Abstract: This paper constructs a novel PC-based automated control system structure. Addressing the characteristics of jacketed furnace temperature systems, such as large inertia, nonlinearity, and difficulty in establishing mathematical models, a fuzzy control strategy is proposed, and a system solution is provided, achieving effective control of the furnace temperature system. Keywords: PC-based automation; fuzzy control; temperature control system 1 Introduction Jacketed furnaces are widely used in industrial sites and university process control laboratories, but they generally suffer from large inertia, nonlinearity, time-varying parameters, and difficulty in establishing mathematical models. Traditional PID control is insufficient to meet field requirements. This design addresses the characteristics and difficulties of furnace temperature control by constructing a novel PC-based temperature control system structure and proposing a fuzzy intelligent control strategy, achieving effective temperature control of jacketed furnaces. This novel PC-based automated control system structure is particularly suitable for process control systems such as temperature, pressure, and flow; it is also suitable for training engineering and technical personnel in industrial enterprise training centers and university practical teaching, possessing certain promotion and application value. 2 Composition of the PC-based Temperature System The structure of the PC-based fieldbus temperature control system is shown in Figure 1. The host computer (or industrial PC) is equipped with INTELLUTION FIX32 monitoring software and BECKHOFF PC-based automation control software to complete the system's control program design and implement fuzzy control algorithms; it also provides functions such as system condition monitoring, parameter setting, data acquisition, trend display, and report printing. The controller uses a PC-based intelligent control module, consisting of a bus coupler with Profibus communication, a K1408 digital input module, a K2424 digital output module, a K3052 analog input module, a K4022 analog output module, and a terminal module. This module performs system start-up, stop, and protection control; it also outputs control signals to control the conduction angle of the thyristor power regulator to control the voltage level on the heater; and it receives field detection signals from the furnace temperature transmitter, forming a closed-loop temperature control system. The controlled objects in the field consist of a jacketed furnace (with an inner and outer tank), a water system, a heater, and a PT100 temperature sensor. Advantages of PC-based fieldbus temperature control system: (1) PC (or industrial PC) has large storage space, good visualization, fast running speed and rich software resources. It can be programmed using VC++, VB, soft PLC and other languages, and is easy to realize complex control algorithms, remote diagnosis, upper-level monitoring and control system functions; (2) Open fieldbus Profibus communication mode, fast transmission rate; (3) Good real-time performance of the system and short execution time. [align=center] Figure 1 Structure diagram of heating furnace temperature system[/align] 3 Design of fuzzy controller 3.1 Design idea The block diagram of heating furnace temperature control system is shown in Figure 2. It consists of fuzzy controller, thyristor power regulator, heating furnace and temperature transmitter. The temperature setpoint R[sub]T[/sub] is compared with the temperature feedback y[sub]T[/sub] to obtain the error signal e and the error change rate signal ec. After fuzzifying e and ec, establishing fuzzy control rules, synthesizing fuzzy relation sets and inferences, and performing fuzzy decision-making, the definite fuzzy controller output control quantity U[sub]K[/sub] is obtained to control the conduction angle of the thyristor power regulator, thereby controlling the voltage on the heater inside the heating furnace and controlling the temperature controlled quantity Y[sub]T[/sub] in real time. [align=center] Figure 2 Block diagram of the heating furnace temperature control system[/align] 3.2 Fuzzy control algorithm The fuzzy controller adopts a dual-input single-output control mode, using temperature error e and error change rate ec as input variables and U[sub]k[/sub] as output variable. The fuzzy subset is E=EC=UK={NB, NM, NS, ZE, PS, PM, PB}={negative large, negative medium, negative small, zero, positive small, positive medium, positive large}, and its universe of discourse is e=ec=uK{-3, -2, -1, 0, 1, 2, 3}, or written as e: [-Xe, Xe], rate of change ec: [-Xec, Xec], uK: [-Yu, Yu]. The membership function adopts the triangular distribution function, as shown in Figure 3. [align=center] Figure 3 Membership function[/align] Based on practical experience, 49 inference language rules were summarized and expressed in the form of if-then statements to obtain the fuzzy control rule table of control variable U[sub]K[/sub], as shown in Table 1. (1) if E is NB and EC is NB then U[sub]K[/sub] is PB; (2) if E is NB and EC is NM then U[sub]K[/sub] is PB; ┇ (49) if E is PB and EC is PB then U[sub]K[/sub] is NB. [align=center] Table 1 Fuzzy control rule table[/align] Based on the fuzzy rules, fuzzy relations were summarized and Mamdani's fuzzy inference and synthesis operation was used to obtain the membership degree of μ[sub]UK[/sub](E, EC) of the corresponding U[sub]K[/sub] universe elements. The weighted average method was used to perform defuzzification operation to obtain the cleared control quantity U[sub]k[/sub]. 3.3 Control Program Design The control program was designed using ST language for soft PLCs on a PC-based industrial control software platform, including the main program, fuzzy control algorithm, interrupt service routine, operation and alarm programs, etc. Information exchange, program execution, and algorithm implementation are performed via the Profibus fieldbus and bus coupler. The fuzzy control algorithm flowchart is shown in Figure 4. [align=center] Figure 4 Fuzzy Control Algorithm Flowchart[/align] 4 Actual Control Effect The upper-level monitoring system was designed using FIX32 configuration software, including five functional modules: process configuration, furnace temperature monitoring, trend display, event alarm, and record printing. This directly reflects the working status, changing trends, and real-time control of the heating furnace. When the inner tank temperature setpoint is 50℃, the historical trend of the monitoring system directly shows that the control accuracy of the controlled variable Y[sub]T[/sub] is within ±1.5℃. The system has a strong ability to overcome disturbances when applied at different locations. The inner tank temperature output characteristics are shown in Figure 5. [align=center] Figure 5 Temperature output characteristics of heating furnace with different disturbances[/align] 5 Conclusion The innovation of the system is that it adopts a new structure of temperature control system based on PC, fuzzy control strategy and fieldbus Profibus communication technology; it makes full use of the advantages of PC, such as fast speed, good visualization and easy implementation of complex fuzzy control algorithm, so that the system has good real-time performance and robustness. Through the temperature control application practice of the rolling mill training center and the process control laboratory of the university, it is proved that the system scheme has good control effect. References: [1] Liu Huikang, et al. Research on fuzzy control of through hole well heating furnace, Microcomputer Information, No. 7, 2006, pp. 62-64. [2] He Yanqing. Industrial production process control. Chemical Industry Press. 2004 [3] Gao Dongjie. Application of advanced control technology. National Defense Industry Press. 2003 Research data download of temperature intelligent control system based on PC