increases the rigidity of the system composed of the cylinder, gas pipe and valve, which is conducive to preventing the system from crawling. Under the action of double factors, crawling is not sensitive to gas source pressure.

Pneumatic cylinder
Fig.2 Displacement Curves Under Different Air Source Pressures

(2) Load quality. When the air source pressure is 0.6MPa and the difference between dynamic and static friction is 5N, the load mass is 2kg, 5kg and 10kg respectively. The simulation results are shown in Fig. 3. With the increase of load mass, that is, the normal pressure of cylinder increases, the friction of cylinder increases, so the creepage will be more and more serious.

Pneumatic cylinder
Fig.3 Displacement Curves Under Different Masses of Load

(3) The influence of dynamic and static friction difference. When the air source pressure is 0.6MPa and the load mass is 2kg, the dynamic friction of the cylinder is set as 25N, and the static friction is set as 30n (the difference is 5N), 40n (the difference is 15N) and 50N (the difference is 25N). The simulation results are shown in Figure 4. The larger the difference between the dynamic and static friction, the more serious the creep, and this factor has the most obvious effect. Therefore, the maximum static friction of the cylinder is an important feature of the cylinder friction, and the difference between the dynamic friction and the static friction is the main reason for the creep.

Pneumatic cylinder
Fig.4 Displacement Curves Under Different Differences
Between Static and Dynamic Friction

4 single neuron PID control

4.1 single neuron PID

To achieve good control effect, it is necessary to design a controller with excellent performance. Artificial neural network is an important branch of intelligent control method, which is proposed through the simulation of human brain function. It is a mapping relationship from multiple input to single output [8]. Combining single neuron with traditional PID controller, complex system control and time-varying system control can be realized, which is called single neuron adaptive PID controller [9]. According to the nonlinear characteristics of pneumatic system, the single neuron PID control can achieve good control.

4.2 single neuron control simulation

In order to ensure the convergence of the learning algorithm and the robustness of the control, the supervised Hebb learning rule is used for normalization [10]. In the Simulink block diagram, S-function is introduced as the carrier of single neuron algorithm code. According to the fixed program format, the single neuron algorithm is written in C language and embedded into S-function to run. Although the M-file s function of MATLAB is very easy to write and understand, c-MEX s function not only runs faster than M-file, but also can generate independent simulation program.

Fig.5 Displacement Curves Under Single Neuron
and Conventional PID Control

The parameters of PID controller replaced by single neuron control are set as follows: the values of learning rate η P, η I and η D are 80000, 400 and 600 respectively, the initial values of weighted coefficient W1 (0), W2 (0) and W3 (0) are all 0.3, and the neuron proportion coefficient K The simulation results are shown in Fig. 5 under the working conditions of gas source pressure of 0.6MPa, load mass of 2kg, dynamic and static friction difference of 5N, working stroke of 450mm and speed of about 10mm / s. The curves in the figure are target curve, PID control curve and single neuron control curve.

The traditional PID control has obvious crawling phenomenon, while the single neuron PID control can improve the positioning accuracy and crawling by adjusting the weighting coefficients W1, W2 and W3 adaptively. It can also be seen from the figure that although the single neuron control improves the system accuracy, it does not completely solve the crawling phenomenon.

5 superimposed flutter signal control

5.1 advantages of flutter signal compensation

Flutter control is to superimpose a high frequency and unequal amplitude signal on the control signal. Because the difference between the dynamic and static friction is the most fundamental link of the friction effect on the system, from the perspective of mechanics, the high-frequency flutter signal is superimposed on the control signal, so that the valve has enough energy to eliminate the static friction, which can achieve the state of quasi dynamic and non dynamic, so as to ease the crawling. From the point of view of aerodynamics, when there is no flutter signal, the displacement of the low-speed cylinder is fed back to the controller, and its crawling phenomenon is reflected in that the control signal is an oscillation signal. The superimposed high-frequency flutter signal can make the control signal have a higher frequency, so as to overcome the oscillation of the control signal, solve the crawling problem, and change the characteristics of the system in essence. The flutter signal compensation is combined with single neuron control to form a robust controller, which improves the control ability of nonlinear system.

5.2 adding method of flutter signal

The system block diagram after adding flutter signal is shown in Fig. 6 (a).

