Composite Fuzzy Control Method for Temperature in Intelligent Moisture Analyzer

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Temperature control system of infrared heating oven in moisture analyzer is characteristic of nonlinear, time-varying and time-lag. A composite fuzzy control (CFC) method is proposed, which combines improved Bang-Bang control with two-stage intelligent fuzzy control. The control algorithm is implemented by MSP430F5438. When the temperature error e between the desired temperature and actual temperature in heating oven is larger than threshold value, the improved Bang-Bang controller is employed in rapidly reducing the error; to decrease the system overshoot, the basic fuzzy controller is used; to reduce the steady-state error of basic fuzzy controller, the auxiliary fuzzy controller is applied. The steady-state error of improved fuzzy controller for oven temperature is less than 0.5°C, which is better than the Chinese National Standards for moisture content measurement.

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1010-1013

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September 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Weiwu Zhong, Dongbiao Zhao, Xi Wang; Adaptive Fuzzy Control of Cutting Temperature Based on Cutting Fluid in High-speed Machining, Advanced Materials Research. Vols. 97-101(2010)pp.2381-2386.

DOI: 10.4028/www.scientific.net/amr.97-101.2381

Google Scholar

[2] Chuansheng Wang, Fuhai Zhou; Reaserch of Temperature Control System Based on Fuzzy Control Algorithm for Mixer, Advanced Materials Research. Vol. 87-88(2010), pp.288-292.

DOI: 10.4028/www.scientific.net/amr.87-88.288

Google Scholar

[3] Guo Jianbo, Zhou Jianli, Cui Tao; The application of the hybrid fuzzy control of the furnace, Computer Information, Vol. 21, No. 7, 2005, pp.92-94.

Google Scholar

[4] T. Callai, J. Santos, R. Sumar et al; Applying the Potentiality of Using Fuzzy Logic in PID Control Design, Advances in Soft Computing 2005, 32: 193–204.

DOI: 10.1007/3-540-32400-3_15

Google Scholar