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The Research of the Oxidized Pellet Rotary Kiln Temperature Control System Based on the Improved BP Neural Network

Author: WangLeiMing
Tutor: ZhangYong
School: Liaoning University of Science and Technology
Course: Control Theory and Control Engineering
Keywords: Rotary kiln BP neural networks Genetic algorithms Clustering detection Fuzzy control
CLC: TP273
Type: Master's thesis
Year: 2012
Downloads: 85
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Abstract


In the oxidation pellets in the process of production of rotary kiln, the quantity and quality of the product is directly influenced by the rotary kiln burning zone temperature. Rotary kiln is a nonlinear and large delay system, which is difficult to establish the precise mathematical model. Due to the rotary kiln continuously running process, which is difficult to detect a temperature of the burning zone. When use the traditional thermocouple temperature measurement method and the PID control method, control results and influence the finished pellet quality often hard to achieve a satisfactory results. To solve the above problems, this paper to rotary kiln burning zone temperature detection and control as the research object,and the rotary kiln temperature prediction model is proposed which based on GA-BP. According to the results of temperature forecast, algorithm of rotary kiln burning zone temperature control model is proposed which based on the fuzzy PID, to the advanced method for the detection and control of rotary kiln temperature.First detailed analysis of the thermal process and rotary kiln temperature control key, a deep research on artificial neural network and genetic algorithm. According to the existing problems of data error, this paper using clustering method of detection processing of data, in order to eliminate interference data. According to the temperature testing existent problem, put forward based on the genetic algorithm to optimize the BP neural network of rotary kiln temperature prediction model. Then using genetic optimize the BP neural network to handle ending data training simulation, the simulation results show that the genetic optimize the BP neural network temperature prediction model for prediction of the temperature in the rotary kiln, which can get better prediction accuracy.Finally, according to the rotary kiln delay and the characteristics of the many interference factors,the method of rotary kiln is proposed which based on fuzzy PID control temperature control. According to the characteristics of rotary kiln design the structure of the fuzzy PID controller and a simulation study, the simulation results show that the fuzzy PID control method than the traditional PID control method of adaptability, can achieve better control effect.

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