In the figure: ① – the input displacement of the system, the desired output displacement; ② – the difference between the input and output displacement of the system; ③ – the signal output by the controller and superimposed with the flutter signal to form a signal; ⑤ control by comparing with the sample valve; ⑥ – the proportional valve transforms the spool displacement according to the received signal to supply air to the cylinder; ⑦ – the actual output displacement; Ⅷ – the actual displacement feedback.

The control strategy is implemented in Simulink, and the superimposed signal is introduced in AMESim. The flutter signal is superimposed on the single neuron control quantity, which acts on the proportional valve together, and is superimposed on the basis of Figure 1, as shown in Figure 6 (b). The flutter signal is a sinusoidal signal, and the optimal amplitude and frequency of the sinusoidal signal, namely 400sin35t, are obtained by trial and error method.

Fig.6 Adding Vibrating Signal

5.3 simulation results after compensation

Under the working conditions of air pressure of 0.6MPa, load mass of 2kg, dynamic and static friction difference of 5N, working stroke of 450mm and speed of about 10mm / s, the simulation results of cylinder displacement superimposed with flutter signal are shown in Figure 7. Compared with the curve in Figure 5, the performance of the system at this time has changed significantly compared with that without adding flutter signal. The influence of the difference between dynamic and static friction on the system no longer exists, and the static friction in the system is converted into sliding friction under the effect of flutter signal. The response speed and accuracy of single neuron control are improved, and the crawling phenomenon of cylinder at low speed is overcome. Although the crawling phenomenon disappears after adding flutter signal to traditional PID, the response speed and positioning accuracy are reduced. At the same time, the positioning accuracy of traditional PID is ± 0.61mm, while the positioning accuracy is ± 0.25mm after using single neuron PID and flutter signal control compensation.

Pneumatic cylinder
Fig.7 Displacement Curves After Adding Vibrating Signal

6 experimental verification

Combined with the simulation results, using Ni pci-6251 data acquisition card and LabVIEW software, the low-speed motion of FESTO rodless cylinder is experimentally studied. Under the working conditions of air source pressure of 0.6MPa, no load, working stroke of 450mm and speed of 25mm / s, the results are shown in Figure 8. Based on the single neuron control, the flutter signal is superimposed, which is obviously better than the traditional PID control, and is consistent with the simulation results.

Pneumatic cylinder
Fig.8 Experimental Curves of Two Control Methods

7 conclusion

(1) The co simulation of AMESim and Simulink makes the motion process of the cylinder close to the real object, and the analysis results are more reliable. Through the co simulation analysis of the influence factors of cylinder crawling, large air pressure, small load mass and small dynamic and static friction difference are conducive to prevent the system from crawling; (2) for the phenomenon of cylinder crawling, the method of linear superposition of single neuron PID control signal and flutter signal is used to compensate, which solves the problem of cylinder crawling and improves the positioning accuracy of the system from ± 0.61 mm 25 mm, which lays a foundation for the application of low-speed cylinder in various industries.

Reference

中图分类号：TH16；TH138 文献标识码：A 文章编号：1001-3997（2018）05-0086-03 刘静，朱志松，陈凯聪（南通大学机械工程学院，江苏南通226019）

Rodless Cylinder Application

Application of rodless cylinder in track splitter

[Abstract] this paper introduces the structure and the type selection of rodless cylinder for driving shunting machine with circular ball bearing guide rail and rodless cylinder with middle stop block. The separator can be used in low speed and large capacity bottle filling production line. By using the characteristics of the slider module of the rodless cylinder, the middle limit block can be selected to realize multi-channel separation, and only simple pneumatic control technology is needed. According to this design, the shunter has the advantages of simple structure, easy control and low manufacturing cost.

1. Introduction

The company’s bottling line is generally equipped with a splitter, which divides a single bottle into multiple bottles according to the production requirements [1]. The track splitter is generally driven by servo, with high speed, high precision, high control technology requirements and relatively high manufacturing cost. At present, the company has newly invested a 4.5-liter large capacity bottled water line with a production line speed of 4000 bottles / h, equipped with a buffer conveyor belt for storing three rows of bottles. When the rear equipment fails, the bottles in the filling area will be stored, so as to improve the production efficiency of the whole line and avoid waste. Because the bottles on the buffer conveyor belt are stored in three rows, the distributor should meet the function of three rows. Based on the large size of product container and the low speed of production line, a new technical scheme of lane splitter drive, Rodless cylinder drive, is proposed. Reciprocating pneumatic machinery has the advantages of simple structure, excellent performance, low cost and environmental protection. Its precise position control is widely used in automatic production [2]. With its own slider module, there is no need to design the guiding and anti reverse mechanism, which greatly simplifies the design.

