Fuzzy control for proportioning and regulating sintered material
Abstract
The sintering process is a critical process in modern metallurgy, which not only directly affects the quality of metallurgical products, but also affects the safety of production. Therefore, accurately controlling the proportioning and dosage of sintered material is essential. As a mature control technology, fuzzy control technology has a very good application effect in various control algorithms. In this paper, fuzzy control technology was used for proportioning and regulating sintered material. The fuzzy control strategy was designed. The control performance of the sintering process was evaluated with concrete examples. The results showed that compared with the traditional PID control, fuzzy control can achieve better control effect and regulate sintering process more accurately.
Key Words: sintering process, fuzzy control, proportioning and controlling
1. Introduction
Sintering is a commonly used metallurgical process characterized by the use of chemical metallurgy processes to harden and solidify metals and other materials. In this process, the chemical compounds of the material are combined to form sintered ore and then sintered into one solid shape. The process of sintering plays an important role in the development of industrial production. It not only affects the quality of the end product, but also has a great influence on the safety of production. Therefore, accurate control of the proportioning and dosage of sintering materials is essential.
At present, with the development of modern control technology, fuzzy control technology is gradually applied to the field of control theory. As a mature automatic control method, fuzzy control technology has achieved wide application in various control systems. It can effectively identify the nonlinear characteristics of the system and improve the control accuracy.
Therefore, this paper uses fuzzy control technology for proportioning and adjusting sintered material, and designs a fuzzy control strategy for sintered material proportioning and adjusting. And through a concrete example to evaluate the performance of the sintering process.
2. Fuzzy Control Theory
Fuzzy control is a kind of control technology that has been developed for many years since the 1960s. It is based on fuzzy set theory, which has strong ability of processing rules and reasoning. It can simulate the intuition of human experts and provide the best control results by making decisions.
The core of fuzzy control theory is fuzzy set which is the core concept of fuzzy control theory. Fuzzy sets contain the information and knowledge of the fuzzy characteristics of the world. The corresponding fuzzy set can be obtained by analyzing and describing the problem, then formation of the fuzzy logic control system.
Fuzzy logic control consists of three basic steps: fuzzification, fuzzy reasoning and defuzzification. Fuzzification is the conversion of crisp input and output variables into fuzzy variables. Fuzzy inference is a process of reasoning fuzzy variables and fuzzy rules. Defuzzification is the process of converting fuzzy output variables into crisp output values.
The advantages of fuzzy control can be summarized as follows:
1)Fuzzy control has good adaptability, better systematization and clear process, which can represent the uncertainties of the system in a general way;
2)Fuzzy control has strong robustness, which not only reduces the sensitivity to parameter changes of the system, but also has a certain degree of immune to external noise;
3)Fuzzy control system has strong fault tolerance performance, it can adapt to the continuous changes of system parameters and fault diagnosis, so as to ensure the normal operation of the system;
4)Compared with other control algorithms, fuzzy control has high control accuracy and short time delay.
3. Design of fuzzy control strategy
Usually, a fuzzy control strategy consists of three parts: fuzzification, fuzzy reasoning, and defuzzification. Generally, seven steps are needed to complete a fuzzy control strategy.
(1) Fuzzification: All inputs and output variables should be fuzzified first. In order to effectively control sintering process, this paper needs to calculate the differences between current peeling force and target peeling force, and then convert them into membership functions.
(2)Fuzzy rules: Fuzzy control comes from expert experience, which means that we can create a set of rules for fuzzy control by analyzing the characteristics of the process. This paper uses a set of fuzzy rules to represent the relationships between inputs and outputs.
(3)Fuzzy reasoning: According to the preceding fuzzification and the establishment of fuzzy rules, fuzzy reasoning process is used to derive the values of control parameters.
(4)Defuzzification: After fuzzy inference, the output of a fuzzy control system is fuzzy and lacks precision. The values of the control parameters obtained from the fuzzy control system should be converted from a fuzzy set to a precise value.
(5)Adaptive adjustment: In order to obtain better control results, adaptive adjustment of fuzzy control parameters needs to be conducted.
(6)System implementation: The fuzzy controller is established according to the above design steps, and then implemented by MATLAB software.
(7)Evaluation of control results: Finally, the control results of the sintering process need to be evaluated.
4. Case Study
In this study, a fuzzy control method was used to control the sintering process and the process variables of the sintered material proportioning and dosing. The temperature, humidity and peeling force of the sintering materials are taken as input variables, and the output is the fuzzy control signals of the proportioning and dosing of sintered material. The proposed fuzzy control strategy is simulated using MATLAB and the results are compared with traditional PID control.
The experimental data used in this study are taken from a practical sintering experiment. The results of the simulation are shown in Figure 1 and Figure 2.
Figure 1
Simulation results of peeling force of sintered material
Figure 2
Simulation results of feed amount of sintered material
From the simulation results, it can be seen that the fuzzy control algorithm achieved a better control effect and can precisely regulate the sintering process. Comparing the fuzzy control with traditional PID controlling, the fuzzy control algorithm can control the sintering process more accurately and effectively, thus achieving better performance.
5. Conclusion
In this paper, fuzzy control was used for proportioning and regulating sintered material in order to ensure the quality and safety of sintering process. The fuzzy control strategy was designed and the control performance of the sintering process was evaluated with concrete examples. The results showed that compared with the traditional PID control, fuzzy control could achieve better control effect and regulate sintering process more accurately. In addition, it can be concluded that due to its high control accuracy and short time delay, fuzzy control is an ideal solution for proportioning and regulating sintered material.
