Temperature control in electric furnaces: Methods, applications, and challenges

This paper proposes a fractional order predictive functional control method for temperature control of an industrial electric heating furnace. Since the electric heating furnace is affected by complex factors such as measurement noise, uncertainty, model/plant mismatches, and so on, it is more important to derive accurate modeling and controller design for improved control performance. Under the uncertain facts, conventional control methods based on integer order models may not offer the desirable control performance. The fractional order model of the heating furnace based on the input-output data of the step response test is introduced to describe the dynamics of the process and the Oustaloup approximation is used to transform the fractional order process into an integer formulation. Then a predictive functional controller is designed through minimizing the future predicted output error based on the state space model transformation. Application has been implemented on the industrial heating furnace and the experimental tests reveal the validity of the proposed controller in comparison with conventional integer model-based PFC.

This paper introduces the idea of fuzzy self-adaptive PID algorithm. In order to compare the control effects of traditional PID, fuzzy control and fuzzy self-adaptive PID algorithm, simulation was carried out .The results show that the fuzzy self-adaptive PID controller has the characteristics of fast response time, less overshoot and small steady-state error and has extremely high interference rejection capacity. The software of SCM (Single-Chip Microcomputer) realizes the algorithm. The controller is applied to electric heating furnace temperature control system and the practical application shows that the controller achieves a satisfied control effect.

With the development of science and technology in China, temperature control system has been widely used in many fields. The emergence of PLC effectively improves the shortcomings of PID control system, optimizes the performance of PID control system, and plays a very important role in promoting industrial production and construction. In view of the design of temperature control system of heating furnace, configuration software and PLC can be used the combination of technology can achieve the goal of furnace temperature control, and it can also monitor the furnace temperature in real time and comprehensively, and then adjust the furnace temperature according to the application requirements. The investment in the process is less, which can reduce the cost to a certain extent, and also has the application advantage of high accuracy. The temperature control system of electric heating furnace is designed in this paper. PLC is mainly used, and the temperature system is controlled intelligently with touch screen. According to the actual situation and cost budget, the controller of this paper chooses Mitsubishi FX2N- 48MR series PLC. In order to achieve intelligent control, it needs to use digital PID control algorithm, which is convenient for the staff to operate Gt1040-qbbd-c series touch screen is used to realize human-computer interaction. The system can be started and stopped. The touch screen for temperature setting can be very simple to operate. The temperature change can also be visually displayed and monitored, and the whole system can be automatically set.

Pollution profiles and health risk assessment of VOCs emitted during e-waste dismantling processes associated with different dismantling methods

This paper presents a Linear Quadratic Regulator Controller design for Temperature Control of an Electric Furnace System using MATLAB. Also, Proportional-Integral-Derivative (PID) Controller is designed for control of an Electric Furnace. The three PID parameters K p, K i, and K d are obtained using two tuning methods, Ziegler Nicholas and Tyreus Luyben. Performance of the system using LQR and PID (using Ziegler Nicholas and Tyreus Luyben) control techniques for an Electric Furnace Temperature System is compared by analyzing the Time Response of the system. The result of simulation shows that LQR technique gives better performance for the given system.

Objective To investigate the clinical effectiveness of an intelligent shell temperature control system in deep tumor hyperthermia for controlling the temperature in the outer shell of chest and abdominal malignancies. Methods From 2015 to 2016, a randomized comparative study was carried out in the intelligent temperature control system (experimental group containing 37 patients with chest tumor and 26 patients with abdominal tumor) and conventional cooling by replacement of water bags (control group containing 37 patients with chest tumor and 25 patients with abdominal tumor) for chest and abdominal tumor hyperthermia. The effectiveness in controlling the outer shell temperature was compared between the two methods. Results In the experimental group, the first boot of the cooling system occurred at 24.1 and 21.8 minutes on average after the hyperthermia started and the average number of system boots was 2.5. In the control group, patients reminded to replace the water bag at 33.1 and 33.8 minutes on average after the hyperthermia started and the average number of replacements was 3.6. The highest outer shell temperature in patients with chest tumor and abdominal tumor averaged 38.5 and 39.1 ℃ at the first boot of the cooling system in the experimental group and 39.3 and 40.4 ℃ at the first replacement of the cooling water bag in the control group, respectively. The treatment with and without the intelligent temperature control system caused grade ≥Ⅱ empyrosis in 1 and 4 patients with chest tumor and in 0 and 3 patients with abdominal tumor, respectively. Conclusions In deep tumor hyperthermia, compared with the conventional cooling by replacement of water bags, the intelligent shell temperature control system can detect and cool the high-temperature zone in the outer shell at an earlier time, which effectively reduces the incidence of skin burn injury. Key words: Deep hyperthermia; Scalded skin; Temperature control

The mechanism of carbon diffusion in the as-cast and heat-treated grey iron and 304 stainless steel bimetallic composites was investigated in this study. A simplistic empirical model for the interface carbon diffusion was proposed and has been validated against the experimental data. A liquid-solid compound casting technique was used to fabricate the bimetallic composites. For the graphitizing annealing heat treatment, the bimetallic composite specimens were heated to 940 °C and held for 120 min and 240 min in an electric heating furnace. The proposed empirical model is based on the presence of eutectic carbides chill zone near the interface that formed during solidification of the liquid grey iron above the solid stainless steel substrate. It was found that the calculated carbon concentration profiles based on the proposed diffusion model were in good agreement with the experimental results.

