Plastic packaging machine sealing temperature control
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 defects of the product and affect the appearance of the product. Therefore, in the packaging machine, the temperature control of the seal is very important. In the process of developing the packaging machine control, 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, the fuzzy control method is adopted. After testing, the system has the characteristics of high temperature control precision and stable temperature control, and has achieved good control effects. Fuzzy reasoning
System composition
The whole device is composed of tempering temperature measuring part, fuzzy control part, output control part and single-chip computer system. The single chip in the picture adopts AtmelrAT89C51, which has 4K FLASH program memory, 128 bytes of RAM, 32 I/O ports. Line, 2 16-bit timers and a full-duplex serial port. It has a strong command system and is supported by better development tools, which is enough to complete the control task of the sealing temperature of the packaging machine. The control uses a thermocouple as a sensor for temperature measurement. The measured temperature parameter is processed as the input of the fuzzy control, and the control amount of the output is obtained by the fuzzy algorithm for controlling the heating power of the sealing heating device to realize the temperature control.
Accurate measurement of temperature
In the temperature control of the packaging machine, a thermocouple is used as the measuring temperature sensor. Thermocouples are widely used because of their simple structure, large temperature range and fast response. However, thermocouples also have output nonlinearities, and the measured temperature is related to the cold junction temperature of the thermocouple.
The temperature measurement consists of a multiplexer, a small signal amplifier, an A/D converter, and a cold junction temperature measurement circuit. The A/D conversion circuit uses a serial 12-bit with a multi-channel input: A/D converter TLC2543. The instrument amplifier uses the high precision AD620N. The cold junction temperature was measured using the AD590 as a measurement sensor.
By measuring temperature in this way, accurate temperature measurements can be obtained over a wide temperature range.
Basic structure and algorithm of fuzzy control
While measuring accurate temperature values, a good control algorithm is needed to complete the temperature control of the packaging machine seal. In the present device, the method of fuzzy control is used for control.
Fuzzy
In this system, fuzzification is to discretize the exact value of the input variable and become an element in the set integer domain. The difference E between the set temperature ts required to be reached and the temperature t measured by the thermocouple is taken as the change rate ΔE=dE/dt of one input quantity U of the fuzzy control as another input quantity of the fuzzy control, and the output quantity ' It is used to control the output of the pulse width modulation PWM circuit, and the PWM circuit outputs a pulse of a corresponding pulse width according to this value to control the magnitude of the heating power.
3.2 Determination of membership function and linguistic variables
The language value of the difference variable, the rate of change of the difference, and the amount of blur of the output control amount are divided into 7 files (negative large, negative medium, negative small, zero, positive small, medium, and large), which are symbolized as: NBNMNSZEPSPMPB The membership function of the fuzzy subset is assigned to Eâ–³EU using the membership function of the triangular waveform.
Design of fuzzy control rules
The control rules of fuzzy controllers are based on the experience and skills of experts or operators. There are many methods for generating control rules. Artificial control experience is used here, which is determined according to the response of the system step signals.
The fuzzy control rule table represents a set of control rules, which characterizes the fuzzy relationship of the fuzzy system. The fuzzy relation matrix R can be obtained by the control rules.
In this system, since the physical quantity of processing is temperature, the response is not required to be very rapid. Therefore, the method of activation rule inference can be used to realize the real-time processing of fuzzy control, that is, using fuzzy--rule calculation--fuzzification Real-time processing. The method of initiating rule reasoning is: sequentially activating each rule according to the input quantity, and for each rule, calculating the membership degree of the input to each membership function, that is, fuzzification, and taking the minimum value as the recommended value of the rule for the output. Then, the recommended values ​​obtained by all the rules are combined and solved by the area center of gravity method to obtain the output of the fuzzy control at the time of input. The advantage of using this method is that it occupies less memory and is easy to adjust, and can be used in a more complicated fuzzy inference system. The output obtained by fuzzy rule inference is used to control the output of the PWM circuit.