Fuzzy control method of sealing temperature of the

Fuzzy control method of sealing temperature of plastic packaging machine

Abstract: This paper discusses the use of single chip microcomputer to control the sealing temperature of plastic packaging machine, using the method of high-precision thermocouple temperature measurement and fuzzy control method of temperature, which has the characteristics of high temperature control accuracy and stable temperature control, and has achieved good control effect in practice

key words: fuzzy control; Thermocouple; SCM

Introduction

when the plastic packaging machine is working, the sealing temperature will directly affect the product quality. If the temperature is too high or too low, it will cause product defects and affect the beauty of the product. Therefore, in the packaging machine, the temperature control of sealing is very important. In the process of developing the control of the packaging machine, we use the single chip microcomputer to control the sealing temperature of the plastic packaging machine separately. In order to achieve better temperature control effect, we use the fuzzy control method. The test shows that the system has the characteristics of high temperature control accuracy and stable temperature control, and has achieved good control effect

1 composition of the system

figure enhancing the safety of electric vehicle 1 gives the control structure of the system. The whole device is composed of four parts: thermocouple temperature measurement part, fuzzy control part, output control part and single chip microcomputer system. The single chip microcomputer in the figure adopts atmelr AT89C51, which has 4K flash program memory, 128 bytes ram, 32 i/o port lines, 2 16 bit timers and a full duplex serial port. With a strong command system and the support of better development tools, it is enough to complete the task of controlling the sealing temperature of the packaging machine. In this control, thermocouple is used as the sensor of temperature measurement, the measured temperature parameters are treated as the input of fuzzy control, and the output control quantity is obtained by fuzzy algorithm, which is used to control the heating power of sealing heating device to realize temperature control

2 accurate measurement of temperature

in the temperature control of the packaging machine, thermocouples are used as temperature sensors. Thermocouple has the characteristics of simple structure, large temperature measurement range and fast response, so it is widely used. However, the thermocouple also has some shortcomings, such as output nonlinearity, and the measured temperature is related to the cold end temperature of the thermocouple

temperature measurement is composed of multi-channel switch, amplifier for small signal instrument, a/d converter and cold end temperature measurement circuit, as shown in Figure 2. The a/d conversion circuit in the figure uses a serial 12 bit: a/d converter TLC2543 with multi-channel input. The instrument amplifier adopts high-precision ad620n. AD590 is used as the measuring sensor for cold end temperature measurement

with this method, accurate temperature measurement results can be obtained in a wide temperature range

3 basic structure and algorithm of fuzzy control

while measuring the accurate temperature value, it is necessary to have a good control algorithm to complete the temperature control of the sealing of the packaging machine. In this device, fuzzy control method is used for control

3.1 fuzziness

in this system, fuzziness is to discretize the precise value of the input variable into an element in the set integer universe. The difference e between the required set temperature ts and the temperature T measured by the thermocouple is taken as one input of fuzzy control, and the change rate of u △ e=de/dt is taken as another input of fuzzy control. The output 'is also an important part of the country to promote the structural reform of the supply side and implement the conversion of old and new dynamic energy to control the output of pulse width modulation PWM circuit, The PWM circuit outputs pulses with corresponding pulse width according to this value to control the heating power

3.2 membership function and language change should be checked regularly; Determination of quantity

the linguistic value of the difference variable, the change rate of the difference and the fuzzy quantity of the output control quantity is divided into seven grades (negative large, negative medium, negative small, zero, positive small, positive medium and positive large), which are expressed by symbols as: NB nm NS Ze PS PM Pb; The membership function of fuzzy subset selects the membership function of triangular waveform to assign value to e △ e U. The membership function of input and output fuzzy subsets is shown in Figure 3

3.3 design of fuzzy control rules

the control rules of fuzzy controller are based on the experience and skills of experts or operators. There are many methods to generate control rules. Here, manual control experience is used, that is, it is determined according to the response of system step signal. The following fuzzy control rule table is obtained, as shown in Table 1. The fuzzy control rule table represents a group of control rules and represents the fuzzy relationship of the fuzzy system. From the control rules, the fuzzy relationship matrix R can be obtained. Its form is:

3.4 fuzzy reasoning

in this system, because the physical quantity processed is temperature, the response is not required to be very fast. Therefore, the method of activating rule reasoning can be selected to realize the real-time processing of fuzzy control, that is, the real-time processing process of fuzzification rule calculation defuzzification is adopted. The method of activating rule reasoning is to activate each rule in turn according to the input quantity. For each rule, calculate the membership degree of the input to each membership function, that is, fuzziness, and take the minimum value as the recommended value of the rule to the output quantity. Then, the recommended values obtained from all the rules are combined, and the area center of gravity method is proposed to solve the problem, so as to obtain the output of fuzzy control at the time of input. The advantage of this method is that it occupies less memory and is easy to adjust. It can be used in more complex fuzzy reasoning systems. The output obtained by fuzzy rule reasoning is used to control the output of PWM circuit. (end)