Dissertation > Industrial Technology > Chemical Industry > Silicate > Ceramic Industry > Production process and equipment > Firing and equipment

The Research of Genetic Algorithms and Fuzzy Neural Network Adaptive Control Applicated in the Shuttle Kiln Control

Author QiuMinMin
Tutor JiangFangLe
School Jingdezhen Ceramic Institute
Course Energy and Power Engineering
Keywords Shuttle kiln Genetic Algorithms Fuzzy Neural Network VC 6.0 MATLAB
CLC TQ174.65
Type Master's thesis
Year 2009
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This topic is divided into two parts, the first part of the genetic algorithm to optimize the gas shuttle kiln heating rate . The various stages of ceramic firing process requirements as a genetic algorithm to optimize the shuttle kiln heating rate constraints. And the heating rate of the various stages of real coding , the total gas consumption as an indicator of fitness function for genetic manipulation . The results showed that the optimized heating rate in the shuttle kiln firing can take to save fuel consumption effect : Part II based model reference adaptive control (MRAC) on the gas shuttle kiln temperature control. Since shuttle kiln as a control object exists in the process of non-linear , long lag, when the variability and uncertainty of the situation , the general conventional PID control can not meet the control precision. Therefore, this paper proposes MRAC control scheme , which uses RBF RBF network as a shuttle kiln temperature object recognition network , it produces Jacobin information provided together with the control error fuzzy neural network controller as their learning signal. After adjustment of the initial parameters MATLAB simulation , simulation results show that the algorithm can be time-varying objects more accurate identification, system stability, robustness . Finally, we use VC 6.0 development of control software , combined with the USB data acquisition card on the gas shuttle kiln control. The realization of the self-priming gas shuttle kiln temperature is more precise control of the atmosphere , the pressure control program control by expert experience , achieved relatively good control effect.

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