Starting from the problems of motor not reaching rated load and low efficiency utilization, this paper uses the theory of fuzzy control to control various situations of thyristor by conduction angle, so as to reduce the voltage at both ends and improve the power factor of motor, so as to achieve the purpose of energy saving under light load. The PID controller was born in 1915. Recently, there are many kinds of control methods.
However, the PID controller has always been superior. It has many advantages, such as strong robustness, simple structure, good stability and easy operation. It has been widely used in industrial process control. Fuzzy control is widely used in engineering, and its theoretical research is particularly fast. It is an intelligent control, very active, research and application in the field of control. The control of fuzzy set theory is a very useful control method. Fuzzy control is of immeasurable value to industry. We can analyze the following two situations: (1) Fuzzy is a new mechanism proposed to deal with the law of control field. It is a narrative process of knowledge and even semantic description; (2) Nonlinear controllers and fuzzy controllers have proposed a relatively easy method to solve the uncertainty of the system, especially when the controlled device contains non-linear and especially difficult to use laws to measure, the fuzzy control is quite effective at the moment. After the emergence of ordinary sets, there are more and more application limitations.
Different fuzzy sets theory is the extent to which the universe conforms to conceptual elements. 0 and 1 can not be absolutely fuzzy, but are real numbers between 0 and 1. In the fuzzy set theory, we know that the importance of status is determined by the fuzzy relationship between quantities, which is the most basic general relationship between each numerical element. Whether they are related or not, to what extent, they need to be blurred by our new control. In manual control, the controlled object is the quantity that is executed. We can collect these information and quantify it numerically. Then we can analyze it through our mind. We rely on the original knowledge to summarize and judge, and combine expert experience analysis and comprehensive utilization to get the corresponding numeric quantity operation controller. We need a process to precise numeric quantity to fuzzy quantity.
In this way, we can use the existing linguistic rules, control experience and expert decision-making knowledge.
Then we input this kind of transformation into the computer, and our ideas are imitated to perform some phenomena of control operations, so that the controlled objects can be controlled, thus forming a fuzzy control system. In many industrial control systems, many manual control is the most basic manual control, but for the ultra-fine and accurate model we encounter, the model of the control object must be complex, then ordinary control rules are difficult to accurately implement the operation of this process, but if the operating staff can operate the system very accurately, the idea is vague. The rules, the strategy of controlling the target, the rules of controlling the magnetic field impact, and the emergence of the key problems are not easy. Moreover, the manual process is not very precise. The basic idea of our operator is not formed in a day. It is formed through the continuous learning and the accumulated knowledge principle accumulated by previous experts. The way of control is to store the knowledge of technology, and use our own words to control.
The way of extracting useful information can be in the form of manual control, which can make the desired rules by fuzzy control.
Then the control goal of the system can be realized. The core is the rule we mentioned earlier, that is, the fuzzy rule. Now the key question we have to consider is how to build it. We know that the starting problem of motor operation, the current will rise very quickly at the beginning, and the rapid reduction of voltage will certainly have a great impact on the magnetic field of stator rotation. In fact, the motor will experience strong current, which is quite harmful to the rotor. It can be seen from the above that this situation has a great impact on the service life of the motor. As a result, the problem of soft start is naturally thought of for reducing voltage and saving energy of motor. Speaking of soft startup, we also consider this aspect in the design paper. With constant current as the main idea, we have studied quite simple methods.
The following are introduced respectively: (1) the given value is calculated by slowly increasing its conduction angle; (2) the feedback current is continuously detected by the instrument, and the values detected many times are compared with the given value. The stator terminal current and the set value larger than the given value will stop increasing the angle. If no current is detected later, the angle of the current will be increased quantitatively and gradually again in view of this phenomenon, so that the motor with constant current can be soft-started. The determination of fuzzy rules and the realization of fuzzy reasoning should be formulated through actual hardware operation. For energy saving, it is a non-linear term. This can not be achieved by traditional control methods in energy-saving control of motors. Firstly, the sampling fuzzy control method and the system’s non-linear mathematical model should be established. Then, according to the error control of the set value, the theoretical input variables and the characteristics of the motor, an ideal control model should meet our control requirements and be able to save energy, unless it can avoid all kinds of unexpected situations and eliminate all kinds of non-linear effects.
