Vacuum induction heating furnace temperature control system based on smith fuzzy-PID

Author(s):  
Ningning Teng ◽  
Jian Zhang
2012 ◽  
Vol 217-219 ◽  
pp. 2463-2466 ◽  
Author(s):  
Xue Gang Hou ◽  
Cheng Long Wang

Induction heating furnace temperature control is a complex nonlinear hysteretic inertial process, it's difficult to obtain an accurate mathematical model because the temperature and disturb from outside is complicated. The normal PID control algorithm is hard to satisfy the standards of control. The fuzzy PID controller provided in this article is a combination between fuzzy control and the traditional PID control. The Fuzzy control theory is used to setting the ratio, the integral and the differential coefficient of the PID control. In the run-up stage, rapidity is guaranteed, overstrike and the steady-state error is up to the mustard. An example indicates that fuzzy PID control is superior to the normal PID controller.


2012 ◽  
Vol 562-564 ◽  
pp. 1594-1597
Author(s):  
Chun Qia Liu ◽  
Shi Feng Yang

The fluidized bed is a complex system with a big lag, time-varying and non-linear. The conventional-PID methods are simple, practical, and high reliability. However, choosing and adjusting PID parameters rely on manual way. It is difficult to choose appropriate values when temperature requirement is higher. Inappropriate values may cause large overshoot and low control precision. Thus, in order to obtain more accurate and rapid PID control parameters and to avoid errors caused by human factors, the fuzzy control and PID algorithm were applied to the fluidized bed furnace temperature control system. The Fuzzy-PID controller was designed and the three PID parameters' self-tuning was realized. Simultaneously, the upper computer and the lower computer were designed. The lower computer mainly completed temperature measurement and adjustment functions. The collected temperature was transferred back to the upper computer at regular intervals. The upper computer was designed by virtual instrument technology. Practical operation shows that the temperature variation is below 0.3 when heating oven is in stable state and is close to the ideal PID response curve, which meets the average requirements of the fluidized bed heating oven. As an advanced reactor, fluidized bed was widely used in industrial process such as combustion, gasification and catalytic cracking[1].As the temperature affect the gas product composition of the fluidized bed, so improving the furnace temperature utilizing the automatic control system is one of the important issues furnace. The fluidized bed heating oven is heated by resistance wire heating and cooled by natural cooling. The temperature control after the adjustment is slow. It is a complex system with a big lag, time-varying and non-linear. Currently, the conventional-PID methods were taken to control the fluidized bed heating oven's temperature. This method is simple, practical, and high reliability. However, choosing and adjusting PID parameter rely on manual way, it is difficult to choose an appropriate values .Inappropriate values may cause large overshoot and low control precision. Thus, in order to obtain more accurate and rapid PID control parameters and to avoid errors caused by human factors, the fuzzy control and PID algorithm are applied to the fluidized bed furnace temperature control system. The self-tuning fuzzy PID controller is designed. Compared with the outdated control methods, PC control is more flexible and even more long-range.


2012 ◽  
Vol 572 ◽  
pp. 376-381
Author(s):  
Jian Long Guan ◽  
An Rui He ◽  
Wen Quan Sun ◽  
Nan Feng Zhang ◽  
Jian Hua Li

The new fuzzy PID control system presented in this thesis is a combination of the models used in traditional temperature control system and Dual cross limiting temperature control system that took problems such as the slow response and overshoot of furnace temperature caused by the drastic change of the value of gas and the pressure in to account. The fuzzy PID control system helps to conquer the drawbacks of Poor dynamic tracking performance and has the distinction of being flexible, quick and adaptable. It is also proven by practice that, it is environmental friendly and energy-saving with the high-accuracy and lower consumption of this new control system.


2011 ◽  
Vol 383-390 ◽  
pp. 3904-3908
Author(s):  
Hong Xia Tian ◽  
Pei Lei Jiang ◽  
Li Xin Tian

In view of the serious misalignment, the mathematical model's uncertainty, the characteristic of the system operating point changing fiercely of the heating furnace temperature control system, this paper designed a new type of intelligent control system - PID neural network system (PIDNN) which melt the PID control rule in the neural network. This system has the quick reasoning speed and the strong anti-interference ability.


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