Fluidized Bed Temperature Control System Based on Virtual Instrument Technology and Fuzzy PID Algorithm

Article Preview

Abstract:

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.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 562-564)

Pages:

1594-1597

Citation:

Online since:

August 2012

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] ZHANG Jun-kui. The control status for circulating fluidized bed boiler[J]. Shanxi Eelectric power, 2004, 6(1): 11-12.

Google Scholar

[2] ZHANG Yan-qin, XU Xiang-dong. Design and research to circulating fluidized bed[J]. Power System Engineering, 2003, 19(5): 50-52.

Google Scholar

[3] U Nai-wei, Fu-hua, Yan-xin. Application of parameter self-tuning fuzzy- PID control in the temperature control system [J]. Control and Automation Publication Group, 2004, 20(6): 48-50.

Google Scholar

[4] CAI chun-qiao, WANG yong-jun, WANG jun-biao. Design and implemention of resistance furance temperature control system[J]. Science Technology and Engineering, 2007, 7(10): 2379-2382.

Google Scholar

[5] Wang Q G, Zou B, Lee T H, et al. Auto-tuning of multivariable PID controllers from decentralized relay feed-back[J]. Automatica, 1997, 34(10): 18-20.

DOI: 10.1016/s0005-1098(96)00177-x

Google Scholar

[6] Zgorzelski P, Unbehauen H, Niederlinski A. New simple decentralized adaptive multivariable regulator and its application to multivariable plants[C]/Proceedings of the 11th Triennial Worle Congress of the International Fede-ration of Automatic Control, Elmsford NY: Pergamon Press Inc, 1991: 381-386.

DOI: 10.1016/s1474-6670(17)52038-8

Google Scholar