We take the error of EMF and EMF as the output, the angle of conduction and the value of power factor as the other input, and design a two-dimensional fuzzy integrator for the factor of asynchronous motor. According to our observation and measurement, we can reduce the degree of freedom factor of voltage operation and use integral function as input and output variables of numerical value. Then the rule table is well formulated and can be done according to its change rate. Larger. Display circuit and over-current problem, the relationship between the three phase voltages measured by their zero-crossing points and the phase current, calculating the asynchronous motor of the fuzzy controller, and dealing with their power factor angle, what we do is to save energy, the method is to reduce the voltage, so as to reduce the starting current. The key problem is how to achieve this, how to control the angle of conduction, we use pulse control bidirectional thyristor, so that we can meet the requirements. This involves the main control circuit, current and voltage sampling circuit, power factor angle detection circuit and trigger circuit, bidirectional thyristor circuit and controller power supply circuit, plus LED display circuit and over-current protection circuit. Selection of main control chip and thyristor module. Whether it is system or design, we will think of the value price and efficiency.
Compatibility performance is very strong through new protection circuit peripheral sampling, higher-level enhanced chips, longer-lived memory.
Program memory is 8 bytes, data trigger circuit is 1024 bytes; data chip memory is 256 double bytes; interrupt generation is done by setting 14 interrupt sources, 10-bit analog to data conversion of 8 branches; the speed of running trigger circuit is very fast, clock chip pulse input, these performances can satisfy me very well. Our system settings are required. The chip of the power supply uses 5 volts of direct current to provide power supply, while 12 volts of direct current mainly supplies external power supply. Then the sampling and triggering circuits need to be processed at high speed by 7805 chip, which can ensure the normal power supply. Voltage zero-crossing detection, current zero-crossing detection and over-current protection circuit. In half a cycle, whether the current in the circuit is qualified or not and whether it meets the rated value is analyzed by checking the voltage of the motor, the angle of trigger, the detection of zero-crossing point, etc. Zero-crossing detection circuit, first of all to check the AC 220V voltage zero-crossing generated by the program interruption; Asynchronous timing length of the predetermined start-up change can interrupt the processing subroutine, the timing function used in the program is achieved by a timer, thermostatic element open after the trigger pulse of the CPU. Phase missing protection and phase sequence detection. In the judgment of phase absence, the correct pulse current can be controlled only through the difference of phase sequence in order to control the turn-on sequence of thyristors. When the voltage is obtained by measuring, it is necessary to detect the signal quantity passing through zero point, and it is necessary to detect every phase sequence that flows through, so as to measure their current value, so that there is no need to add any additional circuits. There are many kinds of squirrel cage motors. First, what kind of links should be used in the phase separation? Trigger circuit. Whether the gate in the trigger circuit can be triggered reliably or not, whether the energy-saving controller designed by us can operate smoothly, and the angle conduction is controlled by the circuit, it must require the circuit to have super-high accuracy and stability. In order to ensure the reliable operation of the circuit, the thyristor control mode needs to be satisfied. The parameters can be corrected by measuring the voltage and current values through triggering pulses. At this time, the conduction time is also affected by the above factors. We have designed the amplifier circuit in the system, which requires accurate control design.
In order to trigger the pulse width, a control amplifier circuit is used, which is a triode trigger control circuit. The hardware anti-interference technology of the system. The working environment of motors is varied, and the degree of complexity and harshness varies. As a design, many aspects should be considered. Safe operation, accurate and reliable work is a very prominent issue that we pay attention to. In the process of design and manufacture, we should avoid all kinds of electrical interference from inside and outside of the system as far as possible. The main factors of reliable and safe operation of the system are determined by the structure design and installation of the system and the external environment conditions, etc. We should adopt corresponding ways to ensure its operation. Fuzzy control is applied to an asynchronous motor energy-saving controller. Fuzzy control method is used to feedback the power factor, so that we can achieve our goal of saving energy. In the design of this system, the commonly used fuzzy control method is adopted, which not only saves energy, but also keeps the stable operation of the motor. Of course, we have only solved a small part of the problem. In the practice of production, we will encounter many problems. For example, although the energy-saving problem of motor has been achieved, its reaction speed in operation is relatively slow, two aspects can not meet the requirements at the same time, its work has limitations, and various details will often be encountered in the actual operation, which requires our efforts to study. To do better.