Research of the Industrial Furnace Temperature Control Based on DMC Algorithm

2014 ◽  
Vol 556-562 ◽  
pp. 2240-2243
Author(s):  
Zhi Yong Meng ◽  
Chen Meng Sui ◽  
Lei Liu
Keyword(s):  
Prediction Model ◽  
Temperature Measurement ◽  
Temperature Control ◽  
Control Algorithm ◽  
Industrial Furnace ◽  
Furnace Temperature ◽  
Feedback Correction ◽  
Rolling Optimization

By introducing the existing lack of industrial temperature control algorithm is applied, leads to the advantage of DMC algorithm industrial furnace temperature control, the next from the prediction model, rolling optimization, feedback correction of the three aspects of the principle of DMC algorithm is fully explained, on this basis, the preparation of Matlab procedures, simulation of the DMC algorithm in industrial furnace temperature control, thus indicating DMC algorithm in the field of industrial temperature measurement is a method should be promoted.

Explicit Indirect Predictive Control Algorithm in the Application of AWC Control

2014 ◽  
Vol 926-930 ◽  
pp. 1344-1347
Author(s):  
Fang Chen Yin ◽  
Geng Sheng Ma ◽  
Ya Feng Ji ◽  
Zhong Ping Li ◽  
Dian Hua Zhang
Keyword(s):  
Predictive Control ◽  
Delay Time ◽  
Control Algorithm ◽  
Continuous Mill ◽  
Control Performance ◽  
Hot Strip ◽  
Parameter Variations ◽  
Feedback Correction ◽  
Rolling Optimization ◽  
Pure Delay

Using the characteristics of prediction model, rolling optimization and feedback correction, a AWC system based on explicit indirect predictive control was designed, and its control performance was simulated based on a hot strip continuous mill. The results show that explicit indirect predictive control achieves better control effects than the normal PID on response time and steady precision with matching model; when model mismatching is caused by inaccuracy of plastic coefficient and pure delay time, the normal PID is overshot or even oscillation, but the control performance of the explicit indirect predictive control is not influenced by model parameter variations [1].

scholarly journals Research on temperature control of heating furnace with intelligent proportional integral derivate control algorithm

2020 ◽  
Vol 24 (5 Part B) ◽  
pp. 3069-3077
Author(s):  
Feilong Zheng ◽  
Yundan Lu ◽  
Shuguang Fu
Keyword(s):  
Neural Network ◽  
Control Theory ◽  
Temperature Control ◽  
Intelligent Control ◽  
Pid Control ◽  
Control Algorithm ◽  
Network Control ◽  
Furnace Temperature ◽  
Proportional Integral ◽  
Intelligent Pid

In view of the problems of large overshoot and large oscillation frequency in cur?rent furnace temperature control, based on the development of intelligent control theory, expert control, fuzzy control, and neural network control in intelligent control theory are combined with proportional integral derivative (PID) control. The intelligent PID control algorithm is used to carry out numerical simulation and experimental research on these several control algorithms. The results show that the adjustment effect of the intelligent PID control algorithm is significantly better than the traditional PID control algorithm. Among them, the fuzzy self-tuning PID control algorithm and the fuzzy immune PID control algorithm are feasible in the application of furnace temperature control. The neural network PID control algorithm It also has good development and application potential.

MATLAB-Based Comparative Furnace Temperature Control Algorithm and Simulation

2014 ◽  
Vol 494-495 ◽  
pp. 1335-1338
Author(s):  
Xiao Yun Zhang
Keyword(s):  
Temperature Control ◽  
Control Algorithm ◽  
Control Object ◽  
Simulation Software ◽  
Temperature Control System ◽  
Simulation Design ◽  
Furnace Temperature ◽  
Simulink Simulation ◽  
Advanced Control ◽  
Complex Temperature

Temperature control is critical temperature and the temperature of the two aspects. Temperature measurement is based on temperature control. However, due to the control object becomes more and more complex, temperature control, there are still many problems. In this paper, based on the use PID, Smith predictive control, Dalin algorithm comparative study of three algorithms for industrial resistance furnace temperature control system computer simulation design, and the use of simulation software MATLAB / SIMULINK simulation of the control algorithms, but also on advanced control algorithm is studied.

Furnace Temperature Control and Simulation

2014 ◽  
Vol 556-562 ◽  
pp. 2492-2495
Author(s):  
Ming Yu Tong ◽  
Di Jian Xu ◽  
Jin Liang Shi
Keyword(s):  
Control System ◽  
Temperature Measurement ◽  
Temperature Control ◽  
Control Algorithm ◽  
Rapid Development ◽  
Control Object ◽  
Simulation Software ◽  
Temperature Control System ◽  
And Control ◽  
Measurement And Control

with the rapid development of science and technology, in all fields of temperature control system of the precision, stability and other requirements of increasingly high, the control system is the myriads of changes. Computer measurement and control technology, the traditional electronic measuring changed dramatically in the principle, function, accuracy and automation degree, degree of automation of the scientific experiment and application engineering to improve. Temperature control key lies in the two aspects of temperature measurement and control. Temperature measurement is based on temperature control, this technology is quite mature. But because of the increasingly complex control object, control in the temperature still exist many problems. This thesis presents the design of industrial temperature resistance furnace computer using PID algorithm, Smith predictive control algorithm, darin algorithm, three algorithms are studied based on the control system, and the control algorithm was simulated using the MATLAB simulation software, and the advanced control algorithm is studied [1-3].

Design of Remote Monitoring System Based on Fuzzy Control of Furnace Temperature

2012 ◽  
Vol 630 ◽  
pp. 241-244
Author(s):  
Hong Fang
Keyword(s):  
Fuzzy Control ◽  
Monitoring System ◽  
Temperature Control ◽  
Remote Monitoring ◽  
Control Algorithm ◽  
Control Process ◽  
Temperature Control System ◽  
Single Chip ◽  
Furnace Temperature ◽  
Remote Monitoring System

During the furnace temperature control process, the thermocouple signal can be easily distorted during the amplification and analog-to-digital (A/D) conversion. In regular PID control algorithm, the PID parameters shall be adjusted according to the ambient temperature. For the informatizaiton and internetization of enterprises, the temperature control system shall be monitored remotely through Internet. This paper, taking the single chip microcomputer as the core and the high-precision AD7705 A/D converter as the sampling element for furnace temperature, designs a remote monitoring system fuzzily controlling the furnace temperature by using fuzzy control algorithm and RTL8019AS Ethernet Control Chip, achieving the accurate control and remote monitoring of the temperature of resistance furnace.

Optimal Control of the Industrial Furnace System

2011 ◽  
Vol 383-390 ◽  
pp. 3077-3080
Author(s):  
Xin Tong Tang ◽  
Chang Qing Cai
Keyword(s):  
Optimal Control ◽  
Control System ◽  
Energy Consumption ◽  
Industrial Furnace ◽  
Gas Temperature ◽  
Furnace Temperature ◽  
Control Temperature ◽  
Target Control ◽  
Fuel Rate ◽  
General Goal

Control system of industrial furnace is optimized based on the aspect of the combustion. General goal of the control system is to achieve the lowest fuel with the constraints of ensuring the target control temperature of the equipment. And in different output and different fuel quantity conditions, the air-fuel rate is automatically optimized to achieve the goal of energy consumption combined with gas temperature of furnace temperature, oxygen and many parameters.

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