2 Overview

The main machine of the production line is bottle blowing, filling and capping machine, and the back channel is equipped with handle adding machine, labeling machine and other equipment. In order to avoid waste caused by scrap of bottle embryo in the heating area of bottle blowing machine, it is necessary to produce 180 bottles in large quantity when the back equipment fails. Therefore, the bottle blowing, filling and capping machine is equipped with a buffer conveyor belt for storing 180 bottles of products. As shown in the figure below:

RODLESS CYLINDER
  1. Track splitter; 2. Buffer conveyor belt

Figure 1 buffer conveyor belt

The normal production is in the middle a channel. When the faulty bottles in the back channel are piled up to the set position, the channel divider works to transport the products in the filling area to channel B and C in turn for storage. After the trouble is eliminated, the bottles are discharged in the order of a, B and C. After enough storage space is available, the filling machine is started and normal production is started.

2.1 track splitter structure

Fig. 2 shows the splitter driven by rodless cylinder. It is a track splitter driven by rodless cylinder.

RODLESS CYLINDER

Figure 2 structure diagram of track splitter

It is mainly composed of guide plate, Rodless cylinder, middle limit block, position limiter, frame and adjusting components. The middle limit block and position limiter are the auxiliary parts of rodless cylinder, which can be selected in the selection. The middle stop block is installed on the cylinder block, and the position limiter is installed on the sliding block. The adjusting component adjusts the spacing of the guide plate according to the size of the bottle, and is fixed on the sliding block to move with the sliding block so as to swing the guide plate for lane changing. The function of the bottle blocking component is to block the bottle and avoid the bottle jamming when the guide plate swings.

2.2 working principle

During normal production, the middle stop block and position limiter in Figure 2 stop the slider of rodless cylinder in the middle position, and the guide plate is positioned in channel a. When the lane divider receives the lane change signal, the action sequence is: the bottle blocking assembly blocks the bottle, the slider of the rodless cylinder drives the guide plate to swing to Lane B, the bottle blocking assembly resets and the bottle is placed. When channel B is full of bottles, the channel divider receives the signal to divide the bottles into channel C, blocks the bottles in turn, resets the middle limit block, drives the guide plate to swing to channel C by the slider of the rodless cylinder, resets the bottle block and puts the bottles. Note that the cylinder of the middle limit block must be reset, otherwise the slider cannot run to the ? C position. After the bottles in the filling area are emptied, the separator returns to its original position.

Due to the unidirectionality of the position limiter, as shown in Fig. 2, the slider from C to a can not stop at channel a, so it needs to run to position B first and then stop at position a. This is a drawback of rodless cylinder with middle limit block, which should be avoided in design.

Drived by rodless cylinder, it is easy to control as long as the pneumatic technology is grasped.

The schematic diagram of control gas path is shown in Figure 3.

Bottle block cylinder; 2. Middle limit block cylinder; 3. Rodless cylinder

Fig. 3 control gas circuit diagram

2.3 selection of rodless cylinder

There are many manufacturers to choose the rodless cylinder. In this case, FESTO products are used

It is required that the load on the surface of sliding block should meet the following formula:

RODLESS CYLINDER

The meaning of the symbols in the formula is shown in Figure 4.

RODLESS CYLINDER

In this example, FY = 0, MX = 0, MZ = 0, FZ is the weight of the dividing mechanism, my is the torque generated by the friction resistance between the bottle and the chain plate swinging with the guide plate. After calculation, FZ = 410n; my = 45N. M. Select the parameters of cylinder diameter 25 according to the sample

Then according to the relationship curve between the maximum allowable piston speed and the effective load and the distance from the center of gravity of the load, it is found that the cylinder diameter needs to be Φ 40 and the maximum speed is 0.6 m / s. Finally, the cylinder diameter of Φ 40 is selected and equipped with terminal position buffer.

3 conclusion

Drived by rodless cylinder, the shunter makes full use of the characteristics of rodless cylinder, so the design is convenient, the structure is compact, the control is simple, and the cost of manufacture and maintenance is low. It has been used in many production lines of the company, and can fully meet the production requirements.

reference

[1] Sun Yayun. Development of PLC based on ATmegal6 and its application in control of shunter [D]. An

Anhui University, 2015

[2] Feng Lei. Design of precise position control system for reciprocating pneumatic manipulator [J]. Modern property (middle)

Xunjiao, 2018 (2): 34-35