基于PID控制的遗传神经网络在焦炉温度控制中的应用研究

Application and Research of Genetic Neural Network Based PID Control for Coke Oven Heating Control

  • 摘要: 以某焦化厂焦炉温度控制系统的开发为背景,提出了一种基于遗传算法的CMAC(小脑模型关联控制器)与PID复合控制方法来优化焦炉对象的温度控制.用遗传算法优化PID控制器的初始参数,然后再结合CMAC网络进行控制.针对焦炉生产过程的简化模型,在Matlab中对这种控制方法进行了仿真.仿真研究表明该方法应用于焦炉控制是可行的.

     

    Abstract: Based on the heating control system of coke ovens in a certain coke oven plant,we present a genetic-algorithm-based CMAC(cerebellar model articulation controller) and PID compound control method to optimize the heating control of coke ovens.We use genetic algorithm to optimize the initial parameters of the PID controller,and then combine the CMAC network to perform the control process.For the simplified coke oven model,we simulate the neural adaptive control method in Matlab,and the simulation results show that it is feasible to apply this method to coke oven control.

     

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