Available online at www.sciencedirect.com
Procedia Engineering 29 (2012) 257 – 261
2012 International Workshop on Information and Electronics Engineering (IWIEE)
Application of Expert Fuzzy PID Method for Temperature
Control of Heating Furnace
SHI Dequan*, GAO Guili, GAO Zhiwei, XIAO Peng
Department of Material Science and Engineering,Harbin University of Science amp; Technology, Harbin 150040, China
Abstract
In order to solve the problem of non-linearity, large delay and time variant of heating furnace, the combination of fuzzy PID control and the expert decision is used to regulate the temperature, and an expert fuzzy PID controller is designed. In this controller, The PID parameters are adjusted by fuzzy reasoning algorithm, so it has self-adapting ability. The expert decision can decrease the temperature shock near the set value. When the error is higher than the set value, the fuzzy PID is used to control the temperature. Otherwise, the expert is selected. The simulations and experimental results show that the temperature control system based on expert fuzzy PID algorithm has the merits of faster response, smaller overshoot and higher robustness than classical PID.
© 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [name organizer]
Open access under CC BY-NC-ND license.
Keywords: Expert control; Fuzzy PID control; heating furnace; temperature control
Introduction
Because the heating furnace has the disadvantages of non-linearity, time-variant and large delay, its control effect is often not satisfactory [1,2]. Therefore, it is very important to seek an effective and accurate method to control the temperature of heating furnace. In recent years, with the continuous development of the fuzzy theory and neural network theory, the intelligent control of heating furnace has become a hot topic and an important research field [3,4].
Fuzzy PID control technology has been widely used in many fields, especially in the temperature control of heating furnace because of its simplicity, flexibility, practicality, stability, high precision and high robustness [5]. However, the control rules and membership functions of fuzzy controller are
* Corresponding author. Tel.: 86-451-86392396. E-mail address: shidequan2008@yahoo.com.cn.
1877-7058 © 2011 Published by Elsevier Ltd. Open access under CC BY-NC-ND license.
doi:10.1016/j.proeng.2011.12.703
258 SHI Dequan et al. / Procedia Engineering 29 (2012) 257 – 261
artificially set, so it is difficult to meet the dynamic requirements of time-varying and hysteresis [6,7]. Therefore, in order to meet the requirements of real-time control, the expert system is introduced. The experience knowledge is stored in computer, and the knowledge database according with the practice is formed to improve the control effect. The expert controller can make the system go into stable state in shorter time.
In this paper, a temperature control system is designed according to the combination fuzzy PID control with expert control, and the expert fuzzy PID controller is described in details.
Structure of temperature control system for heating furnace
Fig.1 shows the structure of temperature control system for heating furnace, and its main control unit is an expert fuzzy PID controller.
Figure 1 Temperature control system of heating furnace based on expert fuzzy PID
When the temperature in heating furnace is measured by the thermocouple, it is compared with the set temperature. As a result, the error e and the error change rate ec will be got, and they are the input parameters. According to the set value of the mode selective switch, either the fuzzy PID control or the expert control will be chosen. When the error e is higher than the set value, the fuzzy PID control will be used. On the contrary, when the error e is lower, the expert control will be selected.
Therefore, the ways of controlling temperature can be regulated flexibly according to the real-time error e and error change rate ec. It not only has the merits of quick regulation of the expert control, but also high precision and good stability of fuzzy PID control.
Design on expert fuzzy PID controller
The fuzzy PID control is developed from tradition PID. Based on the fuzzy control theory, the fuzzy relationship between three PID parameters KP, KI, KD and the error e and error change rate ec can be established. According to different e and ec, the parameters KP, KI, KD can be self-adjusted online in order to make the controlled object have a good dynamic and static performance, which can meet different control requirement.
In general, fuzzy control has no knowledge database, and not has the adaptive ability, and the flexibility and interactivity are not very good. Contrarily, the expert systems often can not directly used to controlled object or production process. So, the combination the fuzzy PID and expert control will bring their respective advantages into play.
Expert controller mainly plays the function of retaining temperature invariable when the measured temperature reaches the range of experimental precision. Therefore, it can make the furnace temperature
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stabile and avoid the temperature shock in the error range, rapidly meeting the tes
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