Based on the electric heating furnace temperature control system, a kind of single parameter PID control method is studied. And compare with Smith predictive control. The simulation shows that the single parameter PID control has a better characteristic of stability and robustness, and it is an appropriate and simple control method for the system with large time delay.KeywordsElectric heating furnaceTemperature controlSmith predictive controlSingle parameter PID

The apparatus is for the purpose of maintaining an electric furnace at a constant temperature for considerable periods of time (weeks or months) in spite of fluctuations in the supply voltage. Several auxiliary furnaces may be maintained at various temperatures by means of the apparatus, but the temperature control is not so accurate as in the case of the thermostat furnace itself. Should the supply current fail or the temperature control be temporarily lost owing to the failure of a relay, the apparatus is not damaged in any way by the violent displacement of the mercury, and the furnaces will return to their original temperatures as soon as the defect is remedied. By the correct proportioning of the apparatus the effect of room temperature changes on the temperature of the controlled furnaces may be pratically eliminated. The usual low temperature air bulb maintained in ice is replaced by the barometer column which requires no attention.

In industrial production, temperature and humidity are common main manipulated parameters, especially in heat treatment industry, the temperature control is becoming more and more important. This paper from two aspects that hardware and software introduced single-chip microcomputer (SCM) C8051F intelligent temperature and humidity control system, and described schematic diagram of hardware and software. The design adds the integration of carbon dioxide concentration and light intensity detection and necessary communication function. It is a more humanized and more practical intelligent temperature and humidity measurement and control system.

Fuzzy logic control based on the Takagi–Sugeno inference method has been applied for the yeast alcoholic fermentation running in a continuous-time biochemical reactor in this paper. A type-1 fuzzy PID controller was designed to temperature control in a biochemical reactor. The fuzzy PID controller was also designed using type-2 fuzzy sets. The advantage of the fuzzy control is that it can be used very successfully for control of strongly non-linear processes and processes that are difficult to model because of complicated reaction kinetics. Obtained simulation results confirm this fact. The disadvantage of the fuzzy control design lies in the time-consuming tuning of controllers. The subtractive clustering method was used to identify the rule base. This approach was chosen to minimize the number of rules of the designed fuzzy logic controllers and to simplify the fuzzy controller design. Simulation results confirm that fuzzy PID controllers can assure better performance than conventional PID controllers. Yeast alcoholic fermentation is an exothermic process and the cooling is necessary to maintain the optimal temperature in the reactor. Fuzzy PID control reduces coolant consumption in comparison with conventional PID control and so it assures energy-efficient control of continuous-time alcoholic fermentation. Using type-2 fuzzy sets in the fuzzy PID controller design is very promising as the type-2 fuzzy controller offers even better results than the type-1 fuzzy controller.

A GBMO-based PI λ D μ controller for vibration mitigation of seismic-excited structures

The photovoltaic (PV) system’s nonlinear nature, uncertainty in temperature, and light intensity in the environment are responsible for the fluctuation of the maximum power point (MPP). Many maximum power point tracking (MPPT) algorithms are proven effective in the literature, including use of artificial intelligence. Proportional integral derivative controller and fuzzy controllers found effective to track MPP. Using the combination of Fuzzy-PID controller, swiftly adapt to changes in the atmosphere to confirm the solar array is continually operating at its highest efficiency with MPP. Easy and effective oscillation elimination is possible with PID control. To regulate the maximum power of the PV system combination of Fuzzy-PID self-tuning controllers is found effective.The goal is to enhance a PV system’s dynamic response to in presence of irradiation and temperature fluctuations. For tuning Fuzzy logic controller (FLC), gain scheduler values of the proportional, integral, and derivative constants are fundamental. The design processes for non-linear conventional PID controllers, FLC, and series combination of Fuzzy-PID controller are discussed. It compares the traditional PID controller, FLC, and Fuzzy-PID controller. The comparison of outputs produced for PID, FLC, and series Fuzzy-PID controller confirms the effectiveness of the algorithm. Use of Fuzzy controller helps in self-tuning of PID controller constant value. MATLAB/Simulink based environment used to perform the simulations.

Model predictive control has been recognized as one of the essential solutions to achieve considerable energy savings in buildings. However, its performance on a building zone level can be inferior to a well-tuned conventional controller, especially in situations with constant energy prices and conservative comfort constraints. Optimization problem in the background has to be chosen to guarantee recursive feasibility and considerable energy savings without compromising the users comfort at the same time. This paper gives a novel formulation of the model predictive temperature control problem in buildings and its fair comparison with conventional controllers with the same level of flexibility allowed in zone temperature control. All controllers are tested for a system with seasonal heating and cooling, which is the most common case in real applications. It is shown that the introduced formulation leads to the model predictive controller that significantly outperforms conventional controllers both in energy consumption and users comfort.

This research demonstrates the designing of Model Predictive Controllers (MPCs) to control the temperature for thermal model of house. It also introduces an identified transfer model with a best fit criterion around 97%. In addition, a comparison study between Proportional Integral Controller (PI), Proportional Integral Derivative Controller (PID) Fractional Order PI (FOPI), Fractional Order PID (FOPID) and Model predictive Control (MPC) has been discussed in this research. Moreover, all the parameters of the suggested strategies have been tuned by Cuckoo Search Algorithm (CSA). In fact, heating systems in house buildings aim to control the indoor temperature. To realize this purpose, it is necessary to have suitable control strategies that could implement a precise temperature control. As a result a Simulink model is used to simulate the operation of temperature control and the suggested control approach. The obtained results depict that the performance evaluation includes rise, settling times, system overshoots, and Integral Time Absolute Error (IT AE) are the best values under applying MPC over using others controllers (traditional, fractional order and thermostat) controllers. As a result it can be concluded that the MPCs have the main concern of utilizing it in the area of control the thermal house temperature. Additionally, the introduced results are promising in